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.

Multi-omics profiling of CHO parental hosts reveals cell line-specific variations in bioprocessing traits.

Chinese hamster ovary (CHO) cells are the most prevalent mammalian cell factories for producing recombinant therapeutic proteins due to their ability to synthesize human-like post-translational modifications and ease of maintenance in suspension cultures. Currently, a wide variety of CHO host cell lines has been developed; substantial differences exist in their phenotypes even when transfected with the same target vector. However, relatively less is known about the influence of their inherited genetic heterogeneity on phenotypic traits and production potential from the bioprocessing point of view. Herein, we present a global transcriptome and proteome profiling of three commonly used parental cell lines (CHO-K1, CHO-DXB11, and CHO-DG44) in suspension cultures and further report their growth-related characteristics, and N- and O-glycosylation patterns of host cell proteins (HCPs). The comparative multi-omics and subsequent genome-scale metabolic network model-based enrichment analyses indicated that some physiological variations of CHO cells grown in the same media are possibly originated from the genetic deficits, particularly in the cell-cycle progression. Moreover, the dihydrofolate reductase deficient DG44 and DXB11 possess relatively less active metabolism when compared to K1 cells. The protein processing abilities and the N- and O-glycosylation profiles also differ significantly across the host cell lines, suggesting the need to select host cells in a rational manner for the cell line development on the basis of recombinant protein being produced.

Comparative phenotypic analysis of CHO clones and culture media for lactate shift.

We explored the effects of media and clonal variation on the lactate shift which can be considered as one of the desirable features in CHO cell culture. Various culture profiles with the specific growth and antibody production rates under three different media conditions in two CHO producing clones were evaluated by resorting to multivariate statistical analysis. In most cases, glutamine depletion coincided with lactate consumption, suggesting that glutaminolysis rather than glycolysis was the preferred pathway for the pyruvate supply toward lactate production. With respect to the lactate shift, high performing medium showed higher glutamate uptake, higher aspartate secretion and lower serine uptake compared to other media conditions. In addition, clone itself exhibited the desired lactate consumption more consistently accompanying with distinguishing phenotype. The clone exhibiting lactate shift produced lesser lactate in exponential phase but two-fold higher non-toxic alanine, thus leading to better culture environment. Thus, we understand the balanced selection of clone and media composition enables cells to utilize the metabolic pathways for the desired lactate shift.

Kinetic Modeling of Mammalian Cell Culture Bioprocessing: The Quest to Advance Biomanufacturing.

Kinetic modeling is the most suitable framework to describe the dynamic behavior of mammalian cell culture although its industrial application is still in its infancy. Herein, the authors reviewed mammalian bioprocess relevant kinetic models, and found that the simple unstructured-unsegregated approach utilizing empirical Monod-type kinetics based on limiting substrates and inhibitory metabolites is commonly used due to its traceability and simple formalism. Notably, the available kinetic models are typically small to moderate in size, and the development of large-scale models is severely hampered by the scarcity of kinetic data and limitations in current parameter estimation methods. The recent availability of abundant high-throughput multi-omics datasets from mammalian cell cultures have now paved the way to improve parameterization of kinetic models, and integrate regulatory, signaling, and product quality related intracellular events, as well as cellular metabolism within the modeling framework. Ultimately, the authors foresee that multi-scale modeling is the way forward in building predictive kinetic models of mammalian cell culture to advance biomanufacturing.

A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism.

Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

Recon 2.2: from reconstruction to model of human metabolism.

INTRODUCTION: The human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed. OBJECTIVES: We report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources. METHODS: Recon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions. RESULTS: Recon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources. CONCLUSION: Through these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001).

Multi-omics data driven analysis establishes reference codon biases for synthetic gene design in microbial and mammalian cells.

