A modeling framework for the study of protein glycosylation

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

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

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.

Identification and characterization of N-glycosylation site on a Mucor circinelloides aspartic protease expressed in Pichia pastoris: effect on secretion, activity and thermo-stability

Methylotrophic yeasts have widely been used as model organisms for understanding cellular functions and biochemical activities in lower eukaryotes. The gene encoding an aspartic protease (MCAP) from Mucor circinelloides DSM 2183 was cloned and expressed into Pichia pastoris using both the native M. circinelloides signal peptide (mcSP) and α-factor secretion signal from Saccharomyces cerevisiae (α-MF). When expressed in P. pastoris using α-MF and mcSP, MCAP was secreted into the culture medium at a concentration 200 mg L-1 (410 MCU mL-1) and 110 mg L-1 (249 MCU mL-1), respectively. The SDS-PAGE analysis of each culture shows that the protein was secreted in the media in two forms with molecular weights of approximately 33 and 37 kDa. Upon digestion using endoglycosidase H (Endo H), only one band at 33 kDa was observed, indicating that the protein might be glycosylated. One putative N-glycosylation site was found and a site-directed mutagenesis at position Asn331-Gln of the sequence produce only one form of the protein of 33 kDa, similar to that obtained when digested with Endo H. The optimum temperature and pH activity of the expressed MCAP was found to be at 60 °C and 3.6, respectively.

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.

Controlling the time evolution of mAb N-linked glycosylation - Part II: Model-based predictions

N-linked glycosylation is known to be a crucial factor for the therapeutic efficacy and safety of monoclonal antibodies (mAbs) and many other glycoproteins. The nontemplate process of glycosylation is influenced by external factors which have to be tightly controlled during the manufacturing process. In order to describe and predict mAb N-linked glycosylation patterns in a CHO-S cell fed-batch process, an existing dynamic mathematical model has been refined and coupled to an unstructured metabolic model. High-throughput cell culture experiments carried out in miniaturized bioreactors in combination with intracellular measurements of nucleotide sugars were used to tune the parameter configuration of the coupled models as a function of extracellular pH, manganese and galactose addition. The proposed modeling framework is able to predict the time evolution of N-linked glycosylation patterns during a fed-batch process as a function of time as well as the manipulated variables. A constant and varying mAb N-linked glycosylation pattern throughout the culture were chosen to demonstrate the predictive capability of the modeling framework, which is able to quantify the interconnected influence of media components and cell culture conditions. Such a model-based evaluation of feeding regimes using high-throughput tools and mathematical models gives rise to a more rational way to control and design cell culture processes with defined glycosylation patterns. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1135-1148, 2016.

Comprehensive analysis of the N-glycan biosynthetic pathway using bioinformatics to generate UniCorn: A theoretical N-glycan structure database

Glycan structures attached to proteins are comprised of diverse monosaccharide sequences and linkages that are produced from precursor nucleotide-sugars by a series of glycosyltransferases. Databases of these structures are an essential resource for the interpretation of analytical data and the development of bioinformatics tools. However, with no template to predict what structures are possible the human glycan structure databases are incomplete and rely heavily on the curation of published, experimentally determined, glycan structure data. In this work, a library of 45 human glycosyltransferases was used to generate a theoretical database of N-glycan structures comprised of 15 or less monosaccharide residues. Enzyme specificities were sourced from major online databases including Kyoto Encyclopedia of Genes and Genomes (KEGG) Glycan, Consortium for Functional Glycomics (CFG), Carbohydrate-Active enZymes (CAZy), GlycoGene DataBase (GGDB) and BRENDA. Based on the known activities, more than 1.1 million theoretical structures and 4.7 million synthetic reactions were generated and stored in our database called UniCorn. Furthermore, we analyzed the differences between the predicted glycan structures in UniCorn and those contained in UniCarbKB (www.unicarbkb.org), a database which stores experimentally described glycan structures reported in the literature, and demonstrate that UniCorn can be used to aid in the assignment of ambiguous structures whilst also serving as a discovery database.

A Markov chain model for N-linked protein glycosylation--towards a low-parameter tool for model-driven glycoengineering

Glycosylation is a critical quality attribute of most recombinant biotherapeutics. Consequently, drug development requires careful control of glycoforms to meet bioactivity and biosafety requirements. However, glycoengineering can be extraordinarily difficult given the complex reaction networks underlying glycosylation and the vast number of different glycans that can be synthesized in a host cell. Computational modeling offers an intriguing option to rationally guide glycoengineering, but the high parametric demands of current modeling approaches pose challenges to their application. Here we present a novel low-parameter approach to describe glycosylation using flux-balance and Markov chain modeling. The model recapitulates the biological complexity of glycosylation, but does not require user-provided kinetic information. We use this method to predict and experimentally validate glycoprofiles on EPO, IgG as well as the endogenous secretome following glycosyltransferase knock-out in different Chinese hamster ovary (CHO) cell lines. Our approach offers a flexible and user-friendly platform that can serve as a basis for powerful computational engineering efforts in mammalian cell factories for biopharmaceutical production.

