Analysis of metabolic flux phenotypes for two Arabidopsis mutants with severe impairment in seed storage lipid synthesis

Carbon and nitrogen provisions alter the metabolic flux in developing soybean embryos

Soybean (Glycine max) seeds store significant amounts of their biomass as protein, levels of which reflect the carbon and nitrogen received by the developing embryo. The relationship between carbon and nitrogen supply during filling and seed composition was examined through a series of embryo-culturing experiments. Three distinct ratios of carbon to nitrogen supply were further explored through metabolic flux analysis. Labeling experiments utilizing [U-(13)C5]glutamine, [U-(13)C4]asparagine, and [1,2-(13)C2]glucose were performed to assess embryo metabolism under altered feeding conditions and to create corresponding flux maps. Additionally, [U-(14)C12]sucrose, [U-(14)C6]glucose, [U-(14)C5]glutamine, and [U-(14)C4]asparagine were used to monitor differences in carbon allocation. The analyses revealed that: (1) protein concentration as a percentage of total soybean embryo biomass coincided with the carbon-to-nitrogen ratio; (2) altered nitrogen supply did not dramatically impact relative amino acid or storage protein subunit profiles; and (3) glutamine supply contributed 10% to 23% of the carbon for biomass production, including 9% to 19% of carbon to fatty acid biosynthesis and 32% to 46% of carbon to amino acids. Seed metabolism accommodated different levels of protein biosynthesis while maintaining a consistent rate of dry weight accumulation. Flux through ATP-citrate lyase, combined with malic enzyme activity, contributed significantly to acetyl-coenzyme A production. These fluxes changed with plastidic pyruvate kinase to maintain a supply of pyruvate for amino and fatty acids. The flux maps were independently validated by nitrogen balancing and highlight the robustness of primary metabolism.

Highlighting the tricarboxylic acid cycle: liquid and gas chromatography-mass spectrometry analyses of (13)C-labeled organic acids

The tricarboxylic acid (TCA) cycle is involved in the complete oxidation of organic acids to carbon dioxide in aerobic cells. It not only uses the acetyl-CoA derived from glycolysis but also uses breakdown products of proteins, fatty acids, and nucleic acids. Therefore, the TCA cycle involves numerous carbon fluxes through central metabolism to produce reductant power and transfer the generated electrons to the aerobic electron transport system where energy is formed by oxidative phosphorylation. Although the TCA cycle plays a crucial role in aerobic organisms and tissues, the lack of direct isotopic labeling information in its intermediates (organic acids) makes the quantification of its metabolic fluxes rather approximate. This is the major technical gap that this study intended to fill. In this work, we established and validated liquid and gas chromatography-mass spectrometry methods to determine (13)C labeling in organic acids involved in the TCA cycle using scheduled multiple reaction monitoring and single ion monitoring modes, respectively. Labeled samples were generated using maize embryos cultured with [(13)C]glucose or [(13)C]glutamine. Once steady-state labeling was reached, (13)C-labeled organic acids were extracted and purified. When applying our mass spectrometric methods to those extracts, mass isotopomer abundances of seven major organic acids were successfully determined.

A noninvasive platform for imaging and quantifying oil storage in submillimeter tobacco seed

While often thought of as a smoking drug, tobacco (Nicotiana spp.) is now considered as a plant of choice for molecular farming and biofuel production. Here, we describe a noninvasive means of deriving both the distribution of lipid and the microtopology of the submillimeter tobacco seed, founded on nuclear magnetic resonance (NMR) technology. Our platform enables counting of seeds inside the intact tobacco capsule to measure seed sizes, to model the seed interior in three dimensions, to quantify the lipid content, and to visualize lipid gradients. Hundreds of seeds can be simultaneously imaged at an isotropic resolution of 25 µm, sufficient to assess each individual seed. The relative contributions of the embryo and the endosperm to both seed size and total lipid content could be assessed. The extension of the platform to a range of wild and cultivated Nicotiana species demonstrated certain evolutionary trends in both seed topology and pattern of lipid storage. The NMR analysis of transgenic tobacco plants with seed-specific ectopic expression of the plastidial phosphoenolpyruvate/phosphate translocator, displayed a trade off between seed size and oil concentration. The NMR-based assay of seed lipid content and topology has a number of potential applications, in particular providing a means to test and optimize transgenic strategies aimed at the manipulation of seed size, seed number, and lipid content in tobacco and other species with submillimeter seeds.

