A metabolic flux analysis to study the role of sucrose synthase in the regulation of the carbon partitioning in central metabolism in maize root tips

Visualizing 13C-Labeled Metabolites in Maize Root Tips with Mass Spectrometry Imaging

Tracing in vivo isotope-labeled metabolites has been used to study metabolic pathways or flux analysis. However, metabolic differences between the cells have been often ignored in these studies due to the limitation of solvent-based extraction. Here we demonstrate that the mass spectrometry imaging of in vivo isotope-labeled metabolites, referred to as MSIi, can provide important insights into metabolic dynamics with cellular resolution that may supplement the traditional metabolomics and flux analysis. Developing maize root tips are adopted as a model system for MSIi by supplementing 200 mM [U-13C]glucose in 0.1x Hoagland medium. MSIi data sets were acquired for longitudinal sections of newly grown maize root tips after growing 5 days in the medium. A total of 56 metabolite features were determined to have been 13C-labeled based on accurate mass and the number of carbon matching with the metabolite databases. Simple sugars and their derivatives were fully labeled, but some small metabolites were partially labeled with a significant amount of fully unlabeled metabolites still present, suggesting the recycling of "old" metabolites in the newly grown tissues. Some distinct localizations were found, including the low abundance of hexose and its derivatives in the meristem, the high abundance of amino acids in the meristem, and the localization to epidermal and endodermal cells for lipids and their intermediates. Fatty acids and lipids were slow in metabolic turnover and showed various isotopologue distributions with intermediate building blocks, which may provide flux information for their biosynthesis.

Overexpression of ZmSUS1 increased drought resistance of maize (Zea mays L.) by regulating sucrose metabolism and soluble sugar content

MAIN CONCLUSION

ZmSUS1 improved drought tolerance of maize by regulating sucrose metabolism and increasing soluble sugar content, and endowing transgenic maize with higher relative water content and photosynthesis levels. Sucrose synthase (SUS), a key enzyme of sugar metabolism, plays an important role in the regulation of carbon partitioning in plant, and affects important agronomic traits and abiotic responses to adversity. However, the function of ZmSUS1 in plant drought tolerance is still unknown. In this study, the expression patterns of ZmSUS1 in different tissues and under drought stress were analyzed in maize (Zea mays L.). It was found that ZmSUS1 was highly expressed during kernel development but also in leaves and roots of maize, and ZmSUS1 was induced by drought stress. Homozygous transgenic maize lines overexpressing ZmSUS1 increased the content and activity of SUS under drought stress and exhibited higher relative water content, proline and abscisic acid content in leaves. Specifically, the net photosynthetic rate and the soluble sugar contents including sucrose, glucose, fructose and SUS decomposition products including UDP-glucose (UDP-G) and ADP-glucose (ADP-G) in transgenic plants were significantly improved after drought stress. RNA-seq analysis showed that overexpressing of ZmSUS1 mainly affected the expression level of carbon metabolism-related genes. Especially the expression level of sucrose metabolism-related genes including sucrose phosphatase gene (SPP), sucrose phosphate synthase gene (SPS) and invertase gene (INV) were significantly up-regulated in transgenic maize. Overall, these results suggested that ZmSUS1 improved drought tolerance by regulating sucrose metabolism and increasing the soluble sugar content, and endowing transgenic maize with higher relative water content and photosynthesis levels, which can serve as a new gene candidate for cultivating drought-resistant maize varieties.

Non-conventional pathways enable pennycress (Thlaspi arvense L.) embryos to achieve high efficiency of oil biosynthesis

Pennycress (Thlaspi arvense L.) accumulates oil up to 35% of the total seed biomass, and its overall fatty acid composition is suitable for aviation fuel. However, for this plant to become economically viable, its oil production needs to be improved. In vivo culture conditions that resemble the development of pennycress embryos in planta were developed based on the composition of the liquid endosperm. Then, substrate uptake rates and biomass accumulation were measured from cultured pennycress embryos, revealing a biosynthetic efficiency of 93%, which is one of the highest in comparison with other oilseeds to date. Additionally, the ratio of carbon in oil to CO2 indicated that non-conventional pathways are likely to be responsible for such a high carbon conversion efficiency. To identify the reactions enabling this phenomenon, parallel labeling experiments with 13C-labeled substrates were conducted in pennycress embryos. The main findings of these labeling experiments include: (i) the occurrence of the oxidative reactions of the pentose phosphate pathway in the cytosol; (ii) the reversibility of isocitrate dehydrogenase; (iii) the operation of the plastidic NADP-dependent malic enzyme; and (iv) the refixation of CO2 by Rubisco. These reactions are key providers of carbon and reductant for fatty acid synthesis and elongation.