Integration of systems glycobiology with bioinformatics toolboxes, glycoinformatics resources, and glycoproteomics data

The glycome constitutes the entire complement of free carbohydrates and glycoconjugates expressed on whole cells or tissues. 'Systems Glycobiology' is an emerging discipline that aims to quantitatively describe and analyse the glycome. Here, instead of developing a detailed understanding of single biochemical processes, a combination of computational and experimental tools are used to seek an integrated or 'systems-level' view. This can explain how multiple biochemical reactions and transport processes interact with each other to control glycome biosynthesis and function. Computational methods in this field commonly build in silico reaction network models to describe experimental data derived from structural studies that measure cell-surface glycan distribution. While considerable progress has been made, several challenges remain due to the complex and heterogeneous nature of this post-translational modification. First, for the in silico models to be standardized and shared among laboratories, it is necessary to integrate glycan structure information and glycosylation-related enzyme definitions into the mathematical models. Second, as glycoinformatics resources grow, it would be attractive to utilize 'Big Data' stored in these repositories for model construction and validation. Third, while the technology for profiling the glycome at the whole-cell level has been standardized, there is a need to integrate mass spectrometry derived site-specific glycosylation data into the models. The current review discusses progress that is being made to resolve the above bottlenecks. The focus is on how computational models can bridge the gap between 'data' generated in wet-laboratory studies with 'knowledge' that can enhance our understanding of the glycome.

Systems glycobiology for glycoengineering

Glycosylation serves essential functions on many proteins produced in biopharmaceutical manufacturing, making it mandatory to thoroughly consider its biogenesis during the production process. Glycoengineering efforts involve the rational design of glycosylation through adjustments in culturing conditions or genetic modifications. Computational models have been developed to aid this process, aiming to offer cheaper and faster alternatives to costly screening strategies. Recently, these models have been successfully utilized to predict glycosylation of products of industrial relevance. Furthermore, systems-level analyses of glycan diversity are elucidating deeper insights into the mechanisms underlying glycosylation. As computational models of glycosylation continue to be expanded, refined, and leveraged for detailed analysis of glycomics data, they will become invaluable resources for cell line development and glycoengineering.

Genome-scale modeling of the protein secretory machinery in yeast

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking. Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery.

Biological Insights into Therapeutic Protein Modifications throughout Trafficking and Their Biopharmaceutical Applications

Over the lifespan of therapeutic proteins, from the point of biosynthesis to the complete clearance from tested subjects, they undergo various biological modifications. Therapeutic influences and molecular mechanisms of these modifications have been well appreciated for some while remained less understood for many. This paper has classified these modifications into multiple categories, according to their processing locations and enzymatic involvement during the trafficking events. It also focuses on the underlying mechanisms and structural-functional relationship between modifications and therapeutic properties. In addition, recent advances in protein engineering, cell line engineering, and process engineering, by exploring these complex cellular processes, are discussed and summarized, for improving functional characteristics and attributes of protein-based biopharmaceutical products.

Metabolic reconstruction and flux analysis of industrial Pichia yeasts

Pichia yeasts have been recognized as important microbial cell factories in the biotechnological industry. Notably, the Pichia pastoris and Pichia stipitis species have attracted much research interest due to their unique cellular physiology and metabolic capability: P. pastoris has the ability to utilize methanol for cell growth and recombinant protein production, while P. stipitis is capable of assimilating xylose to produce ethanol under oxygen-limited conditions. To harness these characteristics for biotechnological applications, it is highly required to characterize their metabolic behavior. Recently, following the genome sequencing of these two Pichia species, genome-scale metabolic networks have been reconstructed to model the yeasts' metabolism from a systems perspective. To date, there are three genome-scale models available for each of P. pastoris and P. stipitis. In this mini-review, we provide an overview of the models, discuss certain limitations of previous studies, and propose potential future works that can be conducted to better understand and engineer Pichia yeasts for industrial applications.

Synthetic biology and metabolic engineering

Metabolic engineering emerged 20 years ago as the discipline occupied with the directed modification of metabolic pathways for the microbial synthesis of various products. As such, it deals with the engineering (design, construction, and optimization) of native as well as non-natural routes of product synthesis, aided in this task by the availability of synthetic DNA, the core enabling technology of synthetic biology. The two fields, however, only partially overlap in their interest in pathway engineering. While fabrication of biobricks, synthetic cells, genetic circuits, and nonlinear cell dynamics, along with pathway engineering, have occupied researchers in the field of synthetic biology, the sum total of these areas does not constitute a coherent definition of synthetic biology with a distinct intellectual foundation and well-defined areas of application. This paper reviews the origins of the two fields and advances two distinct paradigms for each of them: that of unit operations for metabolic engineering and electronic circuits for synthetic biology. In this context, metabolic engineering is about engineering cell factories for the biological manufacturing of chemical and pharmaceutical products, whereas the main focus of synthetic biology is fundamental biological research facilitated by the use of synthetic DNA and genetic circuits.

