Metabolic flux analysis of CHO cells in perfusion culture by metabolite balancing and 2D [13C, 1H] COSY NMR spectroscopy |
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| Authors: | Chetan Goudar Richard Biener C. Boisart Rüdiger Heidemann James Piret Albert de Graaf Konstantin Konstantinov |
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| Affiliation: | 1. Cell Culture Development, Global Biological Development, Bayer Healthcare, 800 Dwight Way, Berkeley, CA 94710, USA;2. University of Applied Sciences Esslingen, Department of Natural Sciences, Kanalstr. 33, 73728 Esslingen, Germany;3. METabolic EXplorer SA, Biopole Clermont-Limagne, F-63360 St. Beauzire, France;4. Michael Smith Laboratories & Department of Chemical and Biological Engineering, University of British Columbia, Vancouver, BC, Canada V6T 1Z4;5. Biosciences, TNO Quality of Life, PO Box 360, 3700 AJ Zeist, Netherlands;6. Genzyme Corporation, 45 New York Ave, Framingham, MA 01701, USA;1. Chemical and Biological Engineering;2. Late Stage Cell Culture, Process R&D Genentech, Inc. 1 DNA Way, MS 32 South San Francisco CA 94080;1. Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA;2. Novo Nordisk Foundation Center for Biosustainability at the School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA;3. Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore 117585, Singapore;5. Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, 1190 Vienna, Austria;6. Austrian Centre of Industrial Biotechnology, 1190 Vienna, Austria;7. Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Corner College and Cooper Roads (Building 75), Brisbane, QLD 4072, Australia;8. Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA;9. Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla 92093, CA, USA;10. Department of Systems Biology, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark;11. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark;12. Centre for Biotechnology and Bioengineering, Department of Chemical Engineering and Biotechnology, University of Chile, Santiago 8370456, Chile;13. MATHomics, Center for Mathematical Modeling; Center for Genome Regulation (Fondap 15090007), University of Chile, Santiago 8370456, Chile;14. Center for Systems Biology, University of Iceland, 101 Reykjavik, Iceland;15. Computational Bioscience Research Centre, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia;16. Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA;1. Institute of Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zurich, 8093 Zurich, Switzerland;2. Biotech Process Sciences, Merck Biopharma, 1804 Corsier-sur-Vevey, Switzerland;1. Biotech Process Sciences, Merck Biopharma, Corsier-sur-Vevey, Switzerland;2. Institute of Chemical and Bioengineering, Department of Chemistry and Applied Bioscences, ETH Zürich, Zürich, Switzerland;1. Cell Culture Process Development, Pfizer Inc, One Burtt Road, Andover, MA 01810, USA;2. Cell Line Development, Pfizer Inc, One Burtt Road, Andover, MA 01810, USA;1. Institute of Biochemical Engineering, University of Stuttgart, Allmandring 31, 70569, Stuttgart, Germany;2. Institute of Biomaterials and Biomolecular Systems, Department of Biobased Materials, University of Stuttgart, Pfaffenwaldring 57, 70569, Stuttgart, Germany |
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| Abstract: | The physiological state of CHO cells in perfusion culture was quantified by determining fluxes through the bioreaction network using 13C glucose and 2D-NMR spectroscopy. CHO cells were cultivated in a 2.5 L perfusion bioreactor with glucose and glutamine as the primary carbon and energy sources. The reactor was inoculated at a cell density of 8×106 cells/mL and operated at ～10×106 cells/mL using unlabeled glucose for the first 13 days. The second phase lasted 12 days and the medium consisted of 10% [U-13C]glucose, 40% labeled [1-13C]glucose with the balance unlabeled. After the culture attained isotopic steady state, biomass samples from the last 3 days of cultivation were considered representative and used for flux estimation. They were hydrolyzed and analyzed by 2D [13C, 1H] COSY measurements using the heteronuclear single quantum correlation sequence with gradients for artifacts suppression. Metabolic fluxes were determined using the 13C-Flux software package by minimizing the residuals between the experimental and the simulated NMR data. Normalized residuals exhibited a Gaussian distribution indicating good model fit to experimental data. The glucose consumption rate was 5-fold higher than that of glutamine with 41% of glucose channeled through the pentose phosphate pathway. The fluxes at the pyruvate branch point were almost equally distributed between lactate and the TCA cycle (55% and 45%, respectively). The anaplerotic conversion of pyruvate to oxaloacetate by pyruvate carboxylase accounted for 10% of the pyruvate flux with the remaining 90% entering the TCA cycle through acetyl-CoA. The conversion of malate to pyruvate catalyzed by the malic enzyme was 70% higher than that for the anaplerotic reaction catalyzed by pyruvate carboxylase. Most amino acid catabolic and biosynthetic fluxes were significantly lower than the glycolytic and TCA cycle fluxes. Metabolic flux data from NMR analysis validated a simplified model where metabolite balancing was used for flux estimation. In this reduced flux space, estimates from these two methods were in good agreement. This simplified model can routinely be used in bioprocess development experiments to estimate metabolic fluxes with much reduced analytical investment. The high resolution flux information from 2D-NMR spectroscopy coupled with the capability to validate a simplified metabolite balancing based model for routine use make 13C-isotopomer analysis an attractive bioprocess development tool for mammalian cell cultures. |
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