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism enables the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In the many studies using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For ¹³C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

Liquid Chromatography Tandem Mass Spectrometry Quantification of 13C-Labeling in Sugars

Subcellular compartmentation has been challenging in plant ¹³C-metabolic flux analysis. Indeed, plant cells are highly compartmented: they contain vacuoles and plastids in addition to the regular organelles found in other eukaryotes. The distinction of reactions between compartments is possible when metabolites are synthesized in a particular compartment or by a unique pathway. Sucrose is an example of such a metabolite: it is specifically produced in the cytosol from glucose 6-phosphate (G6P) and fructose 6-phosphate (F6P). Therefore, determining the ¹³C-labeling in the fructosyl and glucosyl moieties of sucrose directly informs about the labeling of cytosolic F6P and G6P, respectively. To date, the most commonly used method to monitor sucrose labeling is by nuclear magnetic resonance, which requires substantial amounts of biological sample. This study describes a new methodology that accurately measures the labeling in free sugars using liquid chromatography tandem mass spectrometry (LC-MS/MS). For this purpose, maize embryos were pulsed with [U-¹³C]-fructose, intracellular sugars were extracted, and their time-course labeling was analyzed by LC-MS/MS. Additionally, extracts were enzymatically treated with hexokinase to remove the soluble hexoses, and then invertase to cleave sucrose into fructose and glucose. Finally, the labeling in the glucosyl and fructosyl moieties of sucrose was determined by LC-MS/MS.

Cell-Type Specific Metabolic Flux Analysis: A Challenge for Metabolic Phenotyping and a Potential Solution in Plants

Stable isotope labelling experiments are used routinely in metabolic flux analysis (MFA) to determine the metabolic phenotype of cells and tissues. A complication arises in multicellular systems because single cell measurements of transcriptomes, proteomes and metabolomes in multicellular organisms suggest that the metabolic phenotype will differ between cell types. In silico analysis of simulated metabolite isotopomer datasets shows that cellular heterogeneity confounds conventional MFA because labelling data averaged over multiple cell types does not necessarily yield averaged flux values. A potential solution to this problem—the use of cell-type specific reporter proteins as a source of cell-type specific labelling data—is proposed and the practicality of implementing this strategy in the roots of Arabidopsis thaliana seedlings is explored. A protocol for the immunopurification of ectopically expressed green fluorescent protein (GFP) from Arabidopsis thaliana seedlings using a GFP-binding nanobody is developed, and through GC-MS analysis of protein hydrolysates it is established that constitutively expressed GFP reports accurately on the labelling of total protein in root tissues. It is also demonstrated that the constitutive expression of GFP does not perturb metabolism. The principal obstacle to the implementation of the method in tissues with cell-type specific GFP expression is the sensitivity of the GC-MS system.

Plant metabolism as studied by NMR spectroscopy

The study of plant metabolism impacts a broad range of domains such as plant cultural practices, plant breeding, human or animal nutrition, phytochemistry and green biotechnologies. Plant metabolites are extremely diverse in terms of structure or compound families as well as concentrations. This review attempts to illustrate how NMR spectroscopy, with its broad variety of experimental approaches, has contributed widely to the study of plant primary or specialized metabolism in very diverse ways. The review presents recent developments of one-dimensional and multi-dimensional NMR methods to study various aspects of plant metabolism. Through recent examples, it highlights how NMR has proved to be an invaluable tool for the global characterization of sample composition within metabolomic studies, and shows some examples of use for targeted phytochemistry, with a special focus on compound identification and quantitation. In such cases, NMR approaches are often used to provide snapshots of the plant sample composition. The review also covers dynamic aspects of metabolism, with a description of NMR techniques to measure metabolic fluxes - in most cases after stable isotope labelling. It is mainly intended for NMR specialists who would be interested to learn more about the potential of their favourite technique in plant sciences and about specific details of NMR approaches in this field. Therefore, as a practical guide, a paragraph on the specific precautions that should be taken for sample preparation is also included. In addition, since the quality of NMR metabolic studies is highly dependent on approaches to data processing and data sharing, a specific part is dedicated to these aspects. The review concludes with perspectives on the emerging methods that could change significantly the role of NMR in the field of plant metabolism by boosting its sensitivity. The review is illustrated throughout with examples of studies selected to represent diverse applications of liquid-state or HR-MAS NMR.

Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii

Despite the wealth of knowledge available for C. reinhardtii, the central metabolic fluxes of growth on acetate have not yet been determined. In this study, ¹³C-metabolic flux analysis (¹³C-MFA) was used to determine and quantify the metabolic pathways of primary metabolism in C. reinhardtii cells grown under heterotrophic conditions with acetate as the sole carbon source. Isotopic labeling patterns of compartment specific biomass derived metabolites were used to calculate the fluxes. It was found that acetate is ligated with coenzyme A in the three subcellular compartments (cytosol, mitochondria and plastid) included in the model. Two citrate synthases were found to potentially be involved in acetyl-coA metabolism; one localized in the mitochondria and the other acting outside the mitochondria. Labeling patterns demonstrate that Acetyl-coA synthesized in the plastid is directly incorporated in synthesis of fatty acids. Despite having a complete TCA cycle in the mitochondria, it was also found that a majority of the malate flux is shuttled to the cytosol and plastid where it is converted to oxaloacetate providing reducing equivalents to these compartments. When compared to predictions by flux balance analysis, fluxes measured with ¹³C-MFA were found to be suboptimal with respect to biomass yield; C. reinhardtii sacrifices biomass yield to produce ATP and reducing equivalents.

Plant lipidomics at the crossroads: From technology to biology driven science

The identification and quantification of lipids from plant tissues have become commonplace and many researchers now incorporate lipidomics approaches into their experimental studies. Plant lipidomics research continues to involve technological developments such as those in mass spectrometry imaging, but in large part, lipidomics approaches have matured to the point of being accessible to the novice. Here we review some important considerations for those planning to apply plant lipidomics to their biological questions, and offer suggestions for appropriate tools and practices. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

Dynamic Labeling Reveals Temporal Changes in Carbon Re-Allocation within the Central Metabolism of Developing Apple Fruit

In recent years, the application of isotopically labeled substrates has received extensive attention in plant physiology. Measuring the propagation of the label through metabolic networks may provide information on carbon allocation in sink fruit during fruit development. In this research, gas chromatography coupled to mass spectrometry based metabolite profiling was used to characterize the changing metabolic pool sizes in developing apple fruit at five growth stages (30, 58, 93, 121, and 149 days after full bloom) using ¹³C-isotope feeding experiments on hypanthium tissue discs. Following the feeding of [U-¹³C]glucose, the ¹³C-label was incorporated into the various metabolites to different degrees depending on incubation time, metabolic pathway activity, and growth stage. Evidence is presented that early in fruit development the utilization of the imported sugars was faster than in later developmental stages, likely to supply the energy and carbon skeletons required for cell division and fruit growth. The declined ¹³C-incorporation into various metabolites during growth and maturation can be associated with the reduced metabolic activity, as mirrored by the respiratory rate. Moreover, the concentration of fructose and sucrose increased during fruit development, whereas concentrations of most amino and organic acids and polyphenols declined. In general, this study showed that the imported compounds play a central role not only in carbohydrate metabolism, but also in the biosynthesis of amino acid and related protein synthesis and secondary metabolites at the early stage of fruit development.

Can stable isotope mass spectrometry replace ‎radiolabelled approaches in metabolic studies?

Metabolic pathways and the key regulatory points thereof can be deduced using isotopically labelled substrates. One prerequisite is the accurate measurement of the labeling pattern of targeted metabolites. The subsequent estimation of metabolic fluxes following incubation in radiolabelled substrates has been extensively used. Radiolabelling is a sensitive approach and allows determination of total label uptake since the total radiolabel content is easy to detect. However, the incubation of cells, tissues or the whole plant in a stable isotope enriched environment and the use of either mass spectrometry or nuclear magnetic resonance techniques to determine label incorporation within specific metabolites offers the possibility to readily obtain metabolic information with higher resolution. It additionally also offers an important complement to other post-genomic strategies such as metabolite profiling providing insights into the regulation of the metabolic network and thus allowing a more thorough description of plant cellular function. Thus, although safety concerns mean that stable isotope feeding is generally preferred, the techniques are in truth highly complementary and application of both approaches in tandem currently probably provides the best route towards a comprehensive understanding of plant cellular metabolism.