Invertase SUC2 Is the key hydrolase for inulin degradation in Saccharomyces cerevisiae

Specific Saccharomyces cerevisiae strains were recently found to be capable of efficiently utilizing inulin, but genetic mechanisms of inulin hydrolysis in yeast remain unknown. Here we report functional characteristics of invertase SUC2 from strain JZ1C and demonstrate that SUC2 is the key enzyme responsible for inulin metabolism in S. cerevisiae.

Databases and tools in glycobiology

Glycans are crucial to the functioning of multicellular organisms. They may also play a role as mediators between host and parasite or symbiont. As many proteins (>50%) are posttranslationally modified by glycosylation, this mechanism is considered to be the most widespread posttranslational modification in eukaryotes. These surface modifications alter and regulate structure and biological activities/functions of proteins/biomolecules as they are largely involved in the recognition process of the appropriate structure in order to bind to the target cells. Consequently, the recognition of glycans on cellular surfaces plays a crucial role in the promotion or inhibition of various diseases and, therefore, glycosylation itself is considered to be a critical protein quality control attribute for commercial therapeutics, which is one of the fastest growing segments in the pharmaceutical industry. With the development of glycobiology as a separate discipline, a number of databases and tools became available in a similar way to other well-established "omics." Alleviating the recognized shortcomings of the available tools for data storage and retrieval is one of the highest priorities of the international glycoinformatics community. In the last decade, major efforts have been made, by leading scientific groups, towards the integration of a number of major databases and tools into a single portal, which would act as a centralized data repository for glycomics, equipped with a number of comprehensive analytical tools for data systematization, analysis, and comparison. This chapter provides an overview of the most important carbohydrate-related databases and glycoinformatic tools.

Understanding glycomechanics using mathematical modeling: a review of current approaches to simulate cellular glycosylation reaction networks

Following the footsteps of genomics and proteomics, recent years have witnessed the growth of large-scale experimental methods in the field of glycomics. In parallel, there has also been growing interest in developing Systems Biology based methods to study the glycome. The combined goals of these endeavors is to identify glycosylation-dependent mechanisms regulating human physiology, check points that can control the progression of pathophysiology, and modifications to reaction pathways that can result in more uniform biopharmaceutical processes. In these efforts, mathematical models of N- and O-linked glycosylation have emerged as paradigms for the field. While these are relatively few in number, nevertheless, the existing models provide a basic framework that can be used to develop more sophisticated analysis strategies for glycosylation in the future. The current review surveys these computational models with focus on the underlying mathematics and assumptions, and with respect to their ability to generate experimentally testable hypotheses.

A dynamic mathematical model for monoclonal antibody N-linked glycosylation and nucleotide sugar donor transport within a maturing Golgi apparatus

Monoclonal antibodies (mAbs) are one of the most important products of the biopharmaceutical industry. Their therapeutic efficacy depends on the post-translational process of glycosylation, which is influenced by manufacturing process conditions. Herein, we present a dynamic mathematical model for mAb glycosylation that considers cisternal maturation by approximating the Golgi apparatus to a plug flow reactor and by including recycling of Golgi-resident proteins (glycosylation enzymes and transport proteins [TPs]). The glycosylation reaction rate expressions were derived based on the reported kinetic mechanisms for each enzyme, and transport of nucleotide sugar donors [NSDs] from the cytosol to the Golgi lumen was modeled to serve as a link between glycosylation and cellular metabolism. Optimization-based methodologies were developed for estimating unknown enzyme and TP concentration profile parameters. The resulting model is capable of reproducing glycosylation profiles of commercial mAbs. It can further reproduce the effect gene silencing of the FucT glycosylation enzyme and cytosolic NSD depletion have on the mAb oligosaccharide profile. All novel elements of our model are based on biological evidence and generate more accurate results than previous reports. We therefore believe that the improvements contribute to a more detailed representation of the N-linked glycosylation process. The overall results show the potential of our model toward evaluating cell engineering strategies that yield desired glycosylation profiles. Additionally, when coupled to cellular metabolism, this model could be used to assess the effect of process conditions on glycosylation and aid in the design, control, and optimization of biopharmaceutical manufacturing processes.

