Changes in flux pattern of the central carbohydrate metabolism during kernel development in maize

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.

FRET-based glucose imaging identifies glucose signalling in response to biotic and abiotic stresses in rice roots

Glucose is the primary energy provider and the most important sugar-signalling molecule, regulating metabolites and modulating gene expression from unicellular yeast to multicellular plants and animals. Therefore, monitoring intracellular glucose levels temporally and spatially in living cells is an essential step for decoding the glucose signalling in response to biotic and abiotic stresses. In this study, the genetically encoded FRET (Förster resonance energy transfer) nanosensors, FLIPglu-2μ∆13 and FLIPglu-600μΔ13, were used to measure cytosolic glucose dynamics in rice plants. First, we found that the FRET signal decreased in response to external glucose in a concentration-dependent manner. The glucose concentration at which the cytosolic level corresponded to the K_0.5 value for FLIPglu-2μΔ13 was approximately 10.05μM, and that for FLIPglu-600μΔ13 was 0.9mM, respectively. The substrate selectivity of nanosensors for glucose and its analogues is D-Glucose>2-deoxyglucose>3-O-methylglucose>L-Glucose. We further showed that the biotic elicitors (flg22 and chitin) and the abiotic elicitors (osmotic stress, salinity and extreme temperature) induce the intracellular glucose increases in the detached root segments of transgenic rice containing FLIPglu-2μΔ13 in a stimulus-specific manner, but not in FLIPglu-600μΔ13 transgenic lines. These results demonstrated that FRET nanosensors can be used to detect increases in intracellular glucose within the physiological range of 0.2-20μM in response to various stimuli in transgenic rice root cells, which indicated that intracellular glucose may act as a potential secondary messenger to connect extracellular stimuli with cellular physiological responses in plants.

Decoding Biosynthetic Pathways in Plants by Pulse-Chase Strategies Using (13)CO₂ as a Universal Tracer †

(13)CO₂ pulse-chase experiments monitored by high-resolution NMR spectroscopy and mass spectrometry can provide (13)C-isotopologue compositions in biosynthetic products. Experiments with a variety of plant species have documented that the isotopologue profiles generated with (13)CO₂ pulse-chase labeling are directly comparable to those that can be generated by the application of [U-(13)C₆]glucose to aseptically growing plants. However, the application of the (13)CO₂ labeling technology is not subject to the experimental limitations that one has to take into account for experiments with [U-(13)C₆]glucose and can be applied to plants growing under physiological conditions, even in the field. In practical terms, the results of biosynthetic studies with (13)CO₂ consist of the detection of pairs, triples and occasionally quadruples of (13)C atoms that have been jointly contributed to the target metabolite, at an abundance that is well above the stochastic occurrence of such multiples. Notably, the connectivities of jointly transferred (13)C multiples can have undergone modification by skeletal rearrangements that can be diagnosed from the isotopologue data. As shown by the examples presented in this review article, the approach turns out to be powerful in decoding the carbon topology of even complex biosynthetic pathways.

Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future

Metabolism is comprised of networks of chemical transformations, organized into integrated biochemical pathways that are the basis of cellular operation, and function to sustain life. Metabolism, and thus life, is not static. The rate of metabolites transitioning through biochemical pathways (i.e., flux) determines cellular phenotypes, and is constantly changing in response to genetic or environmental perturbations. Each change evokes a response in metabolic pathway flow, and the quantification of fluxes under varied conditions helps to elucidate major and minor routes, and regulatory aspects of metabolism. To measure fluxes requires experimental methods that assess the movements and transformations of metabolites without creating artifacts. Isotopic labeling fills this role and is a long-standing experimental approach to identify pathways and quantify their metabolic relevance in different tissues or under different conditions. The application of labeling techniques to plant science is however far from reaching it potential. In light of advances in genetics and molecular biology that provide a means to alter metabolism, and given recent improvements in instrumentation, computational tools and available isotopes, the use of isotopic labeling to probe metabolism is becoming more and more powerful. We review the principal analytical methods for isotopic labeling with a focus on seminal studies of pathways and fluxes in lipid metabolism and carbon partitioning through central metabolism. Central carbon metabolic steps are directly linked to lipid production by serving to generate the precursors for fatty acid biosynthesis and lipid assembly. Additionally some of the ideas for labeling techniques that may be most applicable for lipid metabolism in the future were originally developed to investigate other aspects of central metabolism. We conclude by describing recent advances that will play an important future role in quantifying flux and metabolic operation in plant tissues.