Characterization of Arabidopsis thaliana lines with altered seed storage protein profiles using synchrotron-powered FT-IR spectromicroscopy

Arabidopsis thaliana lines expressing only one cruciferin subunit type (double-knockout; CRUAbc, CRUaBc, or CRUabC) or devoid of cruciferin (triple-knockout; CRU-) or napin (napin-RNAi) were generated using combined T-DNA insertions or RNA interference approaches. Seeds of double-knockout lines accumulated homohexameric cruciferin and contained similar protein levels as the wild type (WT). Chemical imaging of WT and double-knockout seeds using synchrotron FT-IR spectromicroscopy (amide I band, 1650 cm(-1), νC═O) showed that proteins were concentrated in the cell center and protein storage vacuoles. Protein secondary structure features of the homohexameric cruciferin lines showed predominant β-sheet content. The napin-RNAi line had lower α-helix content than the WT. Lines entirely devoid of cruciferin had high α-helix and low β-sheet levels, indicating that structurally different proteins compensate for the loss of cruciferin. Lines producing homohexameric CRUC showed minimal changes in protein secondary structure after pepsin treatment, indicating low enzyme accessibility. The Synchrotron FT-IR technique provides information on protein secondary structure and changes to the structure within the cell.

Seed-development programs: a systems biology-based comparison between dicots and monocots

Seeds develop differently in dicots and monocots, especially with respect to the major storage organs. High-resolution transcriptome data have provided the first insights into the molecular networks and pathway interactions that function during the development of individual seed compartments. Here, we review mainly recent data obtained by systems biology-based approaches, which have allowed researchers to construct and model complex metabolic networks and fluxes and identify key limiting steps in seed development. Comparative coexpression network analyses define evolutionarily conservative (FUS3/ABI3/LEC1) and divergent (LEC2) networks in dicots and monocots. Finally, we discuss the determination of seed size--an important yield-related characteristic--as mediated by a number of processes (maternal and epigenetic factors, fine-tuned regulation of cell death in distinct seed compartments, and endosperm growth) and underlying genes defined through mutant analyses. Altogether, systems approaches can make important contributions toward a more complete and holistic knowledge of seed biology and thus support strategies for knowledge-based molecular breeding.

Predictive modeling of biomass component tradeoffs in Brassica napus developing oilseeds based on in silico manipulation of storage metabolism

Seed oil content is a key agronomical trait, while the control of carbon allocation into different seed storage compounds is still poorly understood and hard to manipulate. Using bna572, a large-scale model of cellular metabolism in developing embryos of rapeseed (Brassica napus) oilseeds, we present an in silico approach for the analysis of carbon allocation into seed storage products. Optimal metabolic flux states were obtained by flux variability analysis based on minimization of the uptakes of substrates in the natural environment of the embryo. For a typical embryo biomass composition, flux sensitivities to changes in different storage components were derived. Upper and lower flux bounds of each reaction were categorized as oil or protein responsive. Among the most oil-responsive reactions were glycolytic reactions, while reactions related to mitochondrial ATP production were most protein responsive. To assess different biomass compositions, a tradeoff between the fractions of oil and protein was simulated. Based on flux-bound discontinuities and shadow prices along the tradeoff, three main metabolic phases with distinct pathway usage were identified. Transitions between the phases can be related to changing modes of the tricarboxylic acid cycle, reorganizing the usage of organic carbon and nitrogen sources for protein synthesis and acetyl-coenzyme A for cytosol-localized fatty acid elongation. The phase close to equal oil and protein fractions included an unexpected pathway bypassing α-ketoglutarate-oxidizing steps in the tricarboxylic acid cycle. The in vivo relevance of the findings is discussed based on literature on seed storage metabolism.