Computational analysis reveals abundance of potential glycoproteins in Archaea, Bacteria and Eukarya

Glycosylation is the most common type of post-translational modification (PTM) and is known to affect protein stability, folding and activity. Inactivity of enzymes mediating glycosylation can result in serious disorders including colon cancer and brain disorders. Out of five main types of glycosylation, N-linked glycosylation is most abundant and characterized by the addition of a sugar group to an Asparagine residue at the N-X-S/T motif. Enzyme mediating such transfer is known as oligosaccharyl transferase (OST). It has been hypothesized before that a significant number of proteins serve as glycoproteins. In this study, we used programming implementations of Python to statistically quantify the representation of glycoproteins by scanning all the available proteome sequence data at ExPASy server for the presence of glycoproteins and also the enzyme which plays critical role in glycosylation i.e. OST. Our results suggest that more than 50% of the proteins carry N-X-S/T motif i.e. they could be potential glycoproteins. Furthermore, approximately 28-36% (1/3) of proteins possesses signature motifs which are characteristic features of enzyme OST. Quantifying this bias individually reveals that both the number of proteins tagged with N-X-S/T motif and the average number of motifs per protein is significantly higher in case of eukaryotes when compared to prokaryotes. In the light of these results we conclude that there is a significant bias in the representation of glycoproteins in the proteomes of all species and is manifested substantially in eukaryotes and claim for glycosylation to be the most common and ubiquitous PTM in cells, especially in eukaryotes.

Systems glycobiology: biochemical reaction networks regulating glycan structure and function

There is a growing use of bioinformatics based methods in the field of Glycobiology. These have been used largely to curate glycan structures, organize array-based experimental data and display existing knowledge of glycosylation-related pathways in silico. Although the cataloging of vast amounts of data is beneficial, it is often a challenge to gain meaningful mechanistic insight from this exercise alone. The development of specific analysis tools to query the database is necessary. If these queries can integrate existing knowledge of glycobiology, new insights may be gained. Such queries that couple biochemical knowledge and mathematics have been developed in the field of Systems Biology. The current review summarizes the current state of the art in the application of computational modeling in the field of Glycobiology. It provides (i) an overview of experimental and online resources that can be used to construct glycosylation reaction networks, (ii) mathematical methods to formulate the problem including a description of ordinary differential equation and logic-based reaction networks, (iii) optimization techniques that can be applied to fit experimental data for the purpose of model reconstruction and for evaluating unknown model parameters, (iv) post-simulation analysis methods that yield experimentally testable hypotheses and (v) a summary of available software tools that can be used by non-specialists to perform many of the above functions.

Protein glycosylation control in mammalian cell culture: past precedents and contemporary prospects

Protein glycosylation is a post-translational modification of paramount importance for the function, immunogenicity, and efficacy of recombinant glycoprotein therapeutics. Within the repertoire of post-translational modifications, glycosylation stands out as having the most significant proven role towards affecting pharmacokinetics and protein physiochemical characteristics. In mammalian cell culture, the understanding and controllability of the glycosylation metabolic pathway has achieved numerous successes. However, there is still much that we do not know about the regulation of the pathway. One of the frequent conclusions regarding protein glycosylation control is that it needs to be studied on a case-by-case basis since there are often conflicting results with respect to a control variable and the resulting glycosylation. In attempts to obtain a more multivariate interpretation of these potentially controlling variables, gene expression analysis and systems biology have been used to study protein glycosylation in mammalian cell culture. Gene expression analysis has provided information on how glycosylation pathway genes both respond to culture environmental cues, and potentially facilitate changes in the final glycoform profile. Systems biology has allowed researchers to model the pathway as well-defined, inter-connected systems, allowing for the in silico testing of pathway parameters that would be difficult to test experimentally. Both approaches have facilitated a macroscopic and microscopic perspective on protein glycosylation control. These tools have and will continue to enhance our understanding and capability of producing optimal glycoform profiles on a consistent basis.

Effect of surfactant pluronic F-68 on CHO cell growth, metabolism, production, and glycosylation of human recombinant IFN-γ in mild operating conditions

The control of glycosylation to satisfy regulatory requirements and quality consistency of recombinant proteins produced by different processes has become an important issue. With two N-glycosylation sites, γ-interferon (IFN-γ) can be seen as a prototype of a recombinant therapeutic glycoprotein for this purpose. The effect of the nonionic surfactant Pluronic F-68 (PF-68) on cell growth and death was investigated, as well as production and glycosylation of recombinant IFN-γ produced by a CHO cell line that was maintained in a rich protein-free medium in the absence or presence of low agitation. Under these conditions, a dose-dependent effect of PF-68 (0-0.1%) was shown not only to significantly enhance growth but also to reduce cell lysis. Interestingly, supplementing the culture medium with PF-68 led to increased IFN-γ production as a result of both higher cell densities and a higher specific production rate of IFN-γ. If cells were grown with agitation, lack of PF-68 in the culture medium decreased the fraction of the fully glycosylated IFN-γ glycoform (2N) from 80% to 65-70% during the initial period. This effect appeared to be due to a lag phase in cell growth observed during this period. Finally, a global kinetic study of CHO cell metabolism indicated higher efficiency in the utilization of the two major carbon substrates when cultures were supplemented with PF-68. Therefore, these results highlight the importance of understanding how media surfactant can affect cell growth as well as cell death and the product quality of a recombinant glycoprotein expressed in CHO cell cultures.

