The metabolic architecture of plant cells. Stability of central metabolism and flexibility of anabolic pathways during the growth cycle of tomato cells

Line-field dynamic optical coherence tomography platform for volumetric assessment of biological tissues

Dynamic optical coherence tomography (dOCT) utilizes time-dependent signal intensity fluctuations to enhance contrast in OCT images and indirectly probe physiological processes in cells. Majority of the dOCT studies published so far are based on acquisition of 2D images (B-scans or C-scans) by utilizing point-scanning Fourier domain (spectral or swept-source) OCT or full-field OCT respectively, primarily due to limitations in the image acquisition rate. Here we introduce a novel, high-speed spectral domain line-field dOCT (SD-LF-dOCT) system and image acquisition protocols designed for fast, volumetric dOCT imaging of biological tissues. The imaging probe is based on an exchangeable afocal lens pair that enables selection of combinations of transverse resolution (from 1.1 µm to 6.4 µm) and FOV (from 250 × 250 µm2 to 1.4 × 1.4 mm2), suitable for different biomedical applications. The system offers axial resolution of ∼ 1.9 µm in biological tissue, assuming an average refractive index of 1.38. Maximum sensitivity of 90.5 dB is achieved for 3.5 mW optical imaging power at the tissue surface and maximum camera acquisition rate of 2,000 fps. Volumetric dOCT images acquired with the SD-LF-dOCT system from plant tissue (cucumber), animal tissue (mouse liver) and human prostate carcinoma spheroids allow for volumetric visualization of the tissues' cellular and sub-cellular structures and assessment of cellular motility.

Plant Heterotrophic Cultures: No Food, No Growth

Plant cells are capable of uptaking exogenous organic substances. This inherited trait allows the development of heterotrophic cell cultures in various plants. The most common of them are Nicotiana tabacum and Arabidopsis thaliana. Plant cells are widely used in academic studies and as factories for valuable substance production. The repertoire of compounds supporting the heterotrophic growth of plant cells is limited. The best growth of cultures is ensured by oligosaccharides and their cleavage products. Primarily, these are sucrose, raffinose, glucose and fructose. Other molecules such as glycerol, carbonic acids, starch, and mannitol have the ability to support growth occasionally, or in combination with another substrate. Culture growth is accompanied by processes of specialization, such as elongation growth. This determines the pattern of the carbon budget. Culture ageing is closely linked to substrate depletion, changes in medium composition, and cell physiological rearrangements. A lack of substrate leads to starvation, which results in a decrease in physiological activity and the mobilization of resources, and finally in the loss of viability. The cause of the instability of cultivated cells may be the non-optimal metabolism under cultural conditions or the insufficiency of internal regulation.

Carbon Fluxes in Potato (Solanum tuberosum) Remain Stable in Cell Cultures Exposed to Nutritional Phosphate Deficiency

Nutritional phosphate deficiency is a major limitation to plant growth. Here, we monitored fluxes in pathways supporting respiratory metabolism in potato (Solanum tuberosum) cell cultures growing in control or limiting phosphate conditions. Sugar uptake was quantified using [U-14C]sucrose as precursor. Carbohydrate degradation through glycolysis and respiratory pathways was estimated using the catabolism of [U-14C]sucrose to 14CO2. Anaplerotic carbon flux was assessed by labeling with NaH14CO3. The data showed that these metabolic fluxes displayed distinct patterns over culture time. However, phosphate depletion had relatively little impact on the various fluxes. Sucrose uptake was higher during the first six days of culture, followed by a decline, which was steeper in Pi-sufficient cells. Anaplerotic pathway flux was more important at day three and decreased thereafter. In contrast, the flux between sucrose and CO2 was at a maximum in the mid-log phase of the culture, with a peak at Day 6. Metabolization of [U-14C]sucrose into neutral, basic and acidic fractions was also unaffected by phosphate nutrition. Hence, the well-documented changes in central metabolism enzymes activities in response to Pi deficiency do not drastically modify metabolic fluxes, but rather result in the maintenance of the carbon fluxes that support respiration.

Primary Metabolite Screening Shows Significant Differences between Embryogenic and Non-Embryogenic Callus of Tamarillo (Solanum betaceum Cav.)

Tamarillo is a solanaceous tree that has been extensively studied in terms of in vitro clonal propagation, namely somatic embryogenesis. In this work, a protocol of indirect somatic embryogenesis was applied to obtain embryogenic and non-embryogenic callus from leaf segments. Nuclear magnetic resonance spectroscopy was used to analyze the primary metabolome of these distinct calli to elucidate possible differentiation mechanisms from the common genetic background callus. Standard multivariate analysis methods were then applied, and were complemented by univariate statistical methods to identify differentially expressed primary metabolites and related metabolic pathways. The results showed carbohydrate and lipid metabolism to be the most relevant in all the calli assayed, with most discriminant metabolites being fructose, glucose and to a lesser extent choline. The glycolytic rate was higher in embryogenic calli, which shows, overall, a higher rate of sugar catabolism and a different profile of phospholipids with a choline/ethanolamine analysis. In general, our results show that a distinct primary metabolome between embryogenic and non-embryogenic calli occurs and that intracellular levels of fructose and sucrose and the glucose to sucrose ratio seem to be good candidates as biochemical biomarkers of embryogenic competence.

