Flux quantification in central carbon metabolism of Catharanthus roseus hairy roots by 13C labeling and comprehensive bondomer balancing

Sriram, Ganesh; Fulton, D. Bruce; Shanks, Jacqueline V.

doi:10.1016/j.phytochem.2007.04.009

Cited by 60 publications

(41 citation statements)

References 61 publications

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“…Entry of carbon into the TCA cycle via both pyruvate dehydrogenase and PEPC has been observed in all MFA studies of plants. In the Arabidopsis cells, the flux through PEPC was 38% of pyruvate uptake by the mitochondrion, identical to the value obtained for soybean embryos (38%; Sriram et al, 2004b) and similar to values obtained for tomato cell suspension cultures (27% in pre-stationary phase; Rontein et al, 2002) and Catharanthus roseus hairy root cultures (23%; Sriram et al 2007). While these values for PEPC broadly agree with those measured in other tissues, the flux through NAD-ME as a percentage of pyruvate uptake was the lowest yet measured in plants (2.5%), contrasting with the previous lowest value found in tomato cell suspensions at pre-stationary phase (6%) and values as high as 66% found in B. napus embryos (Schwender et al, 2006).…”

Section: The Tca Cycle In Arabidopsissupporting

confidence: 84%

“…While the flux distribution centered on the TCA cycle in heterotrophic Arabidopsis cell suspensions under standard O 2 conditions is qualitatively similar to flux distributions in other plant species (Rontein et al, 2002;Alonso et al, 2007aAlonso et al, , 2007bSriram et al, 2007), there are nonetheless quantitative differences that may reflect the precise function of the TCA cycle in different systems. Entry of carbon into the TCA cycle via both pyruvate dehydrogenase and PEPC has been observed in all MFA studies of plants.…”

Section: The Tca Cycle In Arabidopsissupporting

confidence: 68%

“…To this end, we constructed an initial model of central carbon metabolism in heterotrophic Arabidopsis cell suspension cultures using a format compatible with the steadystate MFA software 13C-FLUX (Wiechert et al, 2001). The structure of the network was based on information from the literature, principally other MFA studies of heterotrophic metabolism in plants (Schwender et al, 2006;Alonso et al, 2007a;Sriram et al, 2007), and from metabolic databases (Schomburg et al, 2004;Zhang et al, 2005). Reactions primarily associated with photosynthetic metabolism (Calvin cycle, photorespiration) and seed germination (glyoxylate cycle) were not included, because there is no evidence that they occur to any significant extent in dark-grown Arabidopsis cell suspensions.…”

Section: Construction and Refinement Of A Metabolic Modelmentioning

confidence: 99%

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

et al. 2008

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Steady-state labeling experiments with [1-13 C]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 O 2 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% 6 5% of carbon entering used for biosynthesis under standard O 2 conditions and 33% 6 2% under elevated O 2 . 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.Although the complexity and plasticity of the metabolic network in plants allows them to adapt to fluctuating environmental conditions, the same properties also present a significant obstacle to metabolic engineering (Carrari et al., 2003a;Kruger and Ratcliffe, 2008;Sweetlove et al., 2008). The problem is particularly acute in primary metabolism, where there have been numerous instances of unsuccessful engineering, and reflects the current incomplete understanding of the way in which metabolic networks respond to environmental and genetic perturbations. Fluxes of central carbon metabolism are part of the missing information (Sweetlove et al., 2003), and although they are necessarily related to enzyme abundances, metabolite concentrations, and transcriptional responses (Carrari et al., 2006;Junker et al., 2007), their reliable prediction from the available data remains a nontrivial task . For this reason, the development and application of techniques for the measurement of flux in plants has become an important area of research (Schwender et al., 2004a;Fernie et al., 2005;Ratcliffe and Shachar-Hill, 2006). Steady-state metabolic flux analysis (MFA) has the capacity to resolve parallel, cyclic, and reversible fluxes, making it a useful technique for quantifying metabolic fluxes and investig...

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Section: The Tca Cycle In Arabidopsissupporting

confidence: 84%

Section: The Tca Cycle In Arabidopsissupporting

confidence: 68%

Section: Construction and Refinement Of A Metabolic Modelmentioning

confidence: 99%

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

et al. 2008

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“…These estimates of carbon use efficiency are within the range obtained for other heterotrophic plant systems, including a rosy periwinkle hairy root culture (24%; Sriram et al, 2007), maize root tips (42%-47%; Alonso et al, 2007b), developing sunflower embryos (50%; Alonso et al, 2007a), and a tomato cell culture (52%-68%; Rontein et al, 2002). Although considerably higher values have been reported for developing embryos of oilseed rape (85%-95%) and soybean (82%-83%), in these systems there is appreciable reassimilation of respired CO 2 through Rubisco, and light makes significant contributions to the provision of ATP and/or reductant required for biosynthesis (Goffman et al, 2005;Allen et al, 2009).…”