Plant genome-scale metabolic reconstruction and modelling

Genome-scale metabolic reconstructions are used extensively in the study of microbial metabolism and have proven powerful tools to guide rational pathway design of industrial strains. Generation and curation of plant genome-scale metabolic models has proven far more challenging, not the least of which is our incomplete knowledge of compartmentation and organelle transporters in plants. Conversely, the potential value of modelling is far greater when exploring a complex, multi-organelle and multi-tissue metabolism. The first generation of plant genome-scale metabolic reconstructions have proven surprisingly functional and robust as well as capable of predicting many observed complex phenotypes. With further refinement, the application of these models promises to make important contributions to plant biology and metabolic engineering.

Isotope labelling of Rubisco subunits provides in vivo information on subcellular biosynthesis and exchange of amino acids between compartments

The architecture of plant metabolism includes substantial duplication of metabolite pools and enzyme catalyzed reactions in different subcellular compartments. This poses challenges for understanding the regulation of metabolism particularly in primary metabolism and amino acid biosynthesis. To explore the extent to which amino acids are made in single compartments and to gain insight into the metabolic precursors from which they derive, we used steady state (13) C labelling and analysed labelling in protein amino acids from plastid and cytosol. Ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) is a major component of green tissues and its large and small subunits are synthesized from different pools of amino acids in the plastid and cytosol, respectively. Developing Brassica napus embryos were cultured in the presence of [U-(13) C]-sucrose, [U-(13) C]-glucose, [U-(13) C]-glutamine or [U-(13) C]-alanine to generate proteins. The large subunits (LSU) and small subunits (SSU) of Rubisco were isolated and the labelling in their constituent amino acids was analysed by gas chromatography-mass spectrometry. Amino acids including alanine, glycine and serine exhibited different (13) C enrichment in the LSU and SSU, demonstrating that these pools have different metabolic origins and are not isotopically equilibrated between the plastid and cytosol on the time scale of cellular growth. Potential extensions of this novel approach to other macromolecules, organelles and cell types of eukaryotes are discussed.

Gas chromatography-mass spectrometry analysis of 13C labeling in sugars for metabolic flux analysis

Metabolic flux analysis, using 13C labeled substrates, has become a powerful methodology for quantifying intracellular fluxes. Most often, analysis is restricted to nuclear magnetic resonance or mass spectrometry measurement of 13C label incorporation into protein amino acids. However, amino acid isotopomer distribution insufficiently covers the entire network of central metabolism, especially in plant cells with highly compartmented metabolism, and analysis of other metabolites is required. Analysis of label in saccharides provides complementary data to better define fluxes around hexose, pentose, and triose phosphate pools. Here, we propose a gas chromatography-mass spectrometry (GC-MS) method to analyze 13C labeling in glucose and fructose moieties of sucrose, free glucose, fructose, maltose, inositol, and starch. Our results show that saccharide labeling for isotopomer quantification is better analyzed by chemical ionization than by electron ionization. The structure of the generated fragments was simulated and validated using labeled standards. The method is illustrated by analysis of saccharides extracted from developing rapeseed (Brassica napus L.) embryos. It is shown that glucose 6-phosphate isomerase and plastidial glucose 6-phosphate transport reactions are not at equilibrium, and light is shed on the pathways leading to fructose, maltose, and inositol synthesis.

Insights into metabolic efficiency from flux analysis

The efficiency of carbon and energy flows throughout metabolism defines the potential for growth and reproductive success of plants. Understanding the basis for metabolic efficiency requires relevant definitions of efficiency as well as measurements of biochemical functions through metabolism. Here insights into the basis of efficiency provided by (13)C-based metabolic flux analysis (MFA) as well as the uses and limitations of efficiency in predictive flux balance analysis (FBA) are highlighted. (13)C-MFA studies have revealed unusual features of central metabolism in developing green seeds for the efficient use of light to conserve carbon and identified metabolic inefficiencies in plant metabolism due to dissipation of ATP by substrate cycling. Constraints-based FBA has used efficiency to guide the prediction of the growth and actual internal flux distribution of plant systems. Comparisons in a few cases have been made between flux maps measured by (13)C-based MFA and those predicted by FBA assuming one or more maximal efficiency parameters. These studies suggest that developing plant seeds and photoautotrophic microorganisms may indeed have patterns of metabolic flux that maximize efficiency. MFA and FBA are synergistic toolsets for uncovering and explaining the metabolic basis of efficiencies and inefficiencies in plant systems.