Elevated carbon assimilation and metabolic reprogramming in tomato high pigment mutants support the increased production of pigments

High pigment mutants in tomato (Solanum lycopersicum L.), a loss of function in the control of photomorphogenesis, with greater pigment production, show altered growth, greater photosynthesis, and a metabolic reprogramming. High pigment mutations cause plants to be extremely responsive to light and produce excessive pigmentation as well as fruits with high levels of health-beneficial nutrients. However, the association of these traits with changes in the physiology and metabolism of leaves remains poorly understood. Here, we performed a detailed morphophysiological and metabolic characterization of high pigment 1 (hp1) and high pigment 2 (hp2) mutants in tomato (Solanum lycopersicum L. 'Micro-Tom') plants under different sunlight conditions (natural light, 50% shading, and 80% shading). These mutants occur in the DDB1 (hp1) and DET1 (hp2) genes, which are related to the regulation of photomorphogenesis and chloroplast development. Our results demonstrate that these mutations delay plant growth and height, by affecting physiological and metabolic parameters at all stages of plant development. Although the mutants were characterized by higher net CO₂ assimilation, lower stomatal limitation, and higher carboxylation rates, with anatomical changes that favour photosynthesis, we found that carbohydrate levels did not increase, indicating a change in the energy flow. Shading minimized the differences between mutants and the wild type or fully reversed them in the phenotype at the metabolic level. Our results indicate that the high levels of pigments in hp1 and hp2 mutants represent an additional energy cost for these plants and that extensive physiological and metabolic reprogramming occurs to support increased pigment biosynthesis.

Osmoregulation and its actions during the drought stress in plants

Drought stress, which causes a decline in quality and quantity of crop yields, has become more accentuated these days due to climatic change. Serious measures need to be taken to increase the tolerance of crop plants to acute drought conditions likely to occur due to global warming. Drought stress causes many physiological and biochemical changes in plants, rendering the maintenance of osmotic adjustment highly crucial. The degree of plant resistance to drought varies with plant species and cultivars, phenological stages of the plant, and the duration of plant exposure to the stress. Osmoregulation in plants under low water potential relies on synthesis and accumulation of osmoprotectants or osmolytes such as soluble proteins, sugars, and sugar alcohols, quaternary ammonium compounds, and amino acids, like proline. This review highlights the role of osmolytes in water-stressed plants and of enzymes entailed in their metabolism. It will be useful, especially for researchers working on the development of drought-resistant crops by using the metabolic-engineering techniques.

New Insight into Justicidin B Pathway and Production in Linum austriacum

Lignans are the main secondary metabolites synthetized by Linum species as plant defense compounds but they are also valuable for human health, in particular, for novel therapeutics. In this work, Linum austriacum in vitro cultures, cells (Cc), adventitious roots (ARc) and hairy roots (HRc) were developed for the production of justicidin B through elicitation with methyl jasmonate (MeJA) and coronatine (COR). The performances of the cultures were evaluated for their stability, total phenols content and antioxidant ability. NMR was used to identify justicidin B and isojusticidin B and HPLC to quantify the production, highlighting ARc and HRc as the highest productive tissues. MeJA and COR treatments induced the synthesis of justicidin B more than three times and the synthesis of other compounds. RNA-sequencing and a de novo assembly of L. austriacum ARc transcriptome was generated to identify the genes activated by MeJA. Furthermore, for the first time, the intracellular localization of justicidin B in ARc was investigated through microscopic analysis. Then, HRc was chosen for small-scale production in a bioreactor. Altogether, our results improve knowledge on justicidin B pathway and cellular localization in L. austriacum for future scale-up processes.

Morphological and metabolic profiling of a tropical-adapted potato association panel subjected to water recovery treatment reveals new insights into plant vigor

Potato (Solanum tuberosum L.) is one of the world's most important crops, but it is facing major challenges due to climatic changes. To investigate the effects of intermittent drought on the natural variability of plant morphology and tuber metabolism in a novel potato association panel comprising 258 varieties we performed an augmented block design field study under normal irrigation and under water-deficit and recovery conditions in Ica, Peru. All potato genotypes were profiled for 45 morphological traits and 42 central metabolites via nuclear magnetic resonance. Statistical tests and norm of reaction analysis revealed that the observed variations were trait specific, that is, genotypic versus environmental. Principal component analysis showed a separation of samples as a result of conditional changes. To explore the relational ties between morphological traits and metabolites, correlation-based network analysis was employed, constructing one network for normal irrigation and one network for water-recovery samples. Community detection and difference network analysis highlighted the differences between the two networks, revealing a significant correlational link between fumarate and plant vigor. A genome-wide association study was performed for each metabolic trait. Eleven single nucleotide polymorphism (SNP) markers were associated with fumarate. Gene Ontology analysis of quantitative trait loci regions associated with fumarate revealed an enrichment of genes regulating metabolic processes. Three of the 11 SNPs were located within genes, coding for a protein of unknown function, a RING domain protein and a zinc finger protein ZAT2. Our findings have important implications for future potato breeding regimes, especially in countries suffering from climate change.