Genome-scale metabolic reconstruction and in silico analysis of methylotrophic yeast Pichia pastoris for strain improvement

Background

Pichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism.

Results

A fully compartmentalized metabolic model of P. pastoris (iPP668), composed of 1,361 reactions and 1,177 metabolites, was reconstructed based on its genome annotation and biochemical information. The constraints-based flux analysis was then used to predict achievable growth rate which is consistent with the cellular phenotype of P. pastoris observed during chemostat experiments. Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins. Interestingly, methanol consumption yields a high regeneration rate of reducing equivalents which is substantial for the synthesis of valuable pharmaceutical precursors. Hence, as a case study, we examined the applicability of P. pastoris system to whole-cell biotransformation and also identified relevant metabolic engineering targets that have been experimentally verified.

Conclusion

The genome-scale metabolic model characterizes the cellular physiology of P. pastoris, thus allowing us to gain valuable insights into the metabolism of methylotrophic yeast and devise possible strategies for strain improvement through in silico simulations. This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network to enhance humanized glycoprotein production.

Synthesis, purification and characterization of recombinant glycosylated human prolactin (G-hPRL) secreted by cycloheximide-treated CHO cells

Human prolactin (hPRL) is a 199 aminoacid protein hormone with a wide spectrum of biological activities which is best known for its stimulation of lactation and development of mammary gland. This protein contains only one potential asparagine-linked glycosylation site, which is partially (10-30%) occupied when the protein is synthesized in eukaryotic cells. Although the biological activity of glycosylated hPRL (G-hPRL) has been found to be approximately 4-fold lower than that of hPRL, its physiological function is not yet well defined. In order to better characterize and study this hormone variant, we carried out its laboratory scale purification from conditioned medium of genetically modified CHO cells that had been supplemented with cycloheximide. Addition of cycloheximide increased the absolute concentration of G-hPRL approximately 4-fold and the glycosylated versus non-glycosylated hPRL concentration ratio by approximately 7-fold. G-hPRL purification was carried out via a two-step process based on a cationic exchanger and a size-exclusion HPLC (HPSEC) column. Characterization was carried out by HPSEC, Western blotting, MALDI-TOF-MS and in vitro bioassay based on Nb2 and Ba/F3-LLP cells, the biological activity being of the same order (11-15 IU mg(-1)) in the two assays. Our results show that addition of cycloheximide can be an important strategy for increasing glycosylated protein production, facilitating the purification and characterization of these isoforms.

Identification of cell culture conditions to control N-glycosylation site-occupancy of recombinant glycoproteins expressed in CHO cells

The effect of different cell culture conditions on N-glycosylation site-occupancy has been elucidated for two different recombinant glycoproteins expressed in Chinese hamster ovary (CHO) cells, recombinant human tissue plasminogen activator (t-PA) and a recombinant enzyme (glycoprotein 2-GP2). Both molecules contain a N-glycosylation site that is variably occupied. Different environmental factors that affect the site-occupancy (the degree of occupied sites) of these molecules were identified. Supplementing the culture medium with additional manganese or iron increased the fraction of fully occupied t-PA (type I t-PA) by approximately 2.5-4%. Decreasing the cultivation temperature from 37 to 33 degrees C or 31 degrees C gradually increased site-occupancy of t-PA up to 4%. The addition of a specific productivity enhancer, butyrate, further increased site-occupancy by an additional 1% under each cultivation temperature tested. In addition, the thyroid hormones triiodothyronine and thyroxine increased site-occupancy of t-PA compared to control conditions by about 2%. In contrast, the addition of relevant nucleoside precursor molecules involved in N-glycan biosynthesis (e.g., uridine, guanosine, mannose) either had no effect or slightly reduced site-occupancy. For the recombinant enzyme (GP2), it was discovered that culture pH and the timing of butyrate addition can be used to control N-glycan site-occupancy within a specific range. An increase in culture pH correlated with a decrease in site-occupancy. Similarly, delaying the timing for butyrate addition also decreased site-occupancy of this molecule. These results highlight the importance of understanding how cell culture conditions and media components can affect the product quality of recombinant glycoproteins expressed in mammalian cell cultures. Furthermore, the identification of relevant factors will enable one to control product quality attributes, specifically N-glycan site-occupancy, within a specific range when applied appropriately.

Systems-level modeling of cellular glycosylation reaction networks: O-linked glycan formation on natural selectin ligands

MOTIVATION

The emerging field of Glycomics requires the development of systems-based modeling strategies to relate glycosyltransferase gene expression and enzyme activity with carbohydrate structure and function.