The complex isotopologue space of glucose as a framework for the study of human intermediary metabolism

The positional distributions of stable isotopes in metabolites provide specific fingerprints of the pathways and fluxes that have occurred in the organisms under study. In particular, modern nuclear magnetic resonance (NMR) spectroscopy enables the detailed assignment of isotope patterns in natural products, for example, in metabolites obtained from labelling experiments using (13)C-enriched precursors, such as glucose, acetate or CO2. In this study, the transient (13)C-isotopologue composition of blood glucose from an adult human volunteer after intravenous supply of [U-(13)C6]glucose was determined by high-resolution (13)C NMR spectroscopy. The non-linear progression curves displaying the relative amounts of eight (13)C-glucose isotopologues reflected the contributions of glucose metabolism by glycolytic cycling, the pentose phosphate pathway and anaplerotic reactions involving the citric acid cycle. The pilot study suggests that the experimental setting can be useful in analysing under non-invasive conditions the impact of physiological and pharmacological constraints on glucose turnover in humans.

Quantification of ¹³C enrichments and isotopomer abundances for metabolic flux analysis using 1D NMR spectroscopy

The analysis of stable isotope incorporation following feeding of (13)C-labeled precursors to plant tissues provides the constraints necessary for metabolic flux analysis. This protocol describes the use of one-dimensional (1)H and (13)C nuclear magnetic resonance spectroscopy for the quantification of (13)C enrichments and isotopomer abundances in mixtures of metabolites or hydrolyzed biomass components.

Analysis of metabolic flux using dynamic labelling and metabolic modelling

Metabolic fluxes and the capacity to modulate them are a crucial component of the ability of the plant cell to react to environmental perturbations. Our ability to quantify them and to attain information concerning the regulatory mechanisms that control them is therefore essential to understand and influence metabolic networks. For all but the simplest of flux measurements labelling methods have proven to be the most informative. Both steady-state and dynamic labelling approaches have been adopted in the study of plant metabolism. Here the conceptual basis of these complementary approaches, as well as their historical application in microbial, mammalian and plant sciences, is reviewed, and an update on technical developments in label distribution analyses is provided. This is supported by illustrative cases studies involving the kinetic modelling of secondary metabolism. One issue that is particularly complex in the analysis of plant fluxes is the extensive compartmentation of the plant cell. This problem is discussed from both theoretical and experimental perspectives, and the current approaches used to address it are assessed. Finally, current limitations and future perspectives of kinetic modelling of plant metabolism are discussed.

Chloroplast-localized 6-phosphogluconate dehydrogenase is critical for maize endosperm starch accumulation

Plants have duplicate versions of the oxidative pentose phosphate pathway (oxPPP) enzymes with a subset localized to the chloroplast. The chloroplast oxPPP provides NADPH and pentose sugars for multiple metabolic pathways. This study identified two loss-of-function alleles of the Zea mays (maize) chloroplast-localized oxPPP enzyme 6-phosphogluconate dehydrogenase (6PGDH). These mutations caused a rough endosperm seed phenotype with reduced embryo oil and endosperm starch. Genetic translocation experiments showed that pgd3 has separate, essential roles in both endosperm and embryo development. Endosperm metabolite profiling experiments indicated that pgd3 shifts redox-related metabolites and increases reducing sugars similar to starch-biosynthetis mutants. Heavy isotope-labelling experiments indicates that carbon flux into starch is altered in pgd3 mutants. Labelling experiments with a loss of cytosolic 6PGDH did not affect flux into starch. These results support the known role for plastid-localized oxPPP in oil synthesis and argue that amyloplast-localized oxPPP reactions are integral to endosperm starch accumulation in maize kernels.