Effect of organochlorine pesticides exposure on the maize root metabolome assessed using high-resolution magic-angle spinning (1)H NMR spectroscopy

(1)H-HRMAS NMR-based metabolomics was used to better understand the toxic effects on maize root tips of organochlorine pesticides (OCPs), namely lindane (γHCH) and chlordecone (CLD). Maize seedlings were exposed to 2.5 μM γHCH (mimicking basic environmental contaminations) for 7 days and compared to 2.5 μM CLD and 25 μM γHCH for 7 days (mimicking hot spot contaminations). The (1)H-HRMAS NMR-based metabolomic profiles provided details of the changes in carbohydrates, amino acids, tricarboxylic acid (TCA) cycle intermediates and fatty acids with a significant separation between the control and OCP-exposed root tips. First of all, alterations in the balance between glycolysis/gluconeogenesis were observed with sucrose depletion and with dose-dependent fluctuations in glucose content. Secondly, observations indicated that OCPs might inactivate the TCA cycle, with sizeable succinate and fumarate depletion. Thirdly, disturbances in the amino acid composition (GABA, glutamine/glutamate, asparagine, isoleucine) reflected a new distribution of internal nitrogen compounds under OCP stress. Finally, OCP exposure caused an increase in fatty acid content, concomitant with a marked rise in oxidized fatty acids which could indicate failures in cell integrity and vitality. Moreover, the accumulation of asparagine and oxidized fatty acids with the induction of LOX3 transcription levels under OCP exposure highlighted an induction of protein and lipid catabolism. The overall data indicated that the effect of OCPs on primary metabolism could have broader physiological consequences on root development. Therefore, (1)H-HRMAS NMR metabolomics is a sensitive tool for understanding molecular disturbances under OCP exposure and can be used to perform a rapid assessment of phytotoxicity.

Changes and their possible causes in δ13C of dark-respired CO2 and its putative bulk and soluble sources during maize ontogeny

The issues of whether, where, and to what extent carbon isotopic fractionations occur during respiration affect interpretations of plant functions that are important to many disciplines across the natural sciences. Studies of carbon isotopic fractionation during dark respiration in C3 plants have repeatedly shown respired CO2 to be (13)C enriched relative to its bulk leaf sources and (13)C depleted relative to its bulk root sources. Furthermore, two studies showed respired CO2 to become progressively (13)C enriched during leaf ontogeny and (13)C depleted during root ontogeny in C3 legumes. As such data on C4 plants are scarce and contradictory, we investigated apparent respiratory fractionations of carbon and their possible causes in different organs of maize plants during early ontogeny. As in the C3 plants, leaf-respired CO2 was (13)C enriched whereas root-respired CO2 was (13)C depleted relative to their putative sources. In contrast to the findings for C3 plants, however, not only root- but also leaf-respired CO2 became more (13)C depleted during ontogeny. Leaf-respired CO2 was highly (13)C enriched just after light-dark transition but the enrichment rapidly decreased over time in darkness. We conclude that (i) although carbon isotopic fractionations in C4 maize and leguminous C3 crop roots are similar, increasing phosphoenolpyruvate-carboxylase activity during maize ontogeny could have produced the contrast between the progressive (13)C depletion of maize leaf-respired CO2 and (13)C enrichment of C3 leaf-respired CO2 over time, and (ii) in both maize and C3 leaves, highly (13)C enriched leaf-respired CO2 at light-to-dark transition and its rapid decrease during darkness, together with the observed decrease in leaf malate content, may be the result of a transient effect of light-enhanced dark respiration.

Transcriptional Analysis of Resistance to Low Temperatures in Bermudagrass Crown Tissues

Bermudagrass (Cynodon dactylon L pers.) is one of the most geographically adapted and utilized of the warm-season grasses. However, bermudagrass adaptation to the Northern USA is limited by freeze damage and winterkill. Our study provides the first large-scale analyses of gene expression in bermudagrass regenerative crown tissues during cold acclimation. We compared gene expression patterns in crown tissues from highly cold tolerant "MSU" and susceptible "Zebra" genotypes exposed to near-freezing temperatures. Suppressive subtractive hybridization was used to isolate putative cold responsive genes Approximately, 3845 transcript sequences enriched for cold acclimation were deposited in the GenBank. A total of 4589 ESTs (3184 unigenes) including 744 ESTs associated with the bermudagrass disease spring dead spot were printed on microarrays and hybridized with cold acclimated complementary Deoxyribonucleic acid (cDNA). A total of 587 differentially expressed unigenes were identified in this study. Of these only 97 (17%) showed significant NCBI matches. The overall expression pattern revealed 40% more down- than up-regulated genes, which was particularly enhanced in MSU compared to Zebra. Among the up-regulated genes 68% were uniquely expressed in MSU (36%) or Zebra (32%). Among the down-regulated genes 40% were unique to MSU, while only 15% to Zebra. Overall expression intensity was significantly higher in MSU than in Zebra (p value ≤ 0.001) and the overall number of genes expressed at 28 days was 2.7 fold greater than at 2 days. These changes in expression patterns reflect the strong genotypic and temporal response to cold temperatures. Additionally, differentially expressed genes from this study can be utilized for developing molecular markers in bermudagrass and other warm season grasses for enhancing cold hardiness.

