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

Modelling metabolic fluxes of tomato stems reveals that nitrogen shapes central metabolism for defence against Botrytis cinerea

Among plant pathogens, the necrotrophic fungus Botrytis cinerea is one of the most prevalent, leading to severe crop damage. Studies related to its colonization of different plant species have reported variable host metabolic responses to infection. In tomato, high N availability leads to decreased susceptibility. Metabolic flux analysis can be used as an integrated method to better understand which metabolic adaptations lead to effective host defence and resistance. Here, we investigated the metabolic response of tomato infected by B. cinerea in symptomless stem tissues proximal to the lesions for 7 d post-inoculation, using a reconstructed metabolic model constrained by a large and consistent metabolic dataset acquired under four different N supplies. An overall comparison of 48 flux solution vectors of Botrytis- and mock-inoculated plants showed that fluxes were higher in Botrytis-inoculated plants, and the difference increased with a reduction in available N, accompanying an unexpected increase in radial growth. Despite higher fluxes, such as those involved in cell wall synthesis and other pathways, fluxes related to glycolysis, the tricarboxylic acid cycle, and amino acid and protein synthesis were limited under very low N, which might explain the enhanced susceptibility. Limiting starch synthesis and enhancing fluxes towards redox and specialized metabolism also contributed to defence independent of N supply.

Hypoxia in tomato (Solanum lycopersicum) fruit during ripening: Biophysical elucidation by a 3D reaction-diffusion model

Respiration provides energy, substrates, and precursors to support physiological changes of the fruit during climacteric ripening. A key substrate of respiration is oxygen that needs to be supplied to the fruit in a passive way by gas transfer from the environment. Oxygen gradients may develop within the fruit due to its bulky size and the dense fruit tissues, potentially creating hypoxia that may have a role in the spatial development of ripening. This study presents a 3D reaction-diffusion model using tomato (Solanum lycopersicum) fruit as a test subject, combining the multiscale fruit geometry generated from magnetic resonance imaging and microcomputed tomography with varying respiration kinetics and contrasting boundary resistances obtained through independent experiments. The model predicted low oxygen levels in locular tissue under atmospheric conditions, and the oxygen level was markedly lower upon scar occlusion, aligning with microsensor profiling results. The locular region was in a hypoxic state, leading to its low aerobic respiration with high CO2 accumulation by fermentative respiration, while the rest of the tissues remained well oxygenated. The model further revealed that the hypoxia is caused by a combination of diffusion resistances and respiration rates of the tissue. Collectively, this study reveals the existence of the respiratory gas gradients and its biophysical causes during tomato fruit ripening, providing richer information for future studies on localized endogenous ethylene biosynthesis and fruit ripening.

Plant Life with and without Oxygen: A Metabolomics Approach

Oxygen deficiency is an environmental challenge which affects plant growth, the development and distribution in land and aquatic ecosystems, as well as crop yield losses worldwide. The capacity to exist in the conditions of deficiency or the complete lack of oxygen depends on a number of anatomic, developmental and molecular adaptations. The lack of molecular oxygen leads to an inhibition of aerobic respiration, which causes energy starvation and the acceleration of glycolysis passing into fermentations. We focus on systemic metabolic alterations revealed with the different approaches of metabolomics. Oxygen deprivation stimulates the accumulation of glucose, pyruvate and lactate, indicating the acceleration of the sugar metabolism, glycolysis and lactic fermentation, respectively. Among the Krebs-cycle metabolites, only the succinate level increases. Amino acids related to glycolysis, including the phosphoglycerate family (Ser and Gly), shikimate family (Phe, Tyr and Trp) and pyruvate family (Ala, Leu and Val), are greatly elevated. Members of the Asp family (Asn, Lys, Met, Thr and Ile), as well as the Glu family (Glu, Pro, Arg and GABA), accumulate as well. These metabolites are important members of the metabolic signature of oxygen deficiency in plants, linking glycolysis with an altered Krebs cycle and allowing alternative pathways of NAD(P)H reoxidation to avoid the excessive accumulation of toxic fermentation products (lactate, acetaldehyde, ethanol). Reoxygenation induces the downregulation of the levels of major anaerobically induced metabolites, including lactate, succinate and amino acids, especially members of the pyruvate family (Ala, Leu and Val), Tyr and Glu family (GABA and Glu) and Asp family (Asn, Met, Thr and Ile). The metabolic profiles during native and environmental hypoxia are rather similar, consisting in the accumulation of fermentation products, succinate, fumarate and amino acids, particularly Ala, Gly and GABA. The most intriguing fact is that metabolic alterations during oxidative stress are very much similar, with plant response to oxygen deprivation but not to reoxygenation.