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.

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.

Central metabolic fluxes in the endosperm of developing maize seeds and their implications for metabolic engineering

¹⁴C labeling experiments performed with kernel cultures showed that developing maize endosperm is more efficient than other non-photosynthetic tissues such as sunflower and maize embryos at converting maternally supplied substrates into biomass. To characterize the metabolic fluxes in endosperm, maize kernels were labeled to isotopic steady state using ¹³C-labeled glucose. The resultant labeling in free metabolites and biomass was analyzed by NMR and GC-MS. After taking into account the labeling of substrates supplied by the metabolically active cob, the fluxes through central metabolism were quantified by computer-aided modeling. The flux map indicates that 51-69% of the ATP produced is used for biomass synthesis and up to 47% is expended in substrate cycling. These findings point to potential engineering targets for improving yield and increasing oil contents by, respectively, reducing substrate cycling and increasing the commitment of plastidic carbon into fatty acid synthesis at the level of pyruvate kinase.

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.

Molecular dissection of heterosis manifestation during early maize root development

Heterosis is of paramount agronomic importance and has been successfully exploited in maize hybrid breeding for decades. Nevertheless, the molecular basis of heterosis remains elusive. Heterosis is not only observed in adult traits like yield or plant height, but is already detected during embryo and seedling development. Hence, the maize (Zea mays L.) primary root which is the first organ that emerges after germination is a suitable model to study heterosis manifestation. Various seedling root traits including primary root length and lateral root density display heterosis. Microarray studies suggest organ specific patterns of nonadditive gene expression in maize hybrids. Moreover, such experiments support the notion that global expression trends in maize primary roots are conserved between different hybrids. Furthermore, nonadditive expression patterns of specific genes such as a SUPEROXIDE DISMUTASE 2 might contribute to the early manifestation of heterosis. Proteome profiling experiments of maize hybrid primary roots revealed nonadditive accumulation patterns that were distinct from the corresponding RNA profiles underscoring the importance of posttranscriptional processes such as protein modifications that might be related to heterosis. Finally, analysis of selected metabolites imply that a subtle regulation of particular biochemical pathways such as the phenylpropanoid pathway in hybrids might contribute to the manifestation of heterosis in maize primary roots. In the future, recently developed molecular tools will facilitate the analysis of the molecular principles underlying heterosis in maize roots.

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

Major storage reserves of Arabidopsis (Arabidopsis thaliana) seeds are triacylglycerols (seed oils) and proteins. Seed oil content is severely reduced for the regulatory mutant wrinkled1 (wri1-1; At3g54320) and for a double mutant in two isoforms of plastidic pyruvate kinase (pkpbeta(1)pkpalpha; At5g52920 and At3g22960). Both already biochemically well-characterized mutants were now studied by (13)C metabolic flux analysis of cultured developing embryos based on comparison with their respective genetic wild-type backgrounds. For both mutations, in seeds as well as in cultured embryos, the oil fraction was strongly reduced while the fractions of proteins and free metabolites increased. Flux analysis in cultured embryos revealed changes in nutrient uptakes and fluxes into biomass as well as an increase in tricarboxylic acid cycle activity for both mutations. While in both wild types plastidic pyruvate kinase (PK(p)) provides most of the pyruvate for plastidic fatty acid synthesis, the flux through PK(p) is reduced in pkpbeta(1)pkpalpha by 43% of the wild-type value. In wri1-1, PK(p) flux is even more reduced (by 82%), although the genes PKpbeta(1) and PKpalpha are still expressed. Along a common paradigm of metabolic control theory, it is hypothesized that a large reduction in PK(p) enzyme activity in pkpbeta(1)pkpalpha has less effect on PK(p) flux than multiple smaller reductions in glycolytic enzymes in wri1-1. In addition, only in the wri1-1 mutant is the large reduction in PK(p) flux compensated in part by an increased import of cytosolic pyruvate and by plastidic malic enzyme. No such limited compensatory bypass could be observed in pkpbeta(1)pkpalpha.