Strategies for investigating the plant metabolic network with steady-state metabolic flux analysis: lessons from an Arabidopsis cell culture and other systems

Steady-state (13)C metabolic flux analysis (MFA) is currently the experimental method of choice for generating flux maps of the compartmented network of primary metabolism in heterotrophic and mixotrophic plant tissues. While statistically robust protocols for the application of steady-state MFA to plant tissues have been developed by several research groups, the implementation of the method is still far from routine. The effort required to produce a flux map is more than justified by the information that it contains about the metabolic phenotype of the system, but it remains the case that steady-state MFA is both analytically and computationally demanding. This article provides an overview of principles that underpin the implementation of steady-state MFA, focusing on the definition of the metabolic network responsible for redistribution of the label, experimental considerations relating to data collection, the modelling process that allows a set of metabolic fluxes to be deduced from the labelling data, and the interpretation of flux maps. The article draws on published studies of Arabidopsis cell cultures and other systems, including developing oilseeds, with the aim of providing practical guidance and strategies for handling the issues that arise when applying steady-state MFA to the complex metabolic networks encountered in plants.

Metabolic cartography: experimental quantification of metabolic fluxes from isotopic labelling studies

For the past decade, flux maps have provided researchers with an in-depth perspective on plant metabolism. As a rapidly developing field, significant headway has been made recently in computation, experimentation, and overall understanding of metabolic flux analysis. These advances are particularly applicable to the study of plant metabolism. New dynamic computational methods such as non-stationary metabolic flux analysis are finding their place in the toolbox of metabolic engineering, allowing more organisms to be studied and decreasing the time necessary for experimentation, thereby opening new avenues by which to explore the vast diversity of plant metabolism. Also, improved methods of metabolite detection and measurement have been developed, enabling increasingly greater resolution of flux measurements and the analysis of a greater number of the multitude of plant metabolic pathways. Methods to deconvolute organelle-specific metabolism are employed with increasing effectiveness, elucidating the compartmental specificity inherent in plant metabolism. Advances in metabolite measurements have also enabled new types of experiments, such as the calculation of metabolic fluxes based on (13)CO(2) dynamic labelling data, and will continue to direct plant metabolic engineering. Newly calculated metabolic flux maps reveal surprising and useful information about plant metabolism, guiding future genetic engineering of crops to higher yields. Due to the significant level of complexity in plants, these methods in combination with other systems biology measurements are necessary to guide plant metabolic engineering in the future.

Metabolic control and regulation of the tricarboxylic acid cycle in photosynthetic and heterotrophic plant tissues

The tricarboxylic acid (TCA) cycle is a crucial component of respiratory metabolism in both photosynthetic and heterotrophic plant organs. All of the major genes of the tomato TCA cycle have been cloned recently, allowing the generation of a suite of transgenic plants in which the majority of the enzymes in the pathway are progressively decreased. Investigations of these plants have provided an almost complete view of the distribution of control in this important pathway. Our studies suggest that citrate synthase, aconitase, isocitrate dehydrogenase, succinyl CoA ligase, succinate dehydrogenase, fumarase and malate dehydrogenase have control coefficients flux for respiration of -0.4, 0.964, -0.123, 0.0008, 0.289, 0.601 and 1.76, respectively; while 2-oxoglutarate dehydrogenase is estimated to have a control coefficient of 0.786 in potato tubers. These results thus indicate that the control of this pathway is distributed among malate dehydrogenase, aconitase, fumarase, succinate dehydrogenase and 2-oxoglutarate dehydrogenase. The unusual distribution of control estimated here is consistent with specific non-cyclic flux mode and cytosolic bypasses that operate in illuminated leaves. These observations are discussed in the context of known regulatory properties of the enzymes and some illustrative examples of how the pathway responds to environmental change are given.