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.

Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli

The use of parallel labeling experiments for (13)C metabolic flux analysis ((13)C-MFA) has emerged in recent years as the new gold standard in fluxomics. The methodology has been termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. In this contribution, we have tested the limits of COMPLETE-MFA by demonstrating integrated analysis of 14 parallel labeling experiments with Escherichia coli. An effort on such a massive scale has never been attempted before. In addition to several widely used isotopic tracers such as [1,2-(13)C]glucose and mixtures of [1-(13)C]glucose and [U-(13)C]glucose, four novel tracers were applied in this study: [2,3-(13)C]glucose, [4,5,6-(13)C]glucose, [2,3,4,5,6-(13)C]glucose and a mixture of [1-(13)C]glucose and [4,5,6-(13)C]glucose. This allowed us for the first time to compare the performance of a large number of isotopic tracers. Overall, there was no single best tracer for the entire E. coli metabolic network model. Tracers that produced well-resolved fluxes in the upper part of metabolism (glycolysis and pentose phosphate pathways) showed poor performance for fluxes in the lower part of metabolism (TCA cycle and anaplerotic reactions), and vice versa. The best tracer for upper metabolism was 80% [1-(13)C]glucose+20% [U-(13)C]glucose, while [4,5,6-(13)C]glucose and [5-(13)C]glucose both produced optimal flux resolution in the lower part of metabolism. COMPLETE-MFA improved both flux precision and flux observability, i.e. more independent fluxes were resolved with smaller confidence intervals, especially exchange fluxes. Overall, this study demonstrates that COMPLETE-MFA is a powerful approach for improving flux measurements and that this methodology should be considered in future studies that require very high flux resolution.

¹⁴C pulse labeling to estimate external fluxes and turnovers in primary metabolism

Steady state (13)C-MFA is classically used to measure fluxes in complex metabolic networks. However, the modeling of steady state labeling allows the quantification of internal fluxes only and requires the estimation, by other methods, of the external fluxes, corresponding to substrate uptake (carbon input into the network) and to the production rate of compounds that accumulate within plant cells (network output). Additionally, it is not always possible to discriminate between different pathways that lead to the same label distribution. Methods to measure fluxes, based on direct measurements of pool size and on (14)C short-time labeling experiments, are described in this chapter. To illustrate this approach, we focus on the quantification of sucrose and starch turnovers.

Analysis of isotopic labeling in peptide fragments by tandem mass spectrometry

Phenotype in multicellular organisms is the consequence of dynamic metabolic events that occur in a spatially dependent fashion. This spatial and temporal complexity presents challenges for investigating metabolism; creating a need for improved methods that effectively probe biochemical events such as amino acid biosynthesis. Isotopic labeling can provide a temporal-spatial recording of metabolic events through, for example, the description of enriched amino acids in the protein pool. Proteins are therefore an important readout of metabolism and can be assessed with modern mass spectrometers. We compared the measurement of isotopic labeling in MS2 spectra obtained from tandem mass spectrometry under either higher energy collision dissociation (HCD) or collision induced dissociation (CID) at varied energy levels. Developing soybean embryos cultured with or without 13C-labeled substrates, and Escherichia coli MG1655 enriched by feeding 7% uniformly labeled glucose served as a source of biological material for protein evaluation. CID with low energies resulted in a disproportionate amount of heavier isotopologues remaining in the precursor isotopic distribution. HCD resulted in fewer quantifiable products; however deviation from predicted distributions were small relative to the CID-based comparisons. Fragment ions have the potential to provide information on the labeling of amino acids in peptides, but our results indicate that without further development the use of this readout in quantitative methods such as metabolic flux analysis is limited.

Liquid chromatography tandem mass spectrometry for measuring ¹³C-labeling in intermediates of the glycolysis and pentose phosphate pathway

This chapter describes a procedure to analyze (13)C-labeled phosphorylated compounds by liquid chromatography tandem mass spectrometry. Phosphorylated compounds, intermediaries of the glycolysis and pentose phosphate pathway, are separated by anion exchange chromatography and their isotopic labeling is determined by mass spectrometry. A sensitivity in the fmole range is achieved using scheduled multiple reaction monitoring mode.