Metabolic flux analysis in plants: coping with complexity

Theory and experience in metabolic engineering both show that metabolism operates at the network level. In plants, this complexity is compounded by a high degree of compartmentation and the synthesis of a very wide array of secondary metabolic products. A further challenge to understanding and predicting plant metabolic function is posed by our ignorance about the structure of metabolic networks even in well-studied systems. Metabolic flux analysis (MFA) provides tools to measure and model the functioning of metabolism, and is making significant contributions to coping with their complexity. This review gives an overview of different MFA approaches, the measurements required to implement them and the information they yield. The application of MFA methods to plant systems is then illustrated by several examples from the recent literature. Next, the challenges that plant metabolism poses for MFA are discussed together with ways that these can be addressed. Lastly, new developments in MFA are described that can be expected to improve the range and reliability of plant MFA in the coming years.

A joint transcriptomic, proteomic and metabolic analysis of maize endosperm development and starch filling

The maize endosperm transcriptome was investigated through cDNA libraries developed at three characteristic stages: (i) lag phase [10 days after pollination (DAP)]; (ii) beginning of storage (14 DAP); and (iii) maximum starch accumulation rate (21 DAP). Expressed sequence tags for 711, 757 and 384 relevant clones, respectively, were obtained and checked manually. The proportion of sequences with no clear function decreased from 35% to 20%, and a large increase in storage protein sequences (i.e. 5% to 38%) was observed from stages (i) to (iii). The remaining major categories included metabolism (11%-13%), transcription-RNA processing-protein synthesis (13%-20%), protein destination (5%-9%), cellular communication (3%-9%) and cell rescue-defence (4%). Good agreement was generally found between category rank in the 10-DAP transcriptome and the recently reported 14-DAP proteome, except that kinases and proteins for RNA processing were not detected in the latter. In the metabolism category, the respiratory pathway transcripts represented the largest proportion (25%-37%), and showed a shift in favour of glycolysis at 21 DAP. At this stage, amino acid metabolism increased to 17%, whereas starch metabolism surprisingly decreased to 7%. A second experiment focused on carbohydrate metabolism by comparing gene expression at three levels (transcripts, proteins and enzyme activities) in relation to substrate or product from 10 to 40 DAP. Here, two distinct patterns were observed: invertases and hexoses were predominant at the beginning, whereas enzyme patterns in the starch pathway, at the three levels, anticipated and paralleled starch accumulation, suggesting that, in most cases, transcriptional control is responsible for the regulation of starch biosynthesis.

Metabolic flux analysis in plants: from intelligent design to rational engineering

Metabolic flux analysis (MFA) is a rapidly developing field concerned with the quantification and understanding of metabolism at the systems level. The application of MFA has produced detailed maps of flow through metabolic networks of a range of plant systems. These maps represent detailed metabolic phenotypes, contribute significantly to our understanding of metabolism in plants, and have led to the discovery of new metabolic routes. The presentation of thorough statistical evaluation with current flux maps has set a new standard for the quality of quantitative flux studies. In microbial systems, powerful methods have been developed for the reconstruction of metabolic networks from genomic and transcriptomic data, pathway analysis, and predictive modeling. This review brings together the recent developments in quantitative MFA and predictive modeling. The application of predictive tools to high quality flux maps in particular promises to be important in the rational metabolic engineering of plants.

