Application of a genome-based predictive CHO model for increased mAb production and Glycosylation control

Monoclonal antibody therapeutics continue to grow in both number and market share with recent forecasts of global sales reaching ~$125MM by 2020. Most mAb products currently on the market are produced using cultured mammalian cells, typically Chinese Hamster Ovary (CHO) cells, which provide the necessary post-translational modifications to make the antibody efficacious. Many post-translational modifications such as the oligosaccharide profile are considered critical quality attributes (CQAs) that must be tightly controlled throughout the manufacturing process to ensure product safety and effectiveness. Therefore, the ability to predict how cell culture media components, including potential contaminants like trace metals, will affect product formation and glycosylation is important from both a process development and process control viewpoint. A detailed genome-based, predictive CHO model from the Insilico Cells™ library was adapted by the reconstruction software Insilico Discovery™ for a representative fed-batch process through a collaborative effort leveraging the computational and experimental expertise of two companies. The final, compartmentalized network model contained 1900 reactions (including transport reactions), 1300 compounds and contains stoichiometric descriptions of anabolic pathways for amino acids, lipids and carbohydrate species. The genome-scale model was constrained using several assumptions on the cell physiology and then used to compute time-resolved flux distributions by the software module Insilico Inspector™. The Insilico Designer™ module was then used to subsequently reduce the large model to a computationally manageable reduced model able to describe all flux distributions using 5 flux modes, of which 4 combined several metabolic functions and one is independently responsible for product synthesis. Using Insilico Designer™, the kinetic parameters of the reduced model were estimated by fitting the model-predicted metabolite concentrations to the experimentally determined values. The calibrated model was able to properly describe the time-dependent trajectories of biomass, product and most metabolites. Simulations using the reduced model were run and a media composition predicted to improve mAb production was identified and experimentally verified. Furthermore, experiments probing the effects of trace metals on product glycosylation were used to extend the model’s glycosylation predictability. The ability to identify both metabolic signatures, as well as media components, that correlate to specific glycan profiles will allow for fine-tuning of desired CQAs and enable more robust control strategies in upstream processes

Systembiologie der Säugetierzellen : mathematische Modellierung zur Offenlegung metabolischer Kompartimentierung

Compartmentation contributes at controlling the mammalian metabolism and is important in aging and diseases. Systems biology methods were applied to study compartmentation between cytosol and mitochondria. A mathematical modeling platform for non-stationary 13C metabolic flux analysis (Inst-13CMFA) was developed and tested. It was then extended to model also extracellular labeling. First, fluxes were determined for the CHO-K1 cell line metabolism using only extracellular labeling and one labeled substrate. The results indicate that the cells adapt to sustain fast growth and to manage the complex media. Then, high resolution of compartment fluxes, reversibility and intracompartmental concentrations resulted by applying Inst-13CMFA to data from two labeling experiments. In both studies, pentose phosphate pathway carried a large flux. The produced NADPH is used by fatty acid synthesis and for mitigating oxidative stress. Differences in labeling were described by a model with pyruvate channeling. Selectively permeabilized CHO-K1 cells were fed mitochondrial substrates. Using the elementary mode decomposition of the mitochondrial network, the observed extracellular rates were distributed into elementary mode fluxes. This evidenced activity of pathways and regulatory effects. By combining more systems biology methods, this thesis constructed a larger picture for characterizing the complex metabolism of CHO-K1 cells and uncovered many new characterstics of metabolic compartmentation.Die Kompartimentierung des Stoffwechsels trägt dazu bei den Stoffwechsel des Säugetiers zu regulieren. Methoden aus der Systembiologie wurden angewendet um die Kompartimentierung zu untersuchen. Eine Modellierungsplattform für nichtstationäre 13C Stoffwechsel-Flussanalyse (Inst-13CMFA) wurde erarbeitet und getestet. Die Plattform wurde erweitert um Änderungen in der extrazellulären Isotopenmarkierung aufzunehmen. Flüsse wurden für die CHO-K1 Zelllinien bestimmt durch die Verwendung von extrazellulärer Markierung. Flusswerte deuten darauf hin, dass sich die Zellen hinsichtlich schnellem Wachstum und der komplexen Medienzusammensetzung anpassen. Eine hohe Auflösung von Parametern wurde erreicht, indem Inst-13CMFA auf die Daten aus zwei Markierungsexperimenten angewendet wurde. In beiden Studien trug die Pentosephosphatweg einen hohen Fluss um NADPH zur Fettsäuresynthese und um oxidativen Stress zu vermeiden. Weiterhin lieferte das Channeling von Pyruvat eine Erklärung für Unterschiede Markierungen. Selektiv permeabilisierten CHO-K1 Zellen wurden verschiedene Substrate zugeführt. Unter Anwendung der Elementarmoden Zerlegung auf das mitochondriale Netzwerk konnte die Aktivität von Stoffwechselpfaden und regulierenden Effekten belegt werden. Indem weitere Methoden der Systembiologie angewandt wurden, trägt diese Dissertation dazu bei ein umfassenderes Bild des Stoffwechsels von CHO-K1 Zellen zu erstellen. Gleichzeitig wurden neue Fragen in Bezug auf Kompartmentflüsse aufgeworfen

Non-stationary 13C metabolic flux analysis of Chinese hamster ovary cells in batch culture using extracellular labeling highlights metabolic reversibility and compartmentation

Mapping the intracellular fluxes for established mammalian cell lines becomes increasingly important for scientific and economic reasons. However, this is being hampered by the high complexity of metabolic networks, particularly concerning compartmentation.Institute of Cell Culture Technology (University Bielefeld, Germany) ; the BMBF (German Federal Ministry of Education and Research

A constraint-based modelling approach to metabolic dysfunction in Parkinson's disease

One of the hallmarks of sporadic Parkinson's disease is degeneration of dopaminergic neurons in the pars compacta of the substantia nigra. The aetiopathogenesis of this degeneration is still not fully understood, with dysfunction of many biochemical pathways in different subsystems suggested to be involved. Recent advances in constraint-based modelling approaches hold great potential to systematically examine the relative contribution of dysfunction in disparate pathways to dopaminergic neuronal degeneration, but few studies have employed these methods in Parkinson's disease research. Therefore, this review outlines a framework for future constraint-based modelling of dopaminergic neuronal metabolism to decipher the multi-factorial mechanisms underlying the neuronal pathology of Parkinson's disease