Model-assisted identification of metabolic engineering strategies for Jatropha curcas lipid pathways

Efficient approaches to increase plant lipid production are necessary to meet current industrial demands for this important resource. While Jatropha curcas cell culture can be used for in vitro lipid production, scaling up the system for industrial applications requires an understanding of how growth conditions affect lipid metabolism and yield. Here we present a bottom-up metabolic reconstruction of J. curcas supported with labeling experiments and biomass characterization under three growth conditions. We show that the metabolic model can accurately predict growth and distribution of fluxes in cell cultures and use these findings to pinpoint energy expenditures that affect lipid biosynthesis and metabolism. In addition, by using constraint-based modeling approaches we identify network reactions whose joint manipulation optimizes lipid production. The proposed model and computational analyses provide a stepping stone for future rational optimization of other agronomically relevant traits in J. curcas.

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.

Flux balance analysis of metabolism during growth by osmotic cell expansion and its application to tomato fruits

Cell expansion is a significant contributor to organ growth and is driven by the accumulation of osmolytes to increase cell turgor pressure. Metabolic modelling has the potential to provide insights into the processes that underpin osmolyte synthesis and transport, but the main computational approach for predicting metabolic network fluxes, flux balance analysis, often uses biomass composition as the main output constraint and ignores potential changes in cell volume. Here we present growth-by-osmotic-expansion flux balance analysis (GrOE-FBA), a framework that accounts for both the metabolic and ionic contributions to the osmotica that drive cell expansion, as well as the synthesis of protein, cell wall and cell membrane components required for cell enlargement. Using GrOE-FBA, the metabolic fluxes in dividing and expanding cells were analysed, and the energetic costs for metabolite biosynthesis and accumulation in the two scenarios were found to be surprisingly similar. The expansion phase of tomato fruit growth was also modelled using a multiphase single-optimization GrOE-FBA model and this approach gave accurate predictions of the major metabolite levels throughout fruit development, as well as revealing a role for transitory starch accumulation in ensuring optimal fruit development.

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.

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.

ABA and sucrose co-regulate strawberry fruit ripening and show inhibition of glycolysis

Abscisic acid (ABA) and sucrose play an important role in strawberry fruit ripening, but how ABA and sucrose co-regulate this ripening progress remains unclear. The intention of this study was to examine the effect of ABA and sucrose on strawberry fruit ripening and to evaluate the ABA/sucrose interaction mechanism on the strawberry fruit ripening process. Here, we report that there is an acute synergistic effect between ABA and sucrose in accelerating strawberry fruit ripening. The time frame of fruit development and ripening was shortened after the application of ABA, sucrose, and ABA + sucrose, but most of the major quality parameters in treated-ripe fruit, including fruit weight, total soluble solids, anthocyanin, ascorbic acid, the total phenolic content, lightness (L*), chroma (C*), and hue angle (h°) values were not affected. Meanwhile, the endogenous ABA and sucrose levels, and the expression of ABA and sucrose signaling genes and ripening-related genes, such as NCED1, NCED2, SnRK2.2, SuSy, MYB5, CEL1, and CEL2, was all significantly enhanced by ABA or sucrose treatment alone, but in particular, by the ABA + sucrose treatment. Therefore, improving the ripening regulation efficiency is one synergetic action of ABA/sucrose. Another synergetic action of ABA/sucrose shows that a short inhibition of glycolysis occurs during accelerated strawberry ripening. ABA and sucrose can induce higher accumulation of H₂O₂, leading to a transient decrease in glycolysis. Conversely, lower endogenous H₂O₂ levels caused by reduced glutathione (GSH) treatment resulted in a transient increase in glycolysis while delaying strawberry fruit ripening. Collectively, this study demonstrates that the ABA/sucrose interaction affects the ripening regulation efficiency and shows inhibition of glycolysis.

Adaptation of Plants to Salt Stress: Characterization of Na+ and K+ Transporters and Role of CBL Gene Family in Regulating Salt Stress Response

Salinity is one of the most serious factors limiting the productivity of agricultural crops, with adverse effects on germination, plant vigor, and crop yield. This salinity may be natural or induced by agricultural activities such as irrigation or the use of certain types of fertilizer. The most detrimental effect of salinity stress is the accumulation of Na+ and Cl− ions in tissues of plants exposed to soils with high NaCl concentrations. The entry of both Na+ and Cl− into the cells causes severe ion imbalance, and excess uptake might cause significant physiological disorder(s). High Na+ concentration inhibits the uptake of K+, which is an element for plant growth and development that results in lower productivity and may even lead to death. The genetic analyses revealed K+ and Na+ transport systems such as SOS1, which belong to the CBL gene family and play a key role in the transport of Na+ from the roots to the aerial parts in the Arabidopsis plant. In this review, we mainly discuss the roles of alkaline cations K+ and Na+, Ion homeostasis-transport determinants, and their regulation. Moreover, we tried to give a synthetic overview of soil salinity, its effects on plants, and tolerance mechanisms to withstand stress.