Experimental and mathematical approaches to modeling plant metabolic networks

To support their sessile and autotrophic lifestyle higher plants have evolved elaborate networks of metabolic pathways. Dynamic changes in these metabolic networks are among the developmental forces underlying the functional differentiation of organs, tissues and specialized cell types. They are also important in the various interactions of a plant with its environment. Further complexity is added by the extensive compartmentation of the various interconnected metabolic pathways in plants. Thus, although being used widely for assessing the control of metabolic flux in microbes, mathematical modeling approaches that require steady-state approximations are of limited utility for understanding complex plant metabolic networks. However, considerable progress has been made when manageable metabolic subsystems were studied. In this article, we will explain in general terms and using simple examples the concepts underlying stoichiometric modeling (metabolic flux analysis and metabolic pathway analysis) and kinetic approaches to modeling (including metabolic control analysis as a special case). Selected studies demonstrating the prospects of these approaches, or combinations of them, for understanding the control of flux through particular plant pathways are discussed. We argue that iterative cycles of (dry) mathematical modeling and (wet) laboratory testing will become increasingly important for simulating the distribution of flux in plant metabolic networks and deriving rational experimental designs for metabolic engineering efforts.

Compartment-specific labeling information in 13C metabolic flux analysis of plants

Metabolic engineering of plants has great potential for the low cost production of chemical feedstocks and novel compounds, but to take full advantage of this potential a better understanding of plant central carbon metabolism is needed. Flux studies define the cellular phenotype of living systems and can facilitate rational metabolic engineering. However the measurements usually made in these analyses are often not sufficient to reliably determine many fluxes that are distributed between different subcellular compartments of eukaryotic cells. We have begun to address this shortcoming by increasing the number and quality of measurements that provide (13)C labeling information from specific compartments within the plant cell. The analysis of fatty acid groups, cell wall components, protein glycans, and starch, using both gas chromatography/mass spectrometry and nuclear magnetic resonance spectroscopy are presented here. Fatty acid labeling determinations are sometimes highly convoluted. Derivatization to butyl amides reduces the errors in isotopomer resolution and quantification, resulting in better determination of fluxes into seed lipid reserves, including both plastidic and cytosolic reactions. While cell walls can account for a third or more of biomass in many seeds, no quantitative cell wall labeling measurements have been reported for plant flux analysis. Hydrolyzing cell wall and derivatizing sugars to the alditol acetates, provides novel labeling information and thereby can improve identification of flux through upper glycolytic intermediates of the cytosol. These strategies improve the quantification of key carbon fluxes in the compartmentalized flux network of plant cells.

Sequence-indexed mutations in maize using the UniformMu transposon-tagging population

BACKGROUND

Gene knockouts are a critical resource for functional genomics. In Arabidopsis, comprehensive knockout collections were generated by amplifying and sequencing genomic DNA flanking insertion mutants. These Flanking Sequence Tags (FSTs) map each mutant to a specific locus within the genome. In maize, FSTs have been generated using DNA transposons. Transposable elements can generate unstable insertions that are difficult to analyze for simple knockout phenotypes. Transposons can also generate somatic insertions that fail to segregate in subsequent generations.

RESULTS

Transposon insertion sites from 106 UniformMu FSTs were tested for inheritance by locus-specific PCR. We confirmed 89% of the FSTs to be germinal transposon insertions. We found no evidence for somatic insertions within the 11% of insertion sites that were not confirmed. Instead, this subset of insertion sites had errors in locus-specific primer design due to incomplete or low-quality genomic sequences. The locus-specific PCR assays identified a knockout of a 6-phosphogluconate dehydrogenase gene that co-segregates with a seed mutant phenotype. The mutant phenotype linked to this knockout generates novel hypotheses about the role for the plastid-localized oxidative pentose phosphate pathway during grain-fill.

CONCLUSION

We show that FSTs from the UniformMu population identify stable, germinal insertion sites in maize. Moreover, we show that these sequence-indexed mutations can be readily used for reverse genetic analysis. We conclude from these data that the current collection of 1,882 non-redundant insertion sites from UniformMu provide a genome-wide resource for reverse genetics.