Section: Energy and Redox Balance In Plant Metabolic Networksupporting

confidence: 76%

“…Nevertheless, the dominance of the cytosolic pathway in catalyzing flux through the oxidative section of the PPP is unexpected, and it is unclear whether this is a general characteristic of the organization of carbohydrate metabolism in higher plants, since compartmentation of the PPP is not included in most flux maps. The only other plant tissues for which information is available are rosy periwinkle (Catharanthus roseus) hairy root cultures and developing soybean embryos, and in both of these only 25% to 50% of flux through the oxidative section of the PPP is cytosolic (Sriram et al, 2004(Sriram et al, , 2007Iyer et al, 2008). However, in these systems, total flux through the oxidative PPP is considerably higher than that observed in Arabidopsis cells, and when expressed as a proportion of the rate of sugar consumption, the cytosolic fluxes in all three systems are similar (rosy periwinkle, 42.6%; soybean, 47.4%; Arabidopsis, 37.2%), implying that variation in the compartmentation of PPP flux is due to fluctuations in plastidic activities rather than to a decrease in the significance of the cytosolic flux.…”

Section: Metabolism In a Heterotrophic Arabidopsis Cell Suspensionmentioning

confidence: 99%

Subcellular Flux Analysis of Central Metabolism in a Heterotrophic Arabidopsis Cell Suspension Using Steady-State Stable Isotope Labeling

et al. 2009

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The presence of cytosolic and plastidic pathways of carbohydrate oxidation is a characteristic feature of plant cell metabolism. Ideally, steady-state metabolic flux analysis, an emerging tool for creating flux maps of heterotrophic plant metabolism, would capture this feature of the metabolic phenotype, but the extent to which this can be achieved is uncertain. To address this question, fluxes through the pathways of central metabolism in a heterotrophic Arabidopsis (Arabidopsis thaliana) cell suspension culture were deduced from the redistribution of label in steady-state 13 C-labeling experiments using [1-13 C]-, [2-13 C]-, and [U- 13C 6 ]glucose. Focusing on the pentose phosphate pathway (PPP), multiple data sets were fitted simultaneously to models in which the subcellular compartmentation of the PPP was altered. The observed redistribution of the label could be explained by any one of three models of the subcellular compartmentation of the oxidative PPP, but other biochemical evidence favored the model in which the oxidative steps of the PPP were duplicated in the cytosol and plastids, with flux through these reactions occurring largely in the cytosol. The analysis emphasizes the inherent difficulty of analyzing the PPP without predefining the extent of its compartmentation and the importance of obtaining high-quality data that report directly on specific subcellular processes. The Arabidopsis flux map also shows that the potential ATP yield of respiration in heterotrophic plant cells can greatly exceed the direct metabolic requirements for biosynthesis, highlighting the need for caution when predicting flux through metabolic networks using assumptions based on the energetics of resource utilization.Extensive subcellular compartmentation, with unique locations for many steps and pathways, as well as the duplication of other steps and pathways in different compartments, adds greatly to the structural complexity of the plant metabolic network (Lunn, 2007;. The need to consider discrete pools of metabolites in specific compartments, and the transporters that link them, complicates the quest for a detailed, predictive understanding of the regulation of plant metabolism; as a result, it remains difficult to manipulate flows of material through the central metabolic network in a predictable way (Carrari et al., 2003;Sweetlove et al., 2008).The emergence of steady-state metabolic flux analysis (MFA) as a practicable systems biology tool for generating flux maps of the central metabolic pathways in plants offers new opportunities for analyzing plant metabolic phenotypes (Ratcliffe and ShacharHill, 2006;Libourel and Shachar-Hill, 2008;Schwender, 2008;Kruger and Ratcliffe, 2009). In this approach, substrates labeled with stable isotopes are introduced into the network, and fluxes are determined by measuring the labeling of the system after it has reached an isotopic and metabolic steady state. Subcellular compartmentation of steps and pathways can be incorporated into the model that describes the redistribution of t...

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Computational Models of Metabolism: Stability and Regulation in Metabolic Networks

Steuer

Junker

2008

Advances in Chemical Physics

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Flux quantification in central carbon metabolism of Catharanthus roseus hairy roots by 13C labeling and comprehensive bondomer balancing

Cited by 60 publications

References 61 publications

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

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

Subcellular Flux Analysis of Central Metabolism in a Heterotrophic Arabidopsis Cell Suspension Using Steady-State Stable Isotope Labeling

Computational Models of Metabolism: Stability and Regulation in Metabolic Networks

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