Functional genomics tools applied to plant metabolism: a survey on plant respiration, its connections and the annotation of complex gene functions

The application of post-genomic techniques in plant respiration studies has greatly improved our ability to assign functions to gene products. In addition it has also revealed previously unappreciated interactions between distal elements of metabolism. Such results have reinforced the need to consider plant respiratory metabolism as part of a complex network and making sense of such interactions will ultimately require the construction of predictive and mechanistic models. Transcriptomics, proteomics, metabolomics, and the quantification of metabolic flux will be of great value in creating such models both by facilitating the annotation of complex gene function, determining their structure and by furnishing the quantitative data required to test them. In this review, we highlight how these experimental approaches have contributed to our current understanding of plant respiratory metabolism and its interplay with associated process (e.g., photosynthesis, photorespiration, and nitrogen metabolism). We also discuss how data from these techniques may be integrated, with the ultimate aim of identifying mechanisms that control and regulate plant respiration and discovering novel gene functions with potential biotechnological implications.

Reconstruction of Arabidopsis metabolic network models accounting for subcellular compartmentalization and tissue-specificity

Plant metabolic engineering is commonly used in the production of functional foods and quality trait improvement. However, to date, computational model-based approaches have only been scarcely used in this important endeavor, in marked contrast to their prominent success in microbial metabolic engineering. In this study we present a computational pipeline for the reconstruction of fully compartmentalized tissue-specific models of Arabidopsis thaliana on a genome scale. This reconstruction involves automatic extraction of known biochemical reactions in Arabidopsis for both primary and secondary metabolism, automatic gap-filling, and the implementation of methods for determining subcellular localization and tissue assignment of enzymes. The reconstructed tissue models are amenable for constraint-based modeling analysis, and significantly extend upon previous model reconstructions. A set of computational validations (i.e., cross-validation tests, simulations of known metabolic functionalities) and experimental validations (comparison with experimental metabolomics datasets under various compartments and tissues) strongly testify to the predictive ability of the models. The utility of the derived models was demonstrated in the prediction of measured fluxes in metabolically engineered seed strains and the design of genetic manipulations that are expected to increase vitamin E content, a significant nutrient for human health. Overall, the reconstructed tissue models are expected to lay down the foundations for computational-based rational design of plant metabolic engineering. The reconstructed compartmentalized Arabidopsis tissue models are MIRIAM-compliant and are available upon request.

Experimental flux measurements on a network scale

Metabolic flux is a fundamental property of living organisms. In recent years, methods for measuring metabolic flux in plants on a network scale have evolved further. One major challenge in studying flux in plants is the complexity of the plant's metabolism. In particular, in the presence of parallel pathways in multiple cellular compartments, the core of plant central metabolism constitutes a complex network. Hence, a common problem with the reliability of the contemporary results of (13)C-Metabolic Flux Analysis in plants is the substantial reduction in complexity that must be included in the simulated networks; this omission partly is due to limitations in computational simulations. Here, I discuss recent emerging strategies that will better address these shortcomings.

Flux-balance modeling of plant metabolism

Flux-balance modeling of plant metabolic networks provides an important complement to (13)C-based metabolic flux analysis. Flux-balance modeling is a constraints-based approach in which steady-state fluxes in a metabolic network are predicted by using optimization algorithms within an experimentally bounded solution space. In the last 2 years several flux-balance models of plant metabolism have been published including genome-scale models of Arabidopsis metabolism. In this review we consider what has been learnt from these models. In addition, we consider the limitations of flux-balance modeling and identify the main challenges to generating improved and more detailed models of plant metabolism at tissue- and cell-specific scales. Finally we discuss the types of question that flux-balance modeling is well suited to address and its potential role in metabolic engineering and crop improvement.

