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Network analysis of intermediary metabolism using linear optimization. II. Interpretation of hybridoma cell metabolism

, and . J Theor Biol 154 (4): 455-473 (February 1992)

Abstract

The reaction network of intermediary metabolism in the mammalian cell has been studied using linear optimization. Experimental measurements of metabolite fluxes entering and leaving hybridoma cell line 167.4G5.3 have been used to interpret the interactions of nutrients and the demand for intermediates for growth. We have ascertained the effects of waste production and energy loads on the cell growth rate using linear optimization. This analysis has shown that neither the maintenance demand for ATP nor the antibody production rate limit growth rate at normal experimental conditions. In addition, the cell uses its nutrients for growth with only 57-78% efficiency, due to the large secretion of alanine. The sensitivity of the growth rate with respect to the demand for cofactors and the supply of nutrients is given by the shadow price for each constraint. The shadow prices have shown that amino acids are the limiting nutrients at experimental conditions. The sensitivities of the growth rate to flux through reactions, given by the reduced costs, have shown that flux through the reaction glutamate dehydrogenase may actually slow down cell growth. We have also found that intermediates with lower shadow prices, and thus with lower value to the cell, are the precursors to compounds secreted from the cell. The shadow prices are also a means for comparing the costs of synthesizing various intermediates in terms of the two major nutrients, glucose and glutamine. At anaerobic conditions, glucose and glutamine have similar values to the cell, and the cost to synthesize most intermediates in terms of glucose is identical to the cost in terms of glutamine. At aerobic conditions, glucose is nearly twice as valuable to the cell as glutamine.

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Network analysis of intermediary metabolism using linear optimization. II. Interpretation of hybridoma cell metabolism. - PubMed - NCBI

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Savinell1992bNetwork
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