Robustness of central carbohydrate metabolism in developing maize kernels

Spielbauer, Gertraud; Margl, Lilla; Hannah, L. Curtis; Römisch, Werner; Ettenhuber, Christian; Bacher, Adelbert; Gierl, Alfons; Eisenreich, Wolfgang; Genschel, Ulrich

doi:10.1016/j.phytochem.2006.05.035

Cited by 56 publications

(39 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While the identity of the reactions that vary is not entirely surprising (they are connected to processes such as glycolysis and TCA cycle that are known to be involved in ATP generation), the fact that the network can accommodate a large range of ATP synthesis rates with minimal disturbance to most fluxes demonstrates the inherent robustness of the metabolic network. Metabolism is known to be robust to gene deletions (Blank et al, 2005;Gerdes et al, 2006;Behre et al, 2008), and steadystate isotope labeling experiments in plants have revealed an inherent robustness to both genetic intervention (Spielbauer et al, 2006) and altered environment (Williams et al, 2008). This work can now extend that observation of robustness from the tens of reac- tions amenable to quantification from isotope labeling experiments to some 185 reactions of primary metabolism, and this robustness is conferred by the structure of the network, independently of kinetic or genetic control (because these were not included in the model).…”

Section: Discussionmentioning

confidence: 99%

A Genome-Scale Metabolic Model of Arabidopsis and Some of Its Properties

et al. 2009

View full text Add to dashboard Cite

We describe the construction and analysis of a genome-scale metabolic model of Arabidopsis (Arabidopsis thaliana) primarily derived from the annotations in the Aracyc database. We used techniques based on linear programming to demonstrate the following: (1) that the model is capable of producing biomass components (amino acids, nucleotides, lipid, starch, and cellulose) in the proportions observed experimentally in a heterotrophic suspension culture; (2) that approximately only 15% of the available reactions are needed for this purpose and that the size of this network is comparable to estimates of minimal network size for other organisms; (3) that reactions may be grouped according to the changes in flux resulting from a hypothetical stimulus (in this case demand for ATP) and that this allows the identification of potential metabolic modules; and (4) that total ATP demand for growth and maintenance can be inferred and that this is consistent with previous estimates in prokaryotes and yeast.Historically, attempts to engineer plant metabolism for increased production of specific useful products have met with mixed success. Problems arise because of considerable metabolic redundancy that allows imposed genetic changes to be circumvented, because of an insufficiently detailed knowledge of the distribution of control of flux, and because the behavior of plant metabolism at the network level is not well described. While increasingly complex metabolic networks are now being characterized with steadystate stable isotope labeling experiments (Libourel and Shachar-Hill, 2008;Schwender, 2008;Kruger and Ratcliffe, 2009), the resulting flux maps still only cover a small percentage of the total metabolic network. The construction of a comprehensive plant metabolic model that includes the complete repertoire of catalyzed transformations represented within a specific genome (a genome-scale metabolic model) would represent a significant step forward in the development of a description of plant metabolic behavior at the network level.The aim of this work is to describe a genome-scale structural model of Arabidopsis (Arabidopsis thaliana) metabolism and to explore the utility of the model as a tool to characterize possible flux behavior states of the metabolic network. Arabidopsis is the logical choice for this exercise because of its well-annotated genome. Moreover, the translation of the Arabidopsis genome into a curated set of metabolic reactions is already well advanced, and the reaction lists are available through the Aracyc database (Mueller et al., 2003;Zhang et al., 2005). While this is an excellent starting point for metabolic modeling, uncritical use of such reaction lists is likely to generate models exhibiting a number of problems, the most fundamental of which is violation of mass conservation. Thus, considerable effort is required to generate a useful genome-scale metabolic model from these databases .Once a stoichiometrically balanced structural model is achieved, the investigator is then faced with the challenge o...

show abstract

Section: Discussionmentioning

confidence: 99%

A Genome-Scale Metabolic Model of Arabidopsis and Some of Its Properties

et al. 2009

View full text Add to dashboard Cite

show abstract

“…In many cases, the metabolic steady state has proven to be remarkably robust: fluxes in heterotrophic tissues measured by MFA are often invariant under different environmental conditions (Spielbauer et al, 2006;Williams et al, 2008). Naturally, this depends on the nature and magnitude of the altered demand.…”

Section: Integrated Metabolic Network Responsesmentioning

confidence: 99%

Inference and prediction of metabolic network fluxes

Nikoloski

Perez-Storey

2015

Plant Physiol.