Sustained substrate cycles between hexose phosphates and free sugars in phosphate-deficient potato (Solanum tuberosum) cell cultures

Futile cycling between free sugars and hexose phosphates occurring under phosphate deficiency could be involved in the maintenance of a threshold level of free cellular phosphate to preserve respiratory metabolism. We studied the metabolic response of potato cell cultures growing in Pi sufficient (2.5 mM, +Pi) or deficient (125 µM, -Pi) conditions. Under Pi deficiency, cellular growth was severely affected, however -Pi cells were able to maintain a low but steady level of free Pi. We surveyed the activities of 33 primary metabolic enzymes during the course of a 12 days Pi deficiency period. Our results show that many of these enzymes had higher specific activity in -Pi cells. Among these, we found typical markers of Pi deficiency such as phosphoenolpyruvate phosphatase and phosphoenolpyruvate carboxylase as well as enzymes involved in the biosynthesis of organic acids. Intriguingly, several ATP-consuming enzymes such as hexokinase (HK) and phosphofructokinase also displayed increased activity in -Pi condition. For HK, this was associated with an increase in the steady state of a specific HK polypeptide. Quantification of glycolytic intermediates showed a pronounced decrease in phosphate esters under Pi deficiency. Adenylate levels also decreased in -Pi cells, but the Adenylate Energy Charge was not affected by the treatment. To investigate the significance of HK induction under low Pi, [U-¹⁴C]-glucose tracer studies were conducted. We found in vivo evidence of futile cycling between pools of hexose phosphates and free sugars under Pi deficiency. Our study suggests that the futile cycling between hexose phosphates and free sugars which is active under +Pi conditions is sustained under Pi deficiency. The possibility that this process represents a metabolic adaptation to Pi deficiency is discussed with respect to Pi homeostasis in Pi-deficient conditions.

Unraveling the Initial Plant Hormone Signaling, Metabolic Mechanisms and Plant Defense Triggering the Endomycorrhizal Symbiosis Behavior

Arbuscular mycorrhizal (AM) fungi establish probably one of the oldest mutualistic relationships with the roots of most plants on earth. The wide distribution of these fungi in almost all soil ecotypes and the broad range of host plant species demonstrate their strong plasticity to cope with various environmental conditions. AM fungi elaborate fine-tuned molecular interactions with plants that determine their spread within root cortical tissues. Interactions with endomycorrhizal fungi can bring various benefits to plants, such as improved nutritional status, higher photosynthesis, protection against biotic and abiotic stresses based on regulation of many physiological processes which participate in promoting plant performances. In turn, host plants provide a specific habitat as physical support and a favorable metabolic frame, allowing uptake and assimilation of compounds required for the life cycle completion of these obligate biotrophic fungi. The search for formal and direct evidences of fungal energetic needs raised strong motivated projects since decades, but the impossibility to produce AM fungi under axenic conditions remains a deep enigma and still feeds numerous debates. Here, we review and discuss the initial favorable and non-favorable metabolic plant context that may fate the mycorrhizal behavior, with a focus on hormone interplays and their links with mitochondrial respiration, carbon partitioning and plant defense system, structured according to the action of phosphorus as a main limiting factor for mycorrhizal symbiosis. Then, we provide with models and discuss their significances to propose metabolic targets that could allow to develop innovations for the production and application of AM fungal inocula.

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.

The Genetics of Plant Metabolism

Plant metabolic studies have traditionally focused on the role and regulation of the enzymes catalyzing key reactions within specific pathways. Within the past 20 years, reverse genetic approaches have allowed direct determination of the effects of the deficiency, or surplus, of a given protein on the biochemistry of a plant. In parallel, top-down approaches have also been taken, which rely on screening broad, natural genetic diversity for metabolic diversity. Here, we compare and contrast the various strategies that have been adopted to enhance our understanding of the natural diversity of metabolism. We also detail how these approaches have enhanced our understanding of both specific and global aspects of the genetic regulation of metabolism. Finally, we discuss how such approaches are providing important insights into the evolution of plant secondary metabolism.

First principle-based models in plant suspension cell cultures: a review

In this work, the development and application of published models for describing the behavior of plant cell cultures is reviewed. The structure of each type of model is analyzed and the new tendencies for the modeling of biotechnological processes that can be applied in plant cell cultures are presented. This review is a tool for clarifying the main features that characterize each type of model in the field of plant cell cultures and can be used as a support on the selection of the more suitable model type, taking into account the purpose of specific research.

Fluxomics links cellular functional analyses to whole-plant phenotyping

Fluxes through metabolic pathways reflect the integration of genetic and metabolic regulations. While it is attractive to measure all the mRNAs (transcriptome), all the proteins (proteome), and a large number of the metabolites (metabolome) in a given cellular system, linking and integrating this information remains difficult. Measurement of metabolome-wide fluxes (termed the fluxome) provides an integrated functional output of the cell machinery and a better tool to link functional analyses to plant phenotyping. This review presents and discusses sets of methodologies that have been developed to measure the fluxome. First, the principles of metabolic flux analysis (MFA), its 'short time interval' version Inst-MFA, and of constraints-based methods, such as flux balance analysis and kinetic analysis, are briefly described. The use of these powerful methods for flux characterization at the cellular scale up to the organ (fruits, seeds) and whole-plant level is illustrated. The added value given by fluxomics methods for unravelling how the abiotic environment affects flux, the process, and key metabolic steps are also described. Challenges associated with the development of fluxomics and its integration with 'omics' for thorough plant and organ functional phenotyping are discussed. Taken together, these will ultimately provide crucial clues for identifying appropriate target plant phenotypes for breeding.