Application of metabolic flux analysis to plants

This volume compiles a series of chapters that cover the major aspects of plant metabolic flux analysis, such as but not limited to labeling of plant material, acquisition of labeling data, mathematical modeling of metabolic network at the cell, tissue, and plant level. A short revue, including methodological points and applications of flux analysis to plants, is presented in this introductory chapter.

A device for single leaf labelling with CO2 isotopes to study carbon allocation and partitioning in Arabidopsis thaliana

BACKGROUND

Plant biomass consists primarily of carbohydrates derived from photosynthesis. Monitoring the assimilation of carbon via the Calvin-Benson cycle and its subsequent utilisation is fundamental to understanding plant growth. The use of stable and radioactive carbon isotopes, supplied to plants as CO2, allows the measurement of fluxes through the intermediates of primary photosynthetic metabolism, long-distance transport of sugars in the vasculature, and the synthesis of structural and storage components.

RESULTS

Here we describe the design of a system for supplying isotopically labelled CO2 to single leaves of Arabidopsis thaliana. We demonstrate that the system works well using short pulses of 14CO2 and that it can be used to produce robust qualitative and quantitative data about carbon export from source leaves to the sink tissues, such as the developing leaves and the roots. Time course experiments show the dynamics of carbon partitioning between storage as starch, local production of biomass, and export of carbon to sink tissues.

CONCLUSION

This isotope labelling method is relatively simple to establish and inexpensive to perform. Our use of 14CO2 helps establish the temporal and spatial allocation of assimilated carbon during plant growth, delivering data complementary to those obtained in recent studies using 13CO2 and MS-based metabolomics techniques. However, we emphasise that this labelling device could also be used effectively in combination with 13CO2 and MS-based techniques.

Modelling metabolic CO₂ evolution--a fresh perspective on respiration

Respiration is a major contributor to net exchange of CO₂ between plants and the atmosphere and thus an important aspect of the vegetation component of global climate change models. However, a mechanistic model of respiration is lacking, and so here we explore the potential for flux balance analysis (FBA) to predict cellular CO₂ evolution rates. Metabolic flux analysis reveals that respiration is not always the dominant source of CO₂, and that metabolic processes such as the oxidative pentose phosphate pathway (OPPP) and lipid synthesis can be quantitatively important. Moreover, there is considerable variation in the metabolic origin of evolved CO₂ between tissues, species and conditions. Comparison of FBA-predicted CO₂ evolution profiles with those determined from flux measurements reveals that FBA is able to predict the metabolic origin of evolved CO₂ in different tissues/species and under different conditions. However, FBA is poor at predicting flux through certain metabolic processes such as the OPPP and we identify the way in which maintenance costs are accounted for as a major area of improvement for future FBA studies. We conclude that FBA, in its standard form, can be used to predict CO₂ evolution in a range of plant tissues and in response to environment.

Metabolomic analysis of key central carbon metabolism carboxylic acids as their 3-nitrophenylhydrazones by UPLC/ESI-MS

Multiple hydroxy-, keto-, di-, and tri-carboxylic acids are among the cellular metabolites of central carbon metabolism (CCM). Sensitive and reliable analysis of these carboxylates is important for many biological and cell engineering studies. In this work, we examined 3-nitrophenylhydrazine as a derivatizing reagent and optimized the reaction conditions for the measurement of ten CCM-related carboxylic compounds, including glycolate, lactate, malate, fumarate, succinate, citrate, isocitrate, pyruvate, oxaloacetate, and α-ketoglutarate as their 3-nitrophenylhydrazones using LC/MS with ESI. With the derivatization protocol which we have developed, and using negative-ion multiple-reaction monitoring on a triple-quadrupole instrument, all of the carboxylates showed good linearity within a dynamic range of ca. 200 to more than 2000. The on-column LODs and LOQs were from high femtomoles to low picomoles. The analytical accuracies for eight of the ten analytes were determined to be between 89.5 to 114.8% (CV≤7.4%, n = 6). Using a QTOF instrument, the isotopic distribution patterns of these carboxylates, extracted from a (13) C-labeled mouse heart, were successfully determined by UPLC/MS with full-mass detection, indicating the possible utility of this analytical method for metabolic flux analysis. In summary, this work demonstrates an efficient chemical derivatization LC/MS method for metabolomic analysis of these key CCM intermediates in a biological matrix.