Computational analysis of storage synthesis in developing Brassica napus L. (oilseed rape) embryos: flux variability analysis in relation to ¹³C metabolic flux analysis

Plant oils are an important renewable resource, and seed oil content is a key agronomical trait that is in part controlled by the metabolic processes within developing seeds. A large-scale model of cellular metabolism in developing embryos of Brassica napus (bna572) was used to predict biomass formation and to analyze metabolic steady states by flux variability analysis under different physiological conditions. Predicted flux patterns are highly correlated with results from prior ¹³C metabolic flux analysis of B. napus developing embryos. Minor differences from the experimental results arose because bna572 always selected only one sugar and one nitrogen source from the available alternatives, and failed to predict the use of the oxidative pentose phosphate pathway. Flux variability, indicative of alternative optimal solutions, revealed alternative pathways that can provide pyruvate and NADPH to plastidic fatty acid synthesis. The nutritional values of different medium substrates were compared based on the overall carbon conversion efficiency (CCE) for the biosynthesis of biomass. Although bna572 has a functional nitrogen assimilation pathway via glutamate synthase, the simulations predict an unexpected role of glycine decarboxylase operating in the direction of NH₄⁺ assimilation. Analysis of the light-dependent improvement of carbon economy predicted two metabolic phases. At very low light levels small reductions in CO₂ efflux can be attributed to enzymes of the tricarboxylic acid cycle (oxoglutarate dehydrogenase, isocitrate dehydrogenase) and glycine decarboxylase. At higher light levels relevant to the ¹³C flux studies, ribulose-1,5-bisphosphate carboxylase activity is predicted to account fully for the light-dependent changes in carbon balance.

Metabolic network reconstruction and flux variability analysis of storage synthesis in developing oilseed rape (Brassica napus L.) embryos

Computational simulation of large-scale biochemical networks can be used to analyze and predict the metabolic behavior of an organism, such as a developing seed. Based on the biochemical literature, pathways databases and decision rules defining reaction directionality we reconstructed bna572, a stoichiometric metabolic network model representing Brassica napus seed storage metabolism. In the highly compartmentalized network about 25% of the 572 reactions are transport reactions interconnecting nine subcellular compartments and the environment. According to known physiological capabilities of developing B. napus embryos, four nutritional conditions were defined to simulate heterotrophy or photoheterotrophy, each in combination with the availability of inorganic nitrogen (ammonia, nitrate) or amino acids as nitrogen sources. Based on mathematical linear optimization the optimal solution space was comprehensively explored by flux variability analysis, thereby identifying for each reaction the range of flux values allowable under optimality. The range and variability of flux values was then categorized into flux variability types. Across the four nutritional conditions, approximately 13% of the reactions have variable flux values and 10-11% are substitutable (can be inactive), both indicating metabolic redundancy given, for example, by isoenzymes, subcellular compartmentalization or the presence of alternative pathways. About one-third of the reactions are never used and are associated with pathways that are suboptimal for storage synthesis. Fifty-seven reactions change flux variability type among the different nutritional conditions, indicating their function in metabolic adjustments. This predictive modeling framework allows analysis and quantitative exploration of storage metabolism of a developing B. napus oilseed.

The remarkable diversity of plant PEPC (phosphoenolpyruvate carboxylase): recent insights into the physiological functions and post-translational controls of non-photosynthetic PEPCs

PEPC [PEP (phosphoenolpyruvate) carboxylase] is a tightly controlled enzyme located at the core of plant C-metabolism that catalyses the irreversible β-carboxylation of PEP to form oxaloacetate and Pi. The critical role of PEPC in assimilating atmospheric CO2 during C4 and Crassulacean acid metabolism photosynthesis has been studied extensively. PEPC also fulfils a broad spectrum of non-photosynthetic functions, particularly the anaplerotic replenishment of tricarboxylic acid cycle intermediates consumed during biosynthesis and nitrogen assimilation. An impressive array of strategies has evolved to co-ordinate in vivo PEPC activity with cellular demands for C4–C6 carboxylic acids. To achieve its diverse roles and complex regulation, PEPC belongs to a small multigene family encoding several closely related PTPCs (plant-type PEPCs), along with a distantly related BTPC (bacterial-type PEPC). PTPC genes encode ~110-kDa polypeptides containing conserved serine-phosphorylation and lysine-mono-ubiquitination sites, and typically exist as homotetrameric Class-1 PEPCs. In contrast, BTPC genes encode larger ~117-kDa polypeptides owing to a unique intrinsically disordered domain that mediates BTPC's tight interaction with co-expressed PTPC subunits. This association results in the formation of unusual ~900-kDa Class-2 PEPC hetero-octameric complexes that are desensitized to allosteric effectors. BTPC is a catalytic and regulatory subunit of Class-2 PEPC that is subject to multi-site regulatory phosphorylation in vivo. The interaction between divergent PEPC polypeptides within Class-2 PEPCs adds another layer of complexity to the evolution, physiological functions and metabolic control of this essential CO2-fixing plant enzyme. The present review summarizes exciting developments concerning the functions, post-translational controls and subcellular location of plant PTPC and BTPC isoenzymes.