View full text Add to dashboard Cite

In this Update, we cover the basic principles of the estimation and prediction of the rates of the many interconnected biochemical reactions that constitute plant metabolic networks. This includes metabolic flux analysis approaches that utilize the rates or patterns of redistribution of stable isotopes of carbon and other atoms to estimate fluxes, as well as constraints-based optimization approaches such as flux balance analysis. Some of the major insights that have been gained from analysis of fluxes in plants are discussed, including the functioning of metabolic pathways in a network context, the robustness of the metabolic phenotype, the importance of cell maintenance costs, and the mechanisms that enable energy and redox balancing at steady state. We also discuss methodologies to exploit 'omic data sets for the construction of tissue-specific metabolic network models and to constrain the range of permissible fluxes in such models. Finally, we consider the future directions and challenges faced by the field of metabolic network flux phenotyping.The metabolic systems of plants utilize a continual energy stream (i.e. light in the case of photosynthetic tissues and chemical energy in the case of heterotrophic tissues) to drive a complex network of hundreds of chemical reactions away from equilibrium. Ultimately, this leads to the catalyzed biosynthesis of the ordered polymeric biomolecules that make up the biomass of the cells in each tissue and underpins the growth and development of the plant (Smith and Stitt, 2007). To operate on a time scale relevant for life, the system is dependent upon the acceleration of its chemistry by enzymes. Additionally, because of the highly compartmented nature of plant cells, transporter proteins are required to permit the movement of metabolites (i.e. the substrates and products of biochemical reactions) between subcellular compartments. Transporter proteins are also required to bring substrates into cells and to allow the excretion of waste products and other metabolites such as defense compounds. The sum total of expressed genes encoding enzymes and metabolite transporters determines the metabolic capabilities of a cell. In a growing tissue, the net output of this metabolism is anabolic (i.e. leading to the biosynthesis of biomass constituents such as starch, fructans, cell wall, lipid, and protein), but catabolic metabolism is also required. Most importantly, catabolism generates universal energy currencies such as ATP and NAD(P)H, whose turnover is used to provide the energetic driving force for anabolism. Catabolism is also important to allow the turnover of cellular components for regulatory and repair purposes (Linster et al., 2013;Ishihara et al., 2015). The turnover and resynthesis of cellular components, along with the maintenance of electrochemical potentials across membranes, are important facets of metabolism that need to be considered alongside the biosynthesis of macromolecules for growth (Stitt, 2013;Sweetlove et al., 2013).Metabolism, then, is the entirety of c...

show abstract

“…While certain environmental and genetic perturbations have been shown to alter the flux distribution in the central metabolic network (Spielbauer et al, 2006;Junker et al, 2007;Iyer et al, 2008), it is also possible for the fluxes to vary in absolute magnitude without any change in their relative values. This is certainly the case in the Arabidopsis cell study reported here, and a similar result was obtained in a less statistically rigorous flux analysis of a tomato cell suspension, where the relative fluxes through glycolysis, the TCA cycle, and the oxidative pentose phosphate pathway remained similar, even though the net fluxes decreased over the culture period (Rontein et al, 2002).…”

Section: Network Stabilitymentioning

confidence: 99%

“…This is certainly the case in the Arabidopsis cell study reported here, and a similar result was obtained in a less statistically rigorous flux analysis of a tomato cell suspension, where the relative fluxes through glycolysis, the TCA cycle, and the oxidative pentose phosphate pathway remained similar, even though the net fluxes decreased over the culture period (Rontein et al, 2002). Similarly analysis of wild-type, hybrid, and starch-deficient maize (Zea mays) lines (Spielbauer et al, 2006) revealed few differences in relative fluxes despite the great variation in accumulation of starch and seed weight across the genotypes. A similar trend has also been observed in microorganisms Sauer, 2003, 2005) and yeast (Saccharomyces cerevisiae; Blank et al, 2005).…”

Section: Network Stabilitymentioning

confidence: 99%

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

et al. 2008

View full text Add to dashboard Cite

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...

show abstract

Robustness of central carbohydrate metabolism in developing maize kernels

Cited by 56 publications

References 64 publications

A Genome-Scale Metabolic Model of Arabidopsis and Some of Its Properties

A Genome-Scale Metabolic Model of Arabidopsis and Some of Its Properties

Inference and prediction of metabolic network fluxes

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

Contact Info

Product

Resources

About