Elucidating the impact of in vitro cultivation on Nicotiana tabacum metabolism through combined in silico modeling and multiomics analysis

The systematical characterization and understanding of the metabolic behaviors are the basis of the efficient plant metabolic engineering and synthetic biology. Genome-scale metabolic networks (GSMNs) are indispensable tools for the comprehensive characterization of overall metabolic profile. Here we first constructed a GSMN of tobacco, which is one of the most widely used plant chassis, and then combined the tobacco GSMN and multiomics analysis to systematically elucidate the impact of in-vitro cultivation on the tobacco metabolic network. In-vitro cultivation is a widely used technique for plant cultivation, not only in the field of basic research but also for the rapid propagation of valuable horticultural and pharmaceutical plants. However, the systemic effects of in-vitro cultivation on overall plant metabolism could easily be overlooked and are still poorly understood. We found that in-vitro tobacco showed slower growth, less biomass and suppressed photosynthesis than soil-grown tobacco. Many changes of metabolites and metabolic pathways between in-vitro and soil-grown tobacco plants were identified, which notably revealed a significant increase of the amino acids content under in-vitro condition. The in silico investigation showed that in-vitro tobacco downregulated photosynthesis and primary carbon metabolism, while significantly upregulated the GS/GOGAT cycle, as well as producing more energy and less NADH/NADPH to acclimate in-vitro growth demands. Altogether, the combination of experimental and in silico analyses offers an unprecedented view of tobacco metabolism, with valuable insights into the impact of in-vitro cultivation, enabling more efficient utilization of in-vitro techniques for plant propagation and metabolic engineering.

Comparative constraint-based modelling of fruit development across species highlights nitrogen metabolism in the growth-defence trade-off

Although primary metabolism is well conserved across species, it is useful to explore the specificity of its network to assess the extent to which some pathways may contribute to particular outcomes. Constraint-based metabolic modelling is an established framework for predicting metabolic fluxes and phenotypes and helps to explore how the plant metabolic network delivers specific outcomes from temporal series. After describing the main physiological traits during fruit development, we confirmed the correlations between fruit relative growth rate (RGR), protein content and time to maturity. Then a constraint-based method is applied to a panel of eight fruit species with a knowledge-based metabolic model of heterotrophic cells describing a generic metabolic network of primary metabolism. The metabolic fluxes are estimated by constraining the model using a large set of metabolites and compounds quantified throughout fruit development. Multivariate analyses showed a clear common pattern of flux distribution during fruit development with differences between fast- and slow-growing fruits. Only the latter fruits mobilise the tricarboxylic acid cycle in addition to glycolysis, leading to a higher rate of respiration. More surprisingly, to balance nitrogen, the model suggests, on the one hand, nitrogen uptake by nitrate reductase to support a high RGR at early stages of cucumber and, on the other hand, the accumulation of alkaloids during ripening of pepper and eggplant. Finally, building virtual fruits by combining 12 biomass compounds shows that the growth-defence trade-off is supported mainly by cell wall synthesis for fast-growing fruits and by total polyphenols accumulation for slow-growing fruits.

Enzyme-based kinetic modelling of ASC-GSH cycle during tomato fruit development reveals the importance of reducing power and ROS availability