The role of transporters in supplying energy to plant plastids

The energy status of plant cells strongly depends on the energy metabolism in chloroplasts and mitochondria, which are capable of generating ATP either by photosynthetic or oxidative phosphorylation, respectively. Another energy-rich metabolite inside plastids is the glycolytic intermediate phosphoenolpyruvate (PEP). However, chloroplasts and most non-green plastids lack the ability to generate PEP via a complete glycolytic pathway. Hence, PEP import mediated by the plastidic PEP/phosphate translocator or PEP provided by the plastidic enolase are vital for plant growth and development. In contrast to chloroplasts, metabolism in non-green plastids (amyloplasts) of starch-storing tissues strongly depends on both the import of ATP mediated by the plastidic nucleotide transporter NTT and of carbon (glucose 6-phosphate, Glc6P) mediated by the plastidic Glc6P/phosphate translocator (GPT). Both transporters have been shown to co-limit starch biosynthesis in potato plants. In addition, non-photosynthetic plastids as well as chloroplasts during the night rely on the import of energy in the form of ATP via the NTT. During energy starvation such as prolonged darkness, chloroplasts strongly depend on the supply of ATP which can be provided by lipid respiration, a process involving chloroplasts, peroxisomes, and mitochondria and the transport of intermediates, i.e. fatty acids, ATP, citrate, and oxaloacetate across their membranes. The role of transporters involved in the provision of energy-rich metabolites and in pathways supplying plastids with metabolic energy is summarized here.

PII is induced by WRINKLED1 and fine-tunes fatty acid composition in seeds of Arabidopsis thaliana

The PII protein is an integrator of central metabolism and energy levels. In Arabidopsis, allosteric sensing of cellular energy and carbon levels alters the ability of PII to interact with target enzymes such as N-acetyl-l-glutamate kinase and heteromeric acetyl-coenzyme A carboxylase, thereby modulating the biological activity of these plastidial ATP- and carbon-consuming enzymes. A quantitative reverse transcriptase-polymerase chain reaction approach revealed a threefold induction of the AtGLB1 gene (At4g01900) encoding PII during early seed maturation. The activity of the AtGLB1 promoter was consistent with this pattern. A complementary set of molecular and genetic analyses showed that WRINKLED1, a transcription factor known to induce glycolytic and fatty acid biosynthetic genes at the onset of seed maturation, directly controls AtGLB1 expression. Immunoblot analyses and immunolocalization experiments using anti-PII antibodies established that PII protein levels faithfully reflected AtGLB1 mRNA accumulation. At the subcellular level, PII was observed in plastids of maturing embryos. To further investigate the function of PII in seeds, comprehensive functional analyses of two pII mutant alleles were carried out. A transient increase in fatty acid production was observed in mutant seeds at a time when PII protein content was found to be maximal in wild-type seeds. Moreover, minor though statistically significant modifications of the fatty acid composition were measured in pII seeds, which exhibited decreased amounts of modified (elongated, desaturated) fatty acid species. The results obtained outline a role for PII in the fine tuning of fatty acid biosynthesis and partitioning in seeds.