Metabolic engineering with plants for a sustainable biobased economy

Plants are bona fide sustainable organisms because they accumulate carbon and synthesize beneficial metabolites from photosynthesis. To meet the challenges to food security and health threatened by increasing population growth and depletion of nonrenewable natural resources, recent metabolic engineering efforts have shifted from single pathways to holistic approaches with multiple genes owing to integration of omics technologies. Successful engineering of plants results in the high yield of biomass components for primary food sources and biofuel feedstocks, pharmaceuticals, and platform chemicals through synthetic biology and systems biology strategies. Further discovery of undefined biosynthesis pathways in plants, integrative analysis of discrete omics data, and diversified process developments for production of platform chemicals are essential to overcome the hurdles for sustainable production of value-added biomolecules from plants.

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.

Parallel labeling experiments and metabolic flux analysis: Past, present and future methodologies

Radioactive and stable isotopes have been applied for decades to elucidate metabolic pathways and quantify carbon flow in cellular systems using mass and isotope balancing approaches. Isotope-labeling experiments can be conducted as a single tracer experiment, or as parallel labeling experiments. In the latter case, several experiments are performed under identical conditions except for the choice of substrate labeling. In this review, we highlight robust approaches for probing metabolism and addressing metabolically related questions though parallel labeling experiments. In the first part, we provide a brief historical perspective on parallel labeling experiments, from the early metabolic studies when radioisotopes were predominant to present-day applications based on stable-isotopes. We also elaborate on important technical and theoretical advances that have facilitated the transition from radioisotopes to stable-isotopes. In the second part of the review, we focus on parallel labeling experiments for (13)C-metabolic flux analysis ((13)C-MFA). Parallel experiments offer several advantages that include: tailoring experiments to resolve specific fluxes with high precision; reducing the length of labeling experiments by introducing multiple entry-points of isotopes; validating biochemical network models; and improving the performance of (13)C-MFA in systems where the number of measurements is limited. We conclude by discussing some challenges facing the use of parallel labeling experiments for (13)C-MFA and highlight the need to address issues related to biological variability, data integration, and rational tracer selection.

Research progresses on the key enzymes involved in sucrose metabolism in maize

Sucrose, as the major product of photosynthesis, is a vital metabolite and signaling molecule in higher plants. Three enzymes are responsible for the synthesis, transport, and degradation of sucrose. In this article, the gene structure, expression and regulation, and the physiological functions of the key enzymes involved in sucrose metabolism in maize are reviewed, moreover, the existing problems of the sucrose metabolism research were discussed in detail, and we present our ideas for future research.

Are we ready for genome-scale modeling in plants?

As it is becoming easier and faster to generate various types of high-throughput data, one would expect that by now we should have a comprehensive systems-level understanding of biology, biochemistry, and physiology at least in major prokaryotic and eukaryotic model systems. Despite the wealth of available data, we only get a glimpse of what is going on at the molecular level from the global perspective. The major reason is the high level of cellular complexity and our limited ability to identify all (or at least important) components and their interactions in virtually infinite number of internal and external conditions. Metabolism can be modeled mathematically by the use of genome-scale models (GEMs). GEMs are in silico metabolic flux models derived from available genome annotation. These models predict the combination of flux values of a defined metabolic network given the influence of internal and external signals. GEMs have been successfully implemented to model bacterial metabolism for over a decade. However, it was not until 2009 when the first GEM for Arabidopsis thaliana cell-suspension cultures was generated. Genome-scale modeling ("GEMing") in plants brings new challenges primarily due to the missing components and complexity of plant cells represented by the existence of: (i) photosynthesis; (ii) compartmentation; (iii) variety of cell and tissue types; and (iv) diverse metabolic responses to environmental and developmental cues as well as pathogens, insects, and competing weeds. This review presents a critical discussion of the advantages of existing plant GEMs, while identifies key targets for future improvements. Plant GEMs tend to be accurate in predicting qualitative changes in selected aspects of central carbon metabolism, while secondary metabolism is largely neglected mainly due to the missing (unknown) genes and metabolites. As such, these models are suitable for exploring metabolism in plants grown in favorable conditions, but not in field-grown plants that have to cope with environmental changes in complex ecosystems. AraGEM is the first GEM describing a photosynthetic and photorespiring plant cell (Arabidopsis thaliana). We demonstrate the use of AraGEM given the current (limited) knowledge of plant metabolism and reveal the unexpected robustness of AraGEM by a series of in silico simulations. The major focus of these simulations is on the assessment of the: (i) network connectivity; (ii) influence of CO₂ and photon uptake rates on cellular growth rates and production of individual biomass components; and (iii) stability of plant central carbon metabolism with internal pH changes.

