Metabolic Network Fluxes in Heterotrophic Arabidopsis Cells: Stability of the Flux Distribution under Different Oxygenation Conditions

Author:

Williams Thomas C.R.1,Miguet Laurent1,Masakapalli Shyam K.1,Kruger Nicholas J.1,Sweetlove Lee J.1,Ratcliffe R. George1

Affiliation:

1. Department of Plant Sciences, University of Oxford, Oxford OX1 3RB, United Kingdom

Abstract

AbstractSteady-state labeling experiments with [1-13C]Glc were used to measure multiple metabolic fluxes through the pathways of central metabolism in a heterotrophic cell suspension culture of Arabidopsis (Arabidopsis thaliana). The protocol was based on in silico modeling to establish the optimal labeled precursor, validation of the isotopic and metabolic steady state, extensive nuclear magnetic resonance analysis of the redistribution of label into soluble metabolites, starch, and protein, and a comprehensive set of biomass measurements. Following a simple modification of the cell culture procedure, cells were grown at two oxygen concentrations, and flux maps of central metabolism were constructed on the basis of replicated experiments and rigorous statistical analysis. Increased growth rate at the higher O2 concentration was associated with an increase in fluxes throughout the network, and this was achieved without any significant change in relative fluxes despite differences in the metabolite profile of organic acids, amino acids, and carbohydrates. The balance between biosynthesis and respiration within the tricarboxylic acid cycle was unchanged, with 38% ± 5% of carbon entering used for biosynthesis under standard O2 conditions and 33% ± 2% under elevated O2. These results add to the emerging picture of the stability of the central metabolic network and its capacity to respond to physiological perturbations with the minimum of rearrangement. The lack of correlation between the change in metabolite profile, which implied significant disruption of the metabolic network following the alteration in the oxygen supply, and the unchanging flux distribution highlights a potential difficulty in the interpretation of metabolomic data.

Publisher

Oxford University Press (OUP)

Subject

Plant Science,Genetics,Physiology

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