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          Institute: MPI für Dynamik komplexer technischer Systeme     Collection: Bioprocess Engineering     Display Documents



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ID: 564641.0, MPI für Dynamik komplexer technischer Systeme / Bioprocess Engineering
Effects of different growth conditions on the catalytic activities of central metabolic enzymes in MDCK cells
Authors:Janke, R.; Genzel, Y.; Wahl, A.; Reichl, U.
Language:English
Name of Conference/Meeting:22nd ESACT Meeting
Place of Conference/Meeting:Vienna, Austria
(Start) Date of Event 
 (YYYY-MM-DD):
2011-05-15
End Date of Conference/Meeting 
 (YYYY-MM-DD):
2011-05-19
Audience:Experts Only
Intended Educational Use:No
Abstract / Description:It is of common knowledge that Madin-Darby canine kidney (MDCK) cells are very suitable for the propagation of different influenza strains and, therefore, for the production of cell culture-based vaccines [1]. However, during growth in glutamine-containing media, the glycolytic and glutaminolytic fluxes of most cell lines are up-regulated and large amounts of toxic by-products, such as lactate and ammonia, are secreted into the medium. This metabolic imbalance often not only affects cell viability and productivity but also can prevent growth to high cell densities [2,3]. A promising approach to reduce waste-products is the substitution of one or several components in the culture medium [4,5]. In glutamine-free medium with pyruvate as carbon source, MDCK cells not only released no ammonia during cell growth but glucose consumption and lactate production was also reduced significantly [4]. In previous work with MDCK cells, several assays were developed, to determine the extra- and intracellular metabolite concentrations [6]. Furthermore, mathematical models were established to analyze the switch from glutamine-containing to glutamine-free (pyruvate) medium [7]. However, concerning the interpretation of experimental data and corresponding flux distributions, still some open questions remain.
The objective of this study was to further elucidate the impact of media changes on metabolism by establishing a high-throughput platform for enzyme activity measurements of mammalian cells [8]. The method established uses four sensitive enzymatic cycling assays, and allows the determination of 28 key enzyme activities of central carbon metabolism in extracts of MDCK cells. Adherent MDCK cells were grown to stationary and exponential phases in 6-well plates in serum-containing GMEM supplemented with glutamine or pyruvate as well as in serum-free EPISERF medium, and key metabolic enzyme activities of cell extracts were analyzed.
Significant differences were found in maximal enzyme activities from cells grown with pyruvate-containing medium compared to glutamine-containing medium. In particular, the overall activity of the pentose phosphate pathway was up-regulated during exponential cell growth in pyruvate-containing medium, which suggests that more glucose 6-phosphate was channeled into the oxidative branch and therefore more NADPH was required. Furthermore, the anaplerotic enzymes pyruvate carboxylase and pyruvate dehydrogenase showed higher cell specific activities with pyruvate, indicating an increased flux into the TCA cycle. An increase was also found for NAD+-dependent isocitrate dehydrogenase, glutamate dehydrogenase and glutamine synthetase, which is a strong indicator for an increased flux through the right part of the citrate cycle in MDCK cells grown with pyruvate. It can be assumed that extracellular pyruvate was directly shunted into the TCA cycle, and that the increase in enzyme activities was most likely required to compensate for the energy demand and to replenish the glutamine pool. On the other hand, the activities of the glutaminolytic enzymes aspartate transaminase, alanine transaminase, malic enzyme and phosphoenolpyruvate carboxykinase were decreased in cells grown with pyruvate, which seems to be related to a decreased glutamine metabolism.
Based on the established enzyme assays metabolic states of production cell lines can now be further characterized. This can then be used to validate mathematical models of cellular metabolism and to improve our understanding of intracellular metabolic interactions relevant for process characterization and optimization.

[1] Genzel, Y., Reichl, U., (2009). Expert Rev Vaccines 8, 1681-1692.
[2] Glacken, M.W., (1988). Bio-Technol 6, 1041-1050.
[3] Ozturk, S.S., Riley, M.R., Palsson, B.O., (1992). Biotechnol and Bioeng 39, 418-431.
[4] Genzel, Y., Ritter, J.B., König, S., Alt, R., Reichl, U., (2005). Biotechnol Prog 21, 58-69.
[5] Butler, M., Christie, A., (1994). Cytotechnology 15, 87-94.
[6] Ritter, J.B., Genzel, Y., Reichl, U., (2008). Anal Biochem 373, 349-369.
[7] Sidorenko, Y., Wahl, A., Dauner, M., Genzel, Y., Reichl, U., (2008). Biotechnol Progr 24, 311-320.
[8] Janke, R., Genzel, Y., Wahl, A., Reichl, U., (2010). Biotechnol and Bioeng 107, 566-581.
Document Type:Poster
Communicated by:Udo Reichl
Affiliations:MPI für Dynamik komplexer technischer Systeme/Bioprocess Engineering
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