Genome-wide Analysis of Phosphoenolpyruvate Carboxylase Gene Family and Their Response to Abiotic Stresses in Soybean

Phosphoenolpyruvate carboxylase (PEPC) plays an important role in assimilating atmospheric CO2 during C4 and crassulacean acid metabolism photosynthesis, and also participates in various non-photosynthetic processes, including fruit ripening, stomatal opening, supporting carbon-nitrogen interactions, seed formation and germination, and regulation of plant tolerance to stresses. However, a comprehensive analysis of PEPC family in Glycine max has not been reported. Here, a total of ten PEPC genes were identified in soybean and denominated as GmPEPC1-GmPEPC10. Based on the phylogenetic analysis of the PEPC proteins from 13 higher plant species including soybean, PEPC family could be classified into two subfamilies, which was further supported by analyses of their conserved motifs and gene structures. Nineteen cis-regulatory elements related to phytohormones, abiotic and biotic stresses were identified in the promoter regions of GmPEPC genes, indicating their roles in soybean development and stress responses. GmPEPC genes were expressed in various soybean tissues and most of them responded to the exogenously applied phytohormones. GmPEPC6, GmPEPC8 and GmPEPC9 were significantly induced by aluminum toxicity, cold, osmotic and salt stresses. In addition, the enzyme activities of soybean PEPCs were also up-regulated by these treatments, suggesting their potential roles in soybean response to abiotic stresses.

SWAPDT: A method for Short-time Withering Assessment of Probability for Drought Tolerance in Camellia sinensis validated by targeted metabolomics

Climate change is causing droughts affecting crop production on a global scale. Classical breeding and selection strategies for drought-tolerant cultivars will help prevent crop losses. Plant breeders, for all crops, need a simple and reliable method to identify drought-tolerant cultivars, but such a method is missing. Plant metabolism is often disrupted by abiotic stress conditions. To survive drought, plants reconfigure their metabolic pathways. Studies have documented the importance of metabolic regulation, i.e. osmolyte accumulation such as polyols and sugars (mannitol, sorbitol); amino acids (proline) during drought. This study identified and quantified metabolites in drought tolerant and drought susceptible Camellia sinensis cultivars under wet and drought stress conditions. For analyses, GC-MS and LC-MS were employed for metabolomics analysis.%RWC results show how the two drought tolerant and two drought susceptible cultivars differed significantly (p≤0.05) from one another; the drought susceptible exhibited rapid water loss compared to the drought tolerant. There was a significant variation (p<0.05) in metabolite content (amino acid, sugars) between drought tolerant and drought susceptible tea cultivars after short-time withering conditions. These metabolite changes were similar to those seen in other plant species under drought conditions, thus validating this method. The Short-time Withering Assessment of Probability for Drought Tolerance (SWAPDT) method presented here provides an easy method to identify drought tolerant tea cultivars that will mitigate the effects of drought due to climate change on crop losses.

Flux Balance Analysis of Plant Metabolism: The Effect of Biomass Composition and Model Structure on Model Predictions

The biomass composition represented in constraint-based metabolic models is a key component for predicting cellular metabolism using flux balance analysis (FBA). Despite major advances in analytical technologies, it is often challenging to obtain a detailed composition of all major biomass components experimentally. Studies examining the influence of the biomass composition on the predictions of metabolic models have so far mostly been done on models of microorganisms. Little is known about the impact of varying biomass composition on flux prediction in FBA models of plants, whose metabolism is very versatile and complex because of the presence of multiple subcellular compartments. Also, the published metabolic models of plants differ in size and complexity. In this study, we examined the sensitivity of the predicted fluxes of plant metabolic models to biomass composition and model structure. These questions were addressed by evaluating the sensitivity of predictions of growth rates and central carbon metabolic fluxes to varying biomass compositions in three different genome-/large-scale metabolic models of Arabidopsis thaliana. Our results showed that fluxes through the central carbon metabolism were robust to changes in biomass composition. Nevertheless, comparisons between the predictions from three models using identical modeling constraints and objective function showed that model predictions were sensitive to the structure of the models, highlighting large discrepancies between the published models.

Correlation-Based Network Analysis of Metabolite and Enzyme Profiles Reveals a Role of Citrate Biosynthesis in Modulating N and C Metabolism in Zea mays

To investigate the natural variability of leaf metabolism and enzymatic activity in a maize inbred population, statistical and network analyses were employed on metabolite and enzyme profiles. The test of coefficient of variation showed that sugars and amino acids displayed opposite trends in their variance within the population, consistently with their related enzymes. The overall higher CV values for metabolites as compared to the tested enzymes are indicative for their greater phenotypic plasticity. H(2) tests revealed galactinol (1) and asparagine (0.91) as the highest scorers among metabolites and nitrate reductase (0.73), NAD-glutamate dehydrogenase (0.52), and phosphoglucomutase (0.51) among enzymes. The overall low H(2) scores for metabolites and enzymes are suggestive for a great environmental impact or gene-environment interaction. Correlation-based network generation followed by community detection analysis, partitioned the network into three main communities and one dyad, (i) reflecting the different levels of phenotypic plasticity of the two molecular classes as observed for the CV values and (ii) highlighting the concerted changes between classes of chemically related metabolites. Community 1 is composed mainly of enzymes and specialized metabolites, community 2' is enriched in N-containing compounds and phosphorylated-intermediates. The third community contains mainly organic acids and sugars. Cross-community linkages are supported by aspartate, by the photorespiration amino acids glycine and serine, by the metabolically related GABA and putrescine, and by citrate. The latter displayed the strongest node-betweenness value (185.25) of all nodes highlighting its fundamental structural role in the connectivity of the network by linking between different communities and to the also strongly connected enzyme aldolase.