RESULTS

We describe the application of object oriented programming concepts to define glycans, enzymes, reactions, pathways and compartments for modeling cellular glycosylation reaction networks. These class definitions are combined with current biochemical knowledge to define potential reaction networks that participate in the formation of the sialyl Lewis-X (sLe(X)) epitope on O-glycans linked to a leukocyte cell-surface glycoprotein, P-selectin Glycoprotein Ligand-1 (PSGL-1). Subset modeling, hierarchical clustering, principal component analysis and adjoint sensitivity analysis are applied to refine the reaction network and to quantify individual glycosyltransferase rate constants. Wet-lab experiments validate estimates from computer modeling. Such analysis predicts that sLe(X) expression varies directly with sialyltransferase alpha2,3ST3Gal-IV expression and inversely with alpha2,3ST3Gal-I/II.

AVAILABILITY

SBML files for all converged models are available at http://www.eng.buffalo.edu/~neel/bio_reaction_network.html

Influence of intracellular nucleotide and nucleotide sugar contents on recombinant interferon-gamma glycosylation during batch and fed-batch cultures of CHO cells

Both the macroheterogeneity of recombinant human IFN-gamma produced by CHO cells and intracellular levels of nucleotides and sugar nucleotides, have been characterized during batch and fed-batch cultures carried out in different media. Whereas PF-BDM medium was capable to maintain a high percentage of the doubly- glycosylated glycoforms all over the process, mono-glycosylated and non-glycosylated forms increased during the batch culture using SF-RPMI medium. Intracellular level of UTP was higher in PF-BDM all over the batch culture compared to the SF-RPMI process. UDP-Gal accumulated only during the culture performed in PF-BDM medium, probably as a consequence of the reduced UDP-Glc synthesis flux in SF-RPMI medium. When the recombinant CHO cells were cultivated in fed-batch mode, the UTP level remained at a relatively high value in serum-containing RPMI and its titer increased during the fed-phase indicating an excess of biosynthesis. Besides, an accumulation of UDP-Gal occurred as well. Those results all together indicate that UTP and UDP-Glc syntheses in CHO cells cultivated in SF-RPMI medium in batch process, could be limiting during the glycosylation processes of the recombinant IFN-gamma. At last, the determination of the energetic status of the cells over the three studied processes suggested that a relationship between the adenylate energy charge and the glycosylation macroheterogeneity of the recombinant IFN-gamma may exist.

RNA interference of sialidase improves glycoprotein sialic acid content consistency

An important challenge facing therapeutic protein production in mammalian cell culture is the cleavage of terminal sialic acids on recombinant protein glycans by the glycosidase enzymes released by lysed cells into the supernatant. This undesired phenomenon results in a protein product which is rapidly cleared from the plasma by asialoglycoprotein receptors in the liver. In this study, RNA interference was utilized as a genetic approach to silence the activity of sialidase, a glycosidase responsible for cleaving terminal sialic acids on IFN-gamma produced by Chinese Hamster Ovary (CHO) cells. We first identified a 21-nt double stranded siRNA that reduced endogenous sialidase mRNA and protein activity levels. Potency of each siRNA sequences was compared using real time RT-PCR and a sialidase activity assay. We next integrated the siRNA sequence into CHO cells, allowing production and selection of stable cell lines. We isolated stable clones with sialidase activity reduced by over 60% as compared to the control cell line. Micellar electrokinetic chromatography (MEKC), thiobarbituric acid assay (TAA), and high performance anion exchange chromatography (HPAEC) coupled to amperometric detection were performed to analyze glycan site occupancy, sialic acid content, and distribution of asialo-/sialylated-glycan structures, respectively. Two of the stable clones successfully retained the full sialic acid content of the recombinant IFN-gamma, even upon cells' death. This was comparable to the case where a chemically synthesized sialidase inhibitor was used. These results demonstrated that RNA interference of sialidase can prevent the desialylation problem in glycoprotein production, resulting improved protein quality during the entire cell culture process.

Expression of heterologous proteins in Pichia pastoris: a useful experimental tool in protein engineering and production