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.

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.

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.

Kinetic modeling and sensitivity analysis of xylose metabolism in Lactococcus lactis IO-1

We proposed a kinetic simulation model of xylose metabolism in Lactococcus lactis IO-1 that describes the dynamic behavior of metabolites using the simulator WinBEST-KIT. This model was developed by comparing the experimental time-course data of metabolites in batch cultures grown in media with initial xylose concentrations of 20.3-57.8 g/l with corresponding calculated data. By introducing the terms of substrate activation, substrate inhibition, and product inhibition, the revised model showed a squared correlation coefficient (r2) of 0.929 between the experimental time-course of metabolites and the calculated data. Thus, the revised model is assumed to be one of the best candidates for kinetic simulation describing the dynamic behavior of metabolites. Sensitivity analysis revealed that pyruvate flux distribution is important for higher lactate production. To confirm the validity of our kinetic model, the results of the sensitivity analysis were compared with enzyme activities observed during increasing lactate production by adding natural rubber serum powder to the xylose medium. The experimental results on pyruvate flux distribution were consistent with the prediction by sensitivity analysis.

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.

Low-temperature effect on enzyme activities involved in sucrose-starch partitioning in salt-stressed and salt-acclimated cotyledons of quinoa (Chenopodium quinoa Willd.) seedlings

The effect of low temperature on growth, sucrose-starch partitioning and related enzymes in salt-stressed and salt-acclimated cotyledons of quinoa (Chenopodium quinoa Willd.) was studied. The growth of cotyledons and growing axes in seedlings grown at 25/20 degrees C (light/dark) and shifted to 5/5 degrees C was lower than in those only growing at 25/20 degrees C (unstressed). However, there were no significant differences between low-temperature control and salt-treated seedlings. The higher activities of sucrose phosphate synthase (SPS, EC 2.4.1.14) and soluble acid invertase (acid INV, EC 3.2.1.25) were observed in salt-stressed cotyledons; however, the highest acid INV activity was observed in unstressed cotyledons. ADP-glucose pyrophosphorylase (ADP-GPPase, EC 2.7.7.27) was higher in unstressed cotyledons than in stressed ones. However, between 0 and 4days the highest value was observed in salt-stressed cotyledons. The lowest value of ADP-GPPase was observed in salt-acclimated cotyledons. Low temperature also affected sucrose synthase (SuSy, EC 2.4.1.13) activity in salt-treated cotyledons. Sucrose and glucose were higher in salt-stressed cotyledons, but fructose was essentially higher in low-temperature control. Starch was higher in low-temperature control; however, the highest content was observed at 0day in salt-acclimated cotyledons. Results demonstrated that low temperature induces different responses on sucrose-starch partitioning in salt-stressed and salt-acclimated cotyledons. Data also suggest that in salt-treated cotyledons source-sink relations (SSR) are changed in order to supply soluble sugars and proline for the osmotic adjustment. Relationships between starch formation and SuSy activity are also discussed.

Low temperature maximizes growth of Crocus vernus (L.) Hill via changes in carbon partitioning and corm development

In Crocus vernus, a spring bulbous species, prolonged growth at low temperatures results in the development of larger perennial organs and delayed foliar senescence. Because corm growth is known to stop before the first visual sign of leaf senescence, it is clear that factors other than leaf duration alone determine final corm size. The aim of this study was to determine whether reduced growth at higher temperatures was due to decreased carbon import to the corm or to changes in the partitioning of this carbon once it had reached the corm. Plants were grown under two temperature regimes and the amount of carbon fixed, transported, and converted into a storable form in the corm, as well as the partitioning into soluble carbohydrates, starch, and the cell wall, were monitored during the growth cycle. The reduced growth at higher temperature could not be explained by a restriction in carbon supply or by a reduced ability to convert the carbon into starch. However, under the higher temperature regime, the plant allocated more carbon to cell wall material, and the amount of glucose within the corm declined earlier in the season. Hexose to sucrose ratios might control the duration of corm growth in C. vernus by influencing the timing of the cell division, elongation, and maturation phases. It is suggested that it is this shift in carbon partitioning, not limited carbon supply or leaf duration, which is responsible for the smaller final biomass of the corm at higher temperatures.

Metabolic network fluxes in heterotrophic Arabidopsis cells: stability of the flux distribution under different oxygenation conditions

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% +/- 5% of carbon entering used for biosynthesis under standard O(2) conditions and 33% +/- 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.