Integrative Approaches to Enhance Understanding of Plant Metabolic Pathway Structure and Regulation

Huge insight into molecular mechanisms and biological network coordination have been achieved following the application of various profiling technologies. Our knowledge of how the different molecular entities of the cell interact with one another suggests that, nevertheless, integration of data from different techniques could drive a more comprehensive understanding of the data emanating from different techniques. Here, we provide an overview of how such data integration is being used to aid the understanding of metabolic pathway structure and regulation. We choose to focus on the pairwise integration of large-scale metabolite data with that of the transcriptomic, proteomics, whole-genome sequence, growth- and yield-associated phenotypes, and archival functional genomic data sets. In doing so, we attempt to provide an update on approaches that integrate data obtained at different levels to reach a better understanding of either single gene function or metabolic pathway structure and regulation within the context of a broader biological process.

Primary metabolism plays a central role in moulding silicon-inducible brown spot resistance in rice

Over recent decades, a multitude of studies have shown the ability of silicon (Si) to protect various plants against a range of microbial pathogens exhibiting different lifestyles and infection strategies. Despite this relative wealth of knowledge, an understanding of the action mechanism of Si is still in its infancy, which hinders its widespread application for agricultural purposes. In an attempt to further elucidate the molecular underpinnings of Si-induced disease resistance, we studied the transcriptome of control and Si-treated rice plants infected with the necrotrophic brown spot fungus Cochliobolus miyabeanus. Analysis of brown spot-infected control plants suggested that C. miyabeanus represses plant photosynthetic processes and nitrate reduction in order to trigger premature senescence and cause disease. In Si-treated plants, however, these pathogen-induced metabolic alterations are strongly impaired, suggesting that Si alleviates stress imposed by the pathogen. Interestingly, Si also significantly increased photorespiration rates in brown spot-infected plants. Although photorespiration is often considered as a wasteful process, recent studies have indicated that this metabolic bypass also enhances resistance during abiotic stress and pathogen attack by protecting the plant's photosynthetic machinery. In view of these findings, our results favour a scenario in which Si enhances brown spot resistance by counteracting C. miyabeanus-induced senescence and cell death via increased photorespiration. Moreover, our results shed light onto the mechanistic basis of Si-induced disease control and support the view that, in addition to activating plant immune responses, Si can also reduce disease severity by interfering with pathogen virulence strategies.

Biosynthesis of hydrocarbons and volatile organic compounds by fungi: bioengineering potential

Recent advances in the biological production of fuels have relied on the optimization of pathways involving genes from diverse organisms. Several recent articles have highlighted the potential to expand the pool of useful genes by looking to filamentous fungi. This review highlights the enzymes and organisms used for the production of a variety of fuel types and commodity chemicals with a focus on the usefulness and promise of those from filamentous fungi.

Fluxes through plant metabolic networks: measurements, predictions, insights and challenges

Although the flows of material through metabolic networks are central to cell function, they are not easy to measure other than at the level of inputs and outputs. This is particularly true in plant cells, where the network spans multiple subcellular compartments and where the network may function either heterotrophically or photoautotrophically. For many years, kinetic modelling of pathways provided the only method for describing the operation of fragments of the network. However, more recently, it has become possible to map the fluxes in central carbon metabolism using the stable isotope labelling techniques of metabolic flux analysis (MFA), and to predict intracellular fluxes using constraints-based modelling procedures such as flux balance analysis (FBA). These approaches were originally developed for the analysis of microbial metabolism, but over the last decade, they have been adapted for the more demanding analysis of plant metabolic networks. Here, the principal features of MFA and FBA as applied to plants are outlined, followed by a discussion of the insights that have been gained into plant metabolic networks through the application of these time-consuming and non-trivial methods. The discussion focuses on how a system-wide view of plant metabolism has increased our understanding of network structure, metabolic perturbations and the provision of reducing power and energy for cell function. Current methodological challenges that limit the scope of plant MFA are discussed and particular emphasis is placed on the importance of developing methods for cell-specific MFA.

Modelling central metabolic fluxes by constraint-based optimization reveals metabolic reprogramming of developing Solanum lycopersicum (tomato) fruit

Modelling of metabolic networks is a powerful tool to analyse the behaviour of developing plant organs, including fruits. Guided by our current understanding of heterotrophic metabolism of plant cells, a medium-scale stoichiometric model, including the balance of co-factors and energy, was constructed in order to describe metabolic shifts that occur through the nine sequential stages of Solanum lycopersicum (tomato) fruit development. The measured concentrations of the main biomass components and the accumulated metabolites in the pericarp, determined at each stage, were fitted in order to calculate, by derivation, the corresponding external fluxes. They were used as constraints to solve the model by minimizing the internal fluxes. The distribution of the calculated fluxes of central metabolism were then analysed and compared with known metabolic behaviours. For instance, the partition of the main metabolic pathways (glycolysis, pentose phosphate pathway, etc.) was relevant throughout fruit development. We also predicted a valid import of carbon and nitrogen by the fruit, as well as a consistent CO2 release. Interestingly, the energetic balance indicates that excess ATP is dissipated just before the onset of ripening, supporting the concept of the climacteric crisis. Finally, the apparent contradiction between calculated fluxes with low values compared with measured enzyme capacities suggest a complex reprogramming of the metabolic machinery during fruit development. With a powerful set of experimental data and an accurate definition of the metabolic system, this work provides important insight into the metabolic and physiological requirements of the developing tomato fruits.