In this study, we analyzed multi-omics data and subsets thereof to establish reference codon usage biases for codon optimization in synthetic gene design. Specifically, publicly available genomic, transcriptomic, proteomic and translatomic data for microbial and mammalian expression hosts, Escherichia coli, Saccharomyces cerevisiae, Pichia pastoris and Chinese hamster ovary (CHO) cells, were compiled to derive their individual codon and codon pair frequencies. Then, host dependent and -omics specific codon biases were generated and compared by principal component analysis and hierarchical clustering. Interestingly, our results indicated the similar codon bias patterns of the highly expressed transcripts, highly abundant proteins, and efficiently translated mRNA in microbial cells, despite the general lack of correlation between mRNA and protein expression levels. However, for CHO cells, the codon bias patterns among various -omics subsets are not distinguishable, forming one cluster. Thus, we further investigated the effect of different input codon biases on codon optimized sequences using the codon context (CC) and individual codon usage (ICU) design parameters, via in silico case study on the expression of human IFNγ sequence in CHO cells. The results supported that CC is more robust design parameter than ICU for improved heterologous gene design.

How does mild hypothermia affect monoclonal antibody glycosylation?

The application of mild hypothermic conditions to cell culture is a routine industrial practice used to improve recombinant protein production. However, a thorough understanding of the regulation of dynamic cellular processes at lower temperatures is necessary to enhance bioprocess design and optimization. In this study, we investigated the impact of mild hypothermia on protein glycosylation. Chinese hamster ovary (CHO) cells expressing a monoclonal antibody (mAb) were cultured at 36.5°C and with a temperature shift to 32°C during late exponential/early stationary phase. Experimental results showed higher cell viability with decreased metabolic rates. The specific antibody productivity increased by 25% at 32°C and was accompanied by a reduction in intracellular nucleotide sugar donor (NSD) concentrations and a decreased proportion of the more processed glycan structures on the mAb constant region. To better understand CHO cell metabolism at 32°C, flux balance analysis (FBA) was carried out and constrained with exometabolite data from stationary phase of cultures with or without a temperature shift. Estimated fluxomes suggested reduced fluxes of carbon species towards nucleotide and NSD synthesis and more energy was used for product formation. Expression of the glycosyltransferases that are responsible for N-linked glycan branching and elongation were significantly lower at 32°C. As a result of mild hypothermia, mAb glycosylation was shown to be affected by both NSD availability and glycosyltransferase expression. The combined experimental/FBA approach generated insight as to how product glycosylation can be impacted by changes in culture temperature. Better feeding strategies can be developed based on the understanding of the metabolic flux distribution.

A framework for the systematic design of fed-batch strategies in mammalian cell culture.

A methodology to calculate the required amount of amino acids (a.a.) and glucose in feeds for animal cell culture from monitoring their levels in batch experiments is presented herein. Experiments with the designed feeds on an antibody-producing Chinese hamster ovary cell line resulted in a 3-fold increase in titer compared to batch culture. Adding 40% more nutrients to the same feed further increases the yield to 3.5 higher than in batch culture. Our results show that above a certain threshold there is no linear correlation between nutrient addition and the integral of viable cell concentration. In addition, although high ammonia levels hinder cell growth, they do not appear to affect specific antibody productivity, while we hypothesize that high extracellular lactate concentration is the cause for the metabolic shift towards lactate consumption for the cell line used. Overall, the performance of the designed feeds is comparable to that of a commercial feed that was tested in parallel. Expanding this approach to more nutrients, as well as changing the ratio of certain amino acids as informed by flux balance analysis, could achieve even higher yields.

Comparative analysis of amino acid metabolism and transport in CHO variants with different levels of productivity.

Chinese hamster ovary (CHO) cells are widely used for the production of biopharmaceuticals; however, our understanding of several physiological elements that contribute to productivity is limited. One of these is amino acid transport and how its limitation and/or regulation might affect productivity. To further our understanding, we have examined the expression of 40 mammalian amino acid transporter genes during batch cultures of three CHO cell lines: a non-producer and two antibody-producing cell lines with different levels of productivity. In parallel, extracellular and intracellular levels of amino acids were quantified. The aim was to identify differences in gene regulation between cell lines and within culture. Our results show that three transporters associated with transport of taurine and ß-alanine, acidic amino acids and branched chain amino acids, are highly upregulated in both antibody-producing cell lines but not in the non-producer. Additionally, genes associated with the transport of amino acids related to the glutathione pathway (alanine, cysteine, cystine, glycine, glutamate) were found to be highly upregulated during the stationary phase of cell culture, correlating well with literature data on the importance of the pathway. Our analysis highlights potential markers for cell line selection and targets for process optimization.