The use of the methylotrophic yeast, Pichia pastoris, as a cellular host for the expression of recombinant proteins has become increasing popular in recent times. P. pastoris is easier to genetically manipulate and culture than mammalian cells and can be grown to high cell densities. Equally important, P. pastoris is also a eukaryote, and thereby provides the potential for producing soluble, correctly folded recombinant proteins that have undergone all the post-translational modifications required for functionality. Additionally, linearized foreign DNA can be inserted in high efficiency via homologous recombination procedures to generate stable cell lines whilst expression vectors can be readily prepared that allow multiple copies of the target protein, multimeric proteins with different subunit structures, or alternatively the target protein and its cognate binding partners, to be expressed. A further benefit of the P. pastoris system is that strong promoters are available to drive the expression of a foreign gene(s) of interest, thus enabling production of large amounts of the target protein(s) with relative technical ease and at a lower cost than most other eukaryotic systems. The purpose of this review is to summarize important developments and features of this expression system and, in particular, to examine from an experimental perspective the genetic engineering, protein chemical and molecular design considerations that have to be taken into account for the successful expression of the target recombinant protein. Included in these considerations are the influences of P. pastoris strain selection; the choice of expression vectors and promoters; procedures for the transformation and integration of the vectors into the P. pastoris genome; the consequences of rare codon usage and truncated transcripts; and techniques employed to achieve multi-copy integration numbers. The impact of the alcohol oxidase (AOX) pathways in terms of the mut+ and mut(s) phenotypes, intracellular expression and folding pathways is examined. The roles of pre-pro signal sequences such as the alpha mating factor (alpha-MF) and the Glu-Ala repeats at the kex2p cleavage site on the processing of the protein translate(s) have also been considered. Protocols for the generation of protein variants and mutants for screening for orphan cognate binding partners and the use of experimental platforms addressing the molecular recognition behaviour of recombinant proteins such as the extracellular domains of transmembrane receptors with their physiological ligands are also described. Finally, the palindromic patterns of glycosylation that can occur with these expression systems, in terms of the role and location of the sequon in the primary structure, the number of mannose units and the types of oligosaccharides incorporated as Asn- or O-linkages and their impact on the thermostability and immunogenicity of the recombinant protein are considered. Procedures to prevent glycosylation through manipulation of cell culture conditions or via enzymatic and site-directed mutagenesis methods are also discussed.

Effect of shear stress on intrinsic CHO culture state and glycosylation of recombinant tissue-type plasminogen activator protein

Shear stress in suspension culture was investigated as a possible manipulative parameter for the control of glycosylation of the recombinant tissue-type plasminogen activator protein (r-tPA) produced by recombinant Chinese hamster ovary (CHO) cell culture, grown in protein-free media. Resulting fractions of partially glycosylated, Type II, and fully glycosylated, Type I, r-tPA protein were monitored as a direct function of the shear characteristics of the culture environment. The shear-induced response of CHO culture to levels of low shear stress, where exponential growth was not obtained, and to higher levels of shear stress, which resulted in extensive cell death, were examined through manipulation of the bioreactor stirring velocity. Both apparent and intrinsic cell growth, metabolite consumption, byproduct and r-tPA production, and r-tPA glycosylation, from a variable site-occupancy standpoint, were monitored throughout. Kinetic analyses revealed a shear-stress-induced alteration of cellular homeostasis resulting in a nonlinear dependency of metabolic yield coefficients and an intrinsic cell lysis kinetic constant on shear stress. Damaging levels of shear stress were used to investigate the shear dependence of cell death and lysis, as well as the effects on the intrinsic growth rate of the culture. Kinetic models were also developed on the basis of the intrinsic state of the culture and compared to traditional models. Total r-tPA production was maximized under moderate shear conditions, as was the viable CHO cell density of the culture. However, Type II r-tPA production and the fraction of Type II glycoform production ratio was maximized under damaging levels of shear stress. Analyses of biomass production yield coefficients coupled with a plug-flow reactor model of glycan addition in the endoplasmic reticulum (ER) were used to propose an overall mechanism of decreased r-tPA protein site-occupancy glycosylation with increasing shear stress. Decreased residence time of r-tPA in the ER as a result of increased protein synthesis related to shear protection mechanisms is proposed to limit contact of site Asn184 with the membrane-bound oligosaccharyltransferase enzyme in the ER.

Extensive N-glycosylation reduces the thermal stability of a recombinant alkalophilic bacillus alpha-amylase produced in Pichia pastoris

Alkalophilic Bacillus alpha-amylase (ABA) was produced in the yeast Pichia pastoris with a yield of 50 mg L(-1) of culture supernatant. The recombinant protein, rABA, was glycosylated at seven of the nine sites for potential N-glycosylation as identified by automated peptide sequencing and MALDI-TOF MS of tryptic fragments. The number of hexose units within each glycan chain was found to vary from 8 to 18 as calculated from the masses of glycosylated peptide fragments. Temperature stability measurements in the absence of substrate showed that the T(50) of glycosylated rABA and its endoglycosidase H-deglycosylated form was 76 degrees C while that of ABA purified from Bacillus was 89 degrees C thus demonstrating that the original temperature stability of ABA was not retained by rABA. The relative thermoperformance, i.e., the activity at 80 degrees C relative to that at 37 degrees C was 0.9 +/- 0.3 for rABA. Removal of all seven N-linked glycans by endoglycosidase H increased the relative thermoperformance to 2.4 +/- 0.6, compared to the value of 3.5 +/- 1.1 for ABA. Thus, removal of the N-linked glycans did not improve the thermostability of rABA but modified its thermoperformance to approach that of the original Bacillus enzyme. rABA had the highest activity around pH 6. Treatment of rABA with endoglycosidase H shifted the pH activity profile in a more alkaline direction approaching the pH activity profile of ABA.