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.

Variability of metabolite levels is linked to differential metabolic pathways in Arabidopsis's responses to abiotic stresses

Constraint-based approaches have been used for integrating data in large-scale metabolic networks to obtain insights into metabolism of various organisms. Due to the underlying steady-state assumption, these approaches are usually not suited for making predictions about metabolite levels. Here, we ask whether we can make inferences about the variability of metabolite levels from a constraint-based analysis based on the integration of transcriptomics data. To this end, we analyze time-resolved transcriptomics and metabolomics data from Arabidopsis thaliana under a set of eight different light and temperature conditions. In a previous study, the gene expression data have already been integrated in a genome-scale metabolic network to predict pathways, termed modulators and sustainers, which are differentially regulated with respect to a biochemically meaningful data-driven null model. Here, we present a follow-up analysis which bridges the gap between flux- and metabolite-centric methods. One of our main findings demonstrates that under certain environmental conditions, the levels of metabolites acting as substrates in modulators or sustainers show significantly lower temporal variations with respect to the remaining measured metabolites. This observation is discussed within the context of a systems-view of plasticity and robustness of metabolite contents and pathway fluxes. Our study paves the way for investigating the existence of similar principles in other species for which both genome-scale networks and high-throughput metabolomics data of high quality are becoming increasingly available.

Transcript abundance on its own cannot be used to infer fluxes in central metabolism

An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism, some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. This limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.

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.

Metabolic network reconstruction and their topological analysis

This chapter focuses on the way to build a metabolic network and how to analyze its structure. The first part of this chapter describes the methods of the network model reconstruction from biochemical data found in specialized databases and/or literature. The second part deals with metabolic pathway analysis as a useful tool for better understanding the complex architecture of intracellular metabolism. The graph analysis and the stoichiometric network analysis are important approaches for understanding the network topology and consequently the function of metabolic networks. Among the methods presented, the Elementary Flux Modes analysis will be more detailed. Finally, we illustrate in this chapter an example of network reconstruction from heterotrophic plant cells metabolism and its topological analysis leading to a huge number of Elementary Flux Modes.

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.

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.

A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions

Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade-off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper-osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper-osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance.

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.

Starch biosynthesis, its regulation and biotechnological approaches to improve crop yields

Structurally composed of the glucose homopolymers amylose and amylopectin, starch is the main storage carbohydrate in vascular plants, and is synthesized in the plastids of both photosynthetic and non-photosynthetic cells. Its abundance as a naturally occurring organic compound is surpassed only by cellulose, and represents both a cornerstone for human and animal nutrition and a feedstock for many non-food industrial applications including production of adhesives, biodegradable materials, and first-generation bioethanol. This review provides an update on the different proposed pathways of starch biosynthesis occurring in both autotrophic and heterotrophic organs, and provides emerging information about the networks regulating them and their interactions with the environment. Special emphasis is given to recent findings showing that volatile compounds emitted by microorganisms promote both growth and the accumulation of exceptionally high levels of starch in mono- and dicotyledonous plants. We also review how plant biotechnologists have attempted to use basic knowledge on starch metabolism for the rational design of genetic engineering traits aimed at increasing starch in annual crop species. Finally we present some potential biotechnological strategies for enhancing starch content.

A dual role of tobacco hexokinase 1 in primary metabolism and sugar sensing

Hexokinase (HXK) is present in all virtually living organisms and is central to carbohydrate metabolism catalysing the ATP-dependent phosphorylation of hexoses. In plants, HXKs are supposed to act as sugar sensors and/or to interact with other enzymes directly supplying metabolic pathways such as glycolysis, the nucleotide phosphate monosaccharide (NDP-glucose) pathway and the pentose phosphate pathway. We identified nine members of the tobacco HXK gene family and observed that among RNAi lines of these nine NtHXKs, only RNAi lines of NtHXK1 showed an altered phenotype, namely stunted growth and leaf chlorosis. NtHXK1 was also the isoform with highest relative expression levels among all NtHXKs. GFP-tagging and immunolocalization indicated that NtHXK1 is associated with mitochondrial membranes. Overexpression of NtHXK1 resulted in elevated glucose phosphorylation activity in leaf extracts or chloroplasts. Moreover, NtHXK1 was able to complement the glucose-insensitive Arabidopsis mutant gin2-1 suggesting that NtHXK1 can take over glucose sensing functions. RNAi lines of NtHXK1 showed severely damaged leaf and chloroplast structure, coinciding with an excess accumulation of starch. We conclude that NtHXK1 is not only essential for maintaining glycolytic activity during respiration but also for regulating starch turnover, especially during the night.