An optimized method for extraction and quantification of nucleotides and nucleotide sugars from mammalian cells.

Glycosylation is a critical attribute of therapeutic proteins given its impact on the clinical safety and efficacy of these molecules. The biochemical process of glycosylation is inextricably dependent on metabolism and ensuing availability of nucleotides and nucleotide sugars (NSs) during cell culture. Herein, we present a comprehensive methodology to extract and quantify these metabolites from cultured cells. To establish the full protocol, two methods for the extraction of these compounds were evaluated for efficiency, and the requirement for quenching and washing the sample was assessed. A chromatographic method based on anion exchange has been optimized to separate and quantify eight nucleotides and nine NSs in less than 30 min. Degradation of nucleotides and NSs under extraction conditions was evaluated to aid in selection of the most efficient extraction protocol. We conclude that the optimized chromatographic method is quick, robust, and sensitive for quantifying nucleotides and NSs. Furthermore, our results show that samples taken from cell culture should be treated with 50% v/v acetonitrile and do not require quenching or washing for reliable extraction of nucleotides and NSs. This comprehensive protocol should prove useful in determining the impact of nucleotide and NS metabolism on protein glycosylation.

Analysis of the landscape of biologically-derived pharmaceuticals in Europe: dominant production systems, molecule types on the rise and approval trends.

A thorough sort of the human drugs approved by the European Medicines Agency (EMA) between its establishment in 1995 until June 2012 is presented herein with a focus on biologically-derived pharmaceuticals. Over 200 (33%) of the 640 approved therapeutic drugs are derived from natural sources, produced via recombinant DNA technology, or generated through virus propagation. A breakdown based on production method, type of molecule and therapeutic category is presented. Current EMA approvals demonstrate that mammalian cells are the only choice for glycoprotein drugs, with Chinese hamster ovary cells being the dominant hosts for their production. On the other hand, bacterial cells and specifically Escherichia coli are the dominant hosts for protein-based drugs, followed by the yeast Saccharomyces cerevisiae. The latter is the dominant host for recombinant vaccine production, although egg-based production is still the main platform of vaccine provision. Our findings suggest that the majority of biologically-derived drugs are prescribed for cancer and related conditions, as well as the treatment of diabetes. The approval rate for biologically-derived drugs shows a strong upward trend for monoclonal antibodies and fusion proteins since 2009, while hormones, antibodies and growth factors remain the most populous categories. Despite a clear pathway for the approval of biosimilars set by the EMA and their potential to drive sales growth, we have only found approved biosimilars for three molecules. In 2012 there appears to be a slow-down in approvals, which coincides with a reported decline in the growth rate of biologics sales.

Metabolic network reconstruction: advances in in silico interpretation of analytical information.

Mathematical modelling is a powerful tool for the organisation and analysis of biological data. Both stoichiometric and kinetic models have been applied to the investigation of cellular metabolism in a variety of bacterial, yeast and mammalian hosts to elucidate metabolic network structure, optimise fermentation conditions and improve genetic engineering strategies among others. The current challenge is to interrelate different levels of information, from the genome to the transcriptome, the proteome and the metabolome, and experimental data from widely used high-throughput techniques to recreate a given phenotype and ultimately to make predictions about network and cellular behaviour.

Carbohydrate esterases of family 2 are 6-O-deacetylases.

Three acetyl esterases (AcEs) from the saprophytic bacteria Cellvibrio japonicus and Clostridium thermocellum, members of the carbohydrate esterase (CE) family 2, were tested for their activity against a series of model substrates including partially acetylated gluco-, manno- and xylopyranosides. All three enzymes showed a strong preference for deacetylation of the 6-position in aldohexoses. This regioselectivity is different from that of typical acetylxylan esterases (AcXEs). In aqueous medium saturated with vinyl acetate, the CE-2 enzymes catalyzed transacetylation to the same position, i.e., to the primary hydroxyl group of mono- and disaccharides. Xylose and xylooligosaccharides did not serve as acetyl group acceptors, therefore the CE-2 enzymes appear to be 6-O-deacetylases.