A genome-scale metabolic model accurately predicts fluxes in central carbon metabolism under stress conditions

Flux is a key measure of the metabolic phenotype. Recently, complete (genome-scale) metabolic network models have been established for Arabidopsis (Arabidopsis thaliana), and flux distributions have been predicted using constraints-based modeling and optimization algorithms such as linear programming. While these models are useful for investigating possible flux states under different metabolic scenarios, it is not clear how close the predicted flux distributions are to those occurring in vivo. To address this, fluxes were predicted for heterotrophic Arabidopsis cells and compared with fluxes estimated in parallel by (13)C-metabolic flux analysis (MFA). Reactions of the central carbon metabolic network (glycolysis, the oxidative pentose phosphate pathway, and the tricarboxylic acid [TCA] cycle) were independently analyzed by the two approaches. Net fluxes in glycolysis and the TCA cycle were predicted accurately from the genome-scale model, whereas the oxidative pentose phosphate pathway was poorly predicted. MFA showed that increased temperature and hyperosmotic stress, which altered cell growth, also affected the intracellular flux distribution. Under both conditions, the genome-scale model was able to predict both the direction and magnitude of the changes in flux: namely, increased TCA cycle and decreased phosphoenolpyruvate carboxylase flux at high temperature and a general decrease in fluxes under hyperosmotic stress. MFA also revealed a 3-fold reduction in carbon-use efficiency at the higher temperature. It is concluded that constraints-based genome-scale modeling can be used to predict flux changes in central carbon metabolism under stress conditions.

Phosphoenolpyruvate provision to plastids is essential for gametophyte and sporophyte development in Arabidopsis thaliana

Restriction of phosphoenolpyruvate (PEP) supply to plastids causes lethality of female and male gametophytes in Arabidopsis thaliana defective in both a phosphoenolpyruvate/phosphate translocator (PPT) of the inner envelope membrane and the plastid-localized enolase (ENO1) involved in glycolytic PEP provision. Homozygous double mutants of cue1 (defective in PPT1) and eno1 could not be obtained, and homozygous cue1 heterozygous eno1 mutants [cue1/eno1(+/-)] exhibited retarded vegetative growth, disturbed flower development, and up to 80% seed abortion. The phenotypes of diminished oil in seeds, reduced flavonoids and aromatic amino acids in flowers, compromised lignin biosynthesis in stems, and aberrant exine formation in pollen indicate that cue1/eno1(+/-) disrupts multiple pathways. While diminished fatty acid biosynthesis from PEP via plastidial pyruvate kinase appears to affect seed abortion, a restriction in the shikimate pathway affects formation of sporopollonin in the tapetum and lignin in the stem. Vegetative parts of cue1/eno1(+/-) contained increased free amino acids and jasmonic acid but had normal wax biosynthesis. ENO1 overexpression in cue1 rescued the leaf and root phenotypes, restored photosynthetic capacity, and improved seed yield and oil contents. In chloroplasts, ENO1 might be the only enzyme missing for a complete plastidic glycolysis.

Not just a circle: flux modes in the plant TCA cycle

The tricarboxylic acid (TCA) cycle is one of the iconic pathways in metabolism. The cycle is commonly thought of in terms of energy metabolism, being responsible for the oxidation of respiratory substrates to drive ATP synthesis. However, the reactions of carboxylic acid metabolism are embedded in a larger metabolic network and the conventional TCA cycle is only one way in which the component reactions can be organised. Recent evidence from labelling studies and metabolic network models suggest that the organisation of carboxylic acid metabolism in plants is highly dependent on the metabolic and physiological demands of the cell. Thus, alternative, non-cyclic flux modes occur in leaves in the light, in some developing oilseeds, and under specific physiological circumstances such as anoxia.

Understanding fatty acid synthesis in developing maize embryos using metabolic flux analysis

The efficiency with which developing maize embryos convert substrates into seed storage reserves was determined to be 57-71%, by incubating developing maize embryos with uniformly labeled 14C substrates and measuring their conversion to CO2 and biomass products. To map the pattern of metabolic fluxes underlying this efficiency, maize embryos were labeled to isotopic steady state using a combination of labeled 13C-substrates. Intermediary metabolic fluxes were estimated by computer-aided modeling of the central metabolic network using the labeling data collected by NMR and GC-MS and the biomass composition. The resultant flux map reveals that even though 36% of the entering carbon goes through the oxidative pentose-phosphate pathway, this does not fully meet the NADPH demands for fatty acid synthesis. Metabolic flux analysis and enzyme activities highlight the importance of plastidic NADP-dependent malic enzyme, which provides one-third of the carbon and NADPH required for fatty acid synthesis in developing maize embryos.