The metabolic flux phenotype of heterotrophic Arabidopsis cells reveals a complex response to changes in nitrogen supply

The extent to which individual plants utilise nitrate and ammonium, the two principal nitrogen sources in the rhizosphere, is variable and many species require a balance between the two forms for optimal growth. The effects of nitrate and ammonium on gene expression, enzyme activity and metabolite composition have been documented extensively with the aim of understanding the way in which plant cells respond to the different forms of nitrogen, but ultimately the impact of these changes on the organisation and operation of the central metabolic network can only be addressed by analysing the fluxes supported by the network. Accordingly steady-state metabolic flux analysis was used to define the metabolic phenotype of a heterotrophic Arabidopsis thaliana cell culture grown in Murashige and Skoog and ammonium-free media, treatments that influenced growth and biomass composition. Fluxes through the central metabolic network were deduced from the redistribution of label into metabolic intermediates and end products observed when cells were labelled with [1-(13) C]-, [2-(13) C]- or [(13) C6 ]glucose, in tandem with (14) C-measurements of the net accumulation of biomass. Analysis of the flux maps showed that: (i) flux through the oxidative pentose phosphate pathway varied independently of the reductant demand for biosynthesis, (ii) non-plastidic processes made a significant and variable contribution to the provision of reducing power for the plastid, and (iii) the inclusion of ammonium in the growth medium increased cell maintenance costs, in agreement with the futile cycling model of ammonium toxicity. These conclusions highlight the complexity of the metabolic response to a change in nitrogen nutrition.

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.

Metabolic fluxes in an illuminated Arabidopsis rosette

Photosynthesis is the basis for life, and its optimization is a key biotechnological aim given the problems of population explosion and environmental deterioration. We describe a method to resolve intracellular fluxes in intact Arabidopsis thaliana rosettes based on time-dependent labeling patterns in the metabolome. Plants photosynthesizing under limiting irradiance and ambient CO2 in a custom-built chamber were transferred into a (13)CO2-enriched environment. The isotope labeling patterns of 40 metabolites were obtained using liquid or gas chromatography coupled to mass spectrometry. Labeling kinetics revealed striking differences between metabolites. At a qualitative level, they matched expectations in terms of pathway topology and stoichiometry, but some unexpected features point to the complexity of subcellular and cellular compartmentation. To achieve quantitative insights, the data set was used for estimating fluxes in the framework of kinetic flux profiling. We benchmarked flux estimates to four classically determined flux signatures of photosynthesis and assessed the robustness of the estimates with respect to different features of the underlying metabolic model and the time-resolved data set.

The futile cycling of hexose phosphates could account for the fact that hexokinase exerts a high control on glucose phosphorylation but not on glycolytic rate in transgenic potato (Solanum tuberosum) roots

The metabolism of potato (Solanum tuberosum) roots constitutively over- and underexpressing hexokinase (HK, EC 2.7.1.1) was examined. An 11-fold variation in HK activity resulted in altered root growth, with antisense roots growing better than sense roots. Quantification of sugars, organic acids and amino acids in transgenic roots demonstrated that the manipulation of HK activity had very little effect on the intracellular pools of these metabolites. However, adenylate and free Pi levels were negatively affected by an increase in HK activity. The flux control coefficient of HK over the phosphorylation of glucose was measured for the first time in plants. Its value varied with HK level. It reached 1.71 at or below normal HK activity value and was much lower (0.32) at very high HK levels. Measurements of glycolytic flux and O₂ uptake rates demonstrated that the differences in glucose phosphorylation did not affect significantly glycolytic and respiratory metabolism. We hypothesized that these results could be explained by the existence of a futile cycle between the pools of hexose-Ps and carbohydrates. This view is supported by several lines of evidence. Firstly, activities of enzymes capable of catalyzing these reactions were detected in roots, including a hexose-P phosphatase. Secondly, metabolic tracer experiments using ¹⁴C-glucose as precursor showed the formation of ¹⁴C-fructose and ¹⁴C-sucrose. We conclude that futile cycling of hexose-P could be partially responsible for the differences in energetic status in roots with high and low HK activity and possibly cause the observed alterations in growth in transgenic roots. The involvement of HK and futile cycles in the control of glucose-6P metabolism is discussed.

Analyzing the effect of decreasing cytosolic triosephosphate isomerase on Solanum tuberosum hairy root cells using a kinetic-metabolic model

A kinetic-metabolic model of Solanum tuberosum hairy roots is presented in the interest of understanding the effect on the plant cell metabolism of a 90% decrease in cytosolic triosephosphate isomerase (cTPI, EC 5.3.1.1) expression by antisense RNA. The model considers major metabolic pathways including glycolysis, pentose phosphate pathway, and TCA cycle, as well as anabolic reactions leading to lipids, nucleic acids, amino acids, and structural hexoses synthesis. Measurements were taken from shake flask cultures for six extracellular nutrients (sucrose, fructose, glucose, ammonia, nitrate, and inorganic phosphate) and 15 intracellular compounds including sugar phosphates (G6P, F6P, R5P, E4P) and organic acids (PYR, aKG, SUCC, FUM, MAL) and the six nutrients. From model simulations and experimental data it can be noted that plant cell metabolism redistributes metabolic fluxes to compensate for the cTPI decrease, leading to modifications in metabolites levels. Antisense roots showed increased exchanges between the pentose phosphate pathway and the glycolysis, an increased oxygen uptake and growth rate.