2014
DOI: 10.1111/tpj.12685
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Modelling central metabolic fluxes by constraint‐based optimization reveals metabolic reprogramming of developing Solanum lycopersicum (tomato) fruit

Abstract: Modelling of metabolic networks is a powerful tool to analyse the behaviour of developing plant organs, including fruits. Guided by our current understanding of heterotrophic metabolism of plant cells, a medium-scale stoichiometric model, including the balance of co–factors and energy, was constructed in order to describe metabolic shifts that occur through the nine sequential stages of Solanum lycopersicum (tomato) fruit development. The measured concentrations of the main biomass components and the accumulat… Show more

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Cited by 67 publications
(77 citation statements)
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“…Cell division and cell expansion impose completely different sets of demands upon the metabolic network and so can be expected to lead to completely different flux maps. In fact, this can be seen in the FBA-predicted network fluxes in tomato fruit at different stages of development, in which network fluxes in fruit at 8 DPA (still in the phase of cell division) are dramatically different from those at later stages of development dominated by cell expansion (Colombié et al, 2015). Tomato fruit are a good system in which to study cell division and cell expansion because the temporal demarcations between them are well established and, also, because sufficient tissue mass accumulates during the cell division phase to make biochemical measurements feasible.…”
Section: Future Directions and Challengesmentioning
confidence: 92%
See 1 more Smart Citation
“…Cell division and cell expansion impose completely different sets of demands upon the metabolic network and so can be expected to lead to completely different flux maps. In fact, this can be seen in the FBA-predicted network fluxes in tomato fruit at different stages of development, in which network fluxes in fruit at 8 DPA (still in the phase of cell division) are dramatically different from those at later stages of development dominated by cell expansion (Colombié et al, 2015). Tomato fruit are a good system in which to study cell division and cell expansion because the temporal demarcations between them are well established and, also, because sufficient tissue mass accumulates during the cell division phase to make biochemical measurements feasible.…”
Section: Future Directions and Challengesmentioning
confidence: 92%
“…CO 2 ) and minimization of the total flux was used to simulate whole-plant behavior and to obtain tissue-specific steady-state flux distributions followed by FBA. Finally, biomass reactions specific for nine stages of tomato (Solanum lycopersicum) fruit development in combination with the minimization of total flux were used to investigate the temporal redistribution of fluxes in the central metabolism of tomato fruits (Colombié et al, 2015).…”
Section: Context-specific Models In Plantsmentioning
confidence: 99%
“…Although metabolic modelling in plant cells is not as advanced as in other organisms such as microorganisms and mammalian cells (Oberhardt et al ., ), considerable progress has been made in recent years in the study of metabolism in plants (for more details, see the review of Shi & Schwender, ). In tomato, a genome‐scale metabolic model of tomato recently has been reconstructed and used to simulate tomato leaf metabolism (Yuan et al ., ), and a constraint‐based model has been used to calculate relevant fluxes throughout tomato fruit development (Colombié et al ., ). Glycolysis, tricarboxylic acid (TCA) cycle and miETC are central features of carbon metabolism and bioenergetics in aerobic organisms in which respiration is connected with sugar supply.…”
Section: Introductionmentioning
confidence: 97%
“…Tomato (Solanum lycopersicum) has been continuously studied concerning genetics, physiology as well as biochemistry due to its agronomical importance and fruit development (Colombie et al, 2015). But it is unable to tolerate the severity of cold stress (Shah et al, 2015).…”
Section: Introductionmentioning
confidence: 99%