Literature DB >> 21188421

Quantitative characterization of metabolism and metabolic shifts during growth of the new human cell line AGE1.HN using time resolved metabolic flux analysis.

Jens Niklas1, Eva Schräder, Volker Sandig, Thomas Noll, Elmar Heinzle.   

Abstract

For the improved production of vaccines and therapeutic proteins, a detailed understanding of the metabolic dynamics during batch or fed-batch production is requested. To study the new human cell line AGE1.HN, a flexible metabolic flux analysis method was developed that is considering dynamic changes in growth and metabolism during cultivation. This method comprises analysis of formation of cellular components as well as conversion of major substrates and products, spline fitting of dynamic data and flux estimation using metabolite balancing. During batch cultivation of AGE1.HN three distinct phases were observed, an initial one with consumption of pyruvate and high glycolytic activity, a second characterized by a highly efficient metabolism with very little energy spilling waste production and a third with glutamine limitation and decreasing viability. Main events triggering changes in cellular metabolism were depletion of pyruvate and glutamine. Potential targets for the improvement identified from the analysis are (i) reduction of overflow metabolism in the beginning of cultivation, e.g. accomplished by reduction of pyruvate content in the medium and (ii) prolongation of phase 2 with its highly efficient energy metabolism applying e.g. specific feeding strategies. The method presented allows fast and reliable metabolic flux analysis during the development of producer cells and production processes from microtiter plate to large scale reactors with moderate analytical and computational effort. It seems well suited to guide media optimization and genetic engineering of producing cell lines.

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Year:  2010        PMID: 21188421      PMCID: PMC3092918          DOI: 10.1007/s00449-010-0502-y

Source DB:  PubMed          Journal:  Bioprocess Biosyst Eng        ISSN: 1615-7591            Impact factor:   3.210


  57 in total

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9.  A correction method for systematic error in (1)H-NMR time-course data validated through stochastic cell culture simulation.

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10.  Identification of growth phases and influencing factors in cultivations with AGE1.HN cells using set-based methods.

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