Differential glycosylation produces heterogeneity in elevated esterases associated with insecticide resistance in the brown planthopper Nilaparvata lugens Stål

The major insecticide resistance mechanism in the brown planthopper Nilaparvata lugens involves overproduction of esterases. Esterases purified from a resistant strain appeared as a ladder of bands on isoelectric focussing (IEF) gels from pI 4.7 to 5.0. Two-dimensional electrophoresis showed that isozymes ranged in size from 66 to 68 kDa with those of lower pI being apparently smaller. All isozymes detected by two-dimensional electrophoresis were glycosylated. N-glycosidase A reduced the number of isozymes on IEF to two, with increased pI and an increased molecular weight of 69 kDa. No O-linked glycans were detected. Deglycosylation had no effect on esterase activity, hence glycosylation is not involved in active site conformation. As N-glycosidase F completely deglycosylated the esterases, none of the glycans has an alpha1,3-bound core fucose. Reactivity with the lectins GNA, MAA and DSA, combined with differential cleavage of N-linked glycans with endoglycosidases F1 and F2, indicated that terminally linked mannose is present in high mannose and/or hybrid type glycans and that terminally linked sialic acid and galactose-beta(1-4)-N-acetylglucosamine are present in biantennary complexes. Neuraminidase treatment had the same effect on pI of isozymes as complete deglycosylation. Therefore, the majority of the heterogeneity of elevated esterases on IEF is due to differential attachment of sialic acid to glycans of the two proteins.

Metabolic effects on recombinant interferon-gamma glycosylation in continuous culture of Chinese hamster ovary cells

Asparagine linked (N-linked) glycosylation is an important modification of recombinant proteins, because the attached oligosaccharide chains can significantly alter protein properties. Potential glycosylation sites are not always occupied with oligosaccharide, and site occupancy can change with the culture environment. To investigate the relationship between metabolism and glycosylation site occupancy, we studied the glycosylation of recombinant human interferon-gamma (IFN-gamma) produced in continuous culture of Chinese hamster ovary cells. Intracellular nucleotide sugar levels and IFN-gamma glycosylation were measured at different steady states which were characterized by central carbon metabolic fluxes estimated by material balances and extracellular metabolite rate measurements. Although site occupancy varied over a rather narrow range, we found that differences correlated with the intracellular pool of UDP-N-acetylglucosamine + UDP-N-acetylgalactosamine (UDP-GNAc). Measured nucleotide levels and estimates of central carbon metabolic fluxes point to UTP depletion as the cause of decreased UDP-GNAc during glucose limitation. Glucose limited cells preferentially utilized available carbon for energy production, causing reduced nucleotide biosynthesis. Lower nucleoside triphosphate pools in turn led to lower nucleotide sugar pools and reduced glycosylation site occupancy. Subsequent experiments in batch and fed-batch culture have confirmed that UDP-sugar concentrations are correlated with UTP levels in the absence of glutamine limitation. Glutamine limitation appears to influence glycosylation by reducing amino sugar formation and hence UDP-GNAc concentration. The influence of nucleotide sugars on site occupancy may only be important during periods of extreme starvation, since relatively large changes in nucleotide sugar pools led to only minor changes in glycosylation.

Monitoring recombinant human interferon-gamma N-glycosylation during perfused fluidized-bed and stirred-tank batch culture of CHO cells

Chinese hamster ovary cells producing recombinant human interferon-gamma were cultivated for 500 h attached to macroporous microcarriers in a perfused, fluidized-bed bioreactor, reaching a maximum cell density in excess of 3 x 10(7) cells (mL microcarrier)-1 at a specific growth rate (mu) of 0.010 h-1. During establishment of the culture, the N-glycosylation of secreted recombinant IFN-gamma was monitored by capillary electrophoresis of intact IFN-gamma proteins and by HPLC analysis of released N-glycans. Rapid analysis of IFN-gamma by micellar electrokinetic capillary chromatography resolved the three glycosylation site occupancy variants of recombinant IFN-gamma (two Asn sites occupied, one Asn site occupied and nonglycosylated) in under 10 min per sample; the relative proportions of these variants remained constant during culture. Analysis of IFN-gamma by capillary isoelectric focusing resolved at least 11 differently sialylated glycoforms over a pI range of 3.4 to 6.4, enabling rapid quantitation of this important source of microheterogeneity. During perfusion culture the relative proportion of acidic IFN-gamma proteins increased after 210 h of culture, indicative of an increase in N-glycan sialylation. This was confirmed by cation-exchange HPLC analysis of released, fluorophore-labeled N-glycans, which showed an increase in the proportion of tri- and tetrasialylated N-glycans associated with IFN-gamma during culture, with a concomitant decrease in the proportion of monosialylated and neutral N-glycans. Comparative analyses of IFN-gamma produced by CHO cells in stirred-tank culture showed that N-glycan sialylation was stable until late in culture, when a decline in sialylation coincided with the onset of cell death and lysis. This study demonstrates that different modes of capillary electrophoresis can be employed to rapidly and quantitatively monitor the main sources of glycoprotein variation, and that the culture system and operation may influence the glycosylation of a recombinant glycoprotein.