Metabolic responses of the new neuronal human cell line AGE1.HN to various substrate levels were analyzed in this study showing that reduced substrate and especially pyruvate load improves metabolic efficiency, leading to improved growth and α(1)-antitrypsin (A1AT) production. The adaptation of the metabolism to different pyruvate and glutamine concentrations was analyzed in detail using a full factorial design. The most important finding was an increasingly inefficient use of substrates as well as the reduction of cell proliferation with increasing pyruvate concentrations in the medium. Cultivations with different feeding profiles showed that the highest viable cell density and A1AT concentration (167% of batch) was reached in the culture with the lowest glucose level and without pyruvate feeding. Analysis of metabolic fluxes in the differently fed cultures revealed a more efficient metabolic phenotype in the cultures without pyruvate feeding. The measured in vitro enzyme activities of the selected enzymes involved in pyruvate metabolism were lower in AGE1.HN compared with CHO cells, which might explain the higher sensitivity and different adaptation of AGE1.HN to increased pyruvate concentrations. The results indicate on the one hand that increasing the connectivity between glycolysis and the TCA cycle might improve substrate use and, finally, the production of A1AT. On the other hand, a better balanced substrate uptake promises a reduction of energy spilling which is increased with increasing substrate levels in this cell line. Overall, the results of this study provide important insights into the regulation of primary metabolism and into the adaptation of AGE1.HN to different substrate levels, providing guidance for further optimization of production cell lines and applied process conditions.

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Accurate determination of cell number is essential for the quantitative description of biological processes. The changes should be related to a measurable reference e.g. in the case of cell culture, the viable cell number is a very valuable reference parameter. Indirect methods of cell number/viability measurements may have up to 10 % standard deviation. This can lead to undesirable large deviations in the analysis of ''-omics'' data as well as time course studies. Such data should be preferably normalized to the exact viable cell number at a given time to allow meaningful interpretation and understanding of the biological processes. Manual counting of cell number is very laborious and not possible in certain experimental setups. We therefore, developed a simple and reliable fluorescence based method with an accuracy of 95-98 % for the determination of the viable cell number in situ. We optimized the seeding cell densities for primary rat hepatocytes for optimal cell adhesion. This will help in efficient use of primary cells which are usually limited in availability. The method will be very useful in the application of ''-omics'' techniques, especially metabolome analysis where the specific rates of uptake/production of metabolites can be reliably calculated.

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