Metabolic flux analysis: recent advances in carbon metabolism in plants

Isotopic tracers are used to both trace metabolic pathways and quantify fluxes through these pathways. The use of different labeling methods recently led to profound changes in our views of plant metabolism. Examples are taken from primary metabolism, with sugar interconversions, carbon partitioning between glycolysis and the pentose phosphate pathway, or metabolite inputs into the tricarboxylic acid (TCA) cycle, as well as from secondary metabolism with the relative contribution of the plastidial and cytosolic pathways to the biosynthesis of terpenoids. While labeling methods are often distinguished according to the instruments used for label detection, emphasis is put here on labeling duration. Short time labeling is adequate to study limited areas of the metabolic network. Long-term labeling, when designed to obtain metabolic and isotopic steady-state, allows to calculate various fluxes in large areas ofcentral metabolism. After longer labeling periods, large amounts of label accumulate in structural or storage compounds: their detailed study through the retrobiosynthetic method gives access to the biosynthetic pathways of otherwise undetectable precursors. This chapter presents the power and limits of the different methods, and illustrates how they can be associated with each other and with other methods of cell biology, to provide the information needed for a rational approach of metabolic engineering.

Rapid metabolism of glucose detected with FRET glucose nanosensors in epidermal cells and intact roots of Arabidopsis RNA-silencing mutants

Genetically encoded glucose nanosensors have been used to measure steady state glucose levels in mammalian cytosol, nuclei, and endoplasmic reticulum. Unfortunately, the same nanosensors in Arabidopsis thaliana transformants manifested transgene silencing and undetectable fluorescence resonance energy transfer changes. Expressing nanosensors in sgs3 and rdr6 transgene silencing mutants eliminated silencing and resulted in high fluorescence levels. To measure glucose changes over a wide range (nanomolar to millimolar), nanosensors with higher signal-to-noise ratios were expressed in these mutants. Perfusion of leaf epidermis with glucose led to concentration-dependent ratio changes for nanosensors with in vitro K(d) values of 600 microM (FLIPglu-600 microDelta13) and 3.2 mM (FLIPglu-3.2 mDelta13), but one with 170 nM K(d) (FLIPglu-170 nDelta13) showed no response. In intact roots, FLIPglu-3.2 mDelta13 gave no response, whereas FLIPglu-600 microDelta13, FLIPglu-2 microDelta13, and FLIPglu-170 nDelta13 all responded to glucose. These results demonstrate that cytosolic steady state glucose levels depend on external supply in both leaves and roots, but under the conditions tested they are lower in root versus epidermal and guard cells. Without photosynthesis and external supply, cytosolic glucose can decrease to <90 nM in root cells. Thus, observed gradients are steeper than expected, and steady state levels do not appear subject to tight homeostatic control. Nanosensor-expressing plants can be used to assess glucose flux differences between cells, invertase-mediated sucrose hydrolysis in vivo, delivery of assimilates to roots, and glucose flux in mutants affected in sugar transport, metabolism, and signaling.

Robustness of central carbohydrate metabolism in developing maize kernels

The central carbohydrate metabolism provides the precursors for the syntheses of various storage products in seeds. While the underlying biochemical map is well established, little is known about the organization and flexibility of carbohydrate metabolic fluxes in the face of changing biosynthetic demands or other perturbations. This question was addressed in developing kernels of maize (Zea mays L.), a model system for the study of starch and sugar metabolism. (13)C-labeling experiments were carried out with inbred lines, heterotic hybrids, and starch-deficient mutants that were selected to cover a wide range of performances and kernel phenotypes. In total, 46 labeling experiments were carried out using either [U-(13)C(6)]glucose or [U-(13)C(12)]sucrose and up to three stages of kernel development. Carbohydrate flux distributions were estimated based on glucose isotopologue abundances, which were determined in hydrolysates of starch by using quantitative (13)C-NMR and GC-MS. Similar labeling patterns in all samples indicated robustness of carbohydrate fluxes in maize endosperm, and fluxes were rather stable in response to glucose or sucrose feeding and during development. A lack of ADP-glucose pyrophosphorylase in the bt2 and sh2 mutants triggered significantly increased hexose cycling. In contrast, other mutations with similar kernel phenotypes had no effect. Thus, the distribution of carbohydrate fluxes is stable and not determined by sink strength in maize kernels.