The ascorbate-glutathione (ASC-GSH) cycle is at the heart of redox metabolism, linking the major redox buffers with central metabolism through the processing of reactive oxygen species (ROS) and pyridine nucleotide metabolism. Tomato fruit development is underpinned by changes in redox buffer contents and their associated enzyme capacities, but interactions between them remain unclear. Based on quantitative data obtained for the core redox metabolism, we built an enzyme-based kinetic model to calculate redox metabolite concentrations with their corresponding fluxes and control coefficients. Dynamic and associated regulations of the ASC-GSH cycle throughout the whole fruit development were analysed and pointed to a sequential metabolic control of redox fluxes by ASC synthesis, NAD(P)H and ROS availability depending on the developmental phase. Furthermore, we highlighted that monodehydroascorbate reductase and the availability of reducing power were found to be the main regulators of the redox state of ASC and GSH during fruit growth under optimal conditions. Our kinetic modelling approach indicated that tomato fruit development displayed growth phase-dependent redox metabolism linked with central metabolism via pyridine nucleotides and H2 O2 availability, while providing a new tool to the scientific community to investigate redox metabolism in fruits.

Genome-scale metabolic model led engineering of Nothapodytes nimmoniana plant cells for high camptothecin production

Camptothecin (CPT) is a vital monoterpene indole alkaloid used in anti-cancer therapeutics. It is primarily derived from Camptotheca acuminata and Nothapodytes nimmoniana plants that are indigenous to Southeast Asia. Plants have intricate metabolic networks and use them to produce secondary metabolites such as CPT, which is a prerequisite for rational metabolic engineering design to optimize their production. By reconstructing metabolic models, we can predict plant metabolic behavior, facilitating the selection of suitable approaches and saving time, cost, and energy, over traditional hit and trial experimental approaches. In this study, we reconstructed a genome-scale metabolic model for N. nimmoniana (NothaGEM iSM1809) and curated it using experimentally obtained biochemical data. We also used in silico tools to identify and rank suitable enzyme targets for overexpression and knockout to maximize camptothecin production. The predicted over-expression targets encompass enzymes involved in the camptothecin biosynthesis pathway, including strictosidine synthase and geraniol 10-hydroxylase, as well as targets related to plant metabolism, such as amino acid biosynthesis and the tricarboxylic acid cycle. The top-ranked knockout targets included reactions responsible for the formation of folates and serine, as well as the conversion of acetyl CoA and oxaloacetate to malate and citrate. One of the top-ranked overexpression targets, strictosidine synthase, was chosen to generate metabolically engineered cell lines of N. nimmoniana using Agrobacterium tumefaciens-mediated transformation. The transformed cell line showed a 5-fold increase in camptothecin production, with a yield of up to 5 µg g-1.

Toward mechanistic modeling and rational engineering of plant respiration

Plant respiration not only provides energy to support all cellular processes, including biomass production, but also plays a major role in the global carbon cycle. Therefore, modulation of plant respiration can be used to both increase the plant yield and mitigate the effects of global climate change. Mechanistic modeling of plant respiration at sufficient biochemical detail can provide key insights for rational engineering of this process. Yet, despite its importance, plant respiration has attracted considerably less modeling effort in comparison to photosynthesis. In this update review, we highlight the advances made in modeling of plant respiration, emphasizing the gradual but important change from phenomenological to models based on first principles. We also provide a detailed account of the existing resources that can contribute to resolving the challenges in modeling plant respiration. These resources point at tangible improvements in the representation of cellular processes that contribute to CO2 evolution and consideration of kinetic properties of underlying enzymes to facilitate mechanistic modeling. The update review emphasizes the need to couple biochemical models of respiration with models of acclimation and adaptation of respiration for their effective usage in guiding breeding efforts and improving terrestrial biosphere models tailored to future climate scenarios.

Enzyme activity profiling for physiological phenotyping within functional phenomics: plant growth and stress responses

High-throughput profiling of key enzyme activities of carbon, nitrogen, and antioxidant metabolism is emerging as a valuable approach to integrate cell physiological phenotyping into a holistic functional phenomics approach. However, the analyses of the large datasets generated by this method represent a bottleneck, often keeping researchers from exploiting the full potential of their studies. We address these limitations through the exemplary application of a set of data evaluation and visualization tools within a case study. This includes the introduction of multivariate statistical analyses that can easily be implemented in similar studies, allowing researchers to extract more valuable information to identify enzymatic biosignatures. Through a literature meta-analysis, we demonstrate how enzyme activity profiling has already provided functional information on the mechanisms regulating plant development and response mechanisms to abiotic stress and pathogen attack. The high robustness of the distinct enzymatic biosignatures observed during developmental processes and under stress conditions underpins the enormous potential of enzyme activity profiling for future applications in both basic and applied research. Enzyme activity profiling will complement molecular -omics approaches to contribute to the mechanistic understanding required to narrow the genotype-to-phenotype knowledge gap and to identify predictive biomarkers for plant breeding to develop climate-resilient crops.

From fruit growth to ripening in plantain: a careful balance between carbohydrate synthesis and breakdown

In this study, we aimed to investigate for the first time different fruit development stages in plantain banana in order gain insights into the order of appearance and dominance of specific enzymes and fluxes. We examined fruit development in two plantain banana cultivars during the period between 2-12 weeks after bunch emergence using high-throughput proteomics, quantification of major metabolites, and analyses of metabolic fluxes. Starch synthesis and breakdown are processes that take place simultaneously. During the first 10 weeks fruits accumulated up to 48% of their dry weight as starch, and glucose 6-phosphate and fructose were important precursors. We found a unique amyloplast transporter and hypothesize that it facilitates the import of fructose. We identified an invertase originating from the Musa balbisiana genome that would enable carbon flow back to growth and starch synthesis and maintain a high starch content even during ripening. Enzymes associated with the initiation of ripening were involved in ethylene and auxin metabolism, starch breakdown, pulp softening, and ascorbate biosynthesis. The initiation of ripening was cultivar specific, with faster initiation being particularly linked to the 1-aminocyclopropane-1-carboxylate oxidase and 4-alpha glucanotransferase disproportionating enzymes. Information of this kind is fundamental to determining the optimal time for picking the fruit in order to reduce post-harvest losses, and has potential applications for breeding to improve fruit quality.

A multi-organ metabolic model of tomato predicts plant responses to nutritional and genetic perturbations

Predicting and understanding plant responses to perturbations require integrating the interactions between nutritional sources, genes, cell metabolism, and physiology in the same model. This can be achieved using metabolic modeling calibrated by experimental data. In this study, we developed a multi-organ metabolic model of a tomato (Solanum lycopersicum) plant during vegetative growth, named Virtual Young TOmato Plant (VYTOP) that combines genome-scale metabolic models of leaf, stem and root and integrates experimental data acquired from metabolomics and high-throughput phenotyping of tomato plants. It is composed of 6,689 reactions and 6,326 metabolites. We validated VYTOP predictions on five independent use cases. The model correctly predicted that glutamine is the main organic nutrient of xylem sap. The model estimated quantitatively how stem photosynthetic contribution impacts exchanges between the different organs. The model was also able to predict how nitrogen limitation affects vegetative growth and the metabolic behavior of transgenic tomato lines with altered expression of core metabolic enzymes. The integration of different components, such as a metabolic model, physiological constraints, and experimental data, generates a powerful predictive tool to study plant behavior, which will be useful for several other applications, such as plant metabolic engineering or plant nutrition.

The effect of NH4+ on phosphoenolpyruvate carboxykinase gene expression, metabolic flux and citrate content of citrus juice sacs

Citrate is one of the most important metabolites determining the flavour of citrus fruit. It has been reported that nitrogen supply may have an impact on acid level of fruit. Here, the relationship between nitrogen metabolism and citrate catabolism was studied in pumelo juice sacs. Differences in metabolites, gene expression and flux distributions were analyzed in juice sacs incubated in medium with and without NH₄⁺. Compared with those incubated with NH₄⁺, juice sacs under nitrogen deficiency exhibited enhanced flux through phosphoenolpyruvate carboxykinase (PEPCK) and accelerated consumption of citrate, while the other two TCA cycle efflux points, through malic enzyme (ME) and glutamate dehydrogenase (GDH), were both repressed. Consistent with the estimated fluxes, the expression of PEPCK1 was upregulated under nitrogen deficiency, while that of GDH1, GDH2, NAD-ME1 and NADP-ME2 were all repressed. Thus, we propose that PEPCK1 contributes to citrate degradation under nitrogen limitation.

The NAC transcription factor FaRIF controls fruit ripening in strawberry

In contrast to climacteric fruits such as tomato, the knowledge on key regulatory genes controlling the ripening of strawberry, a nonclimacteric fruit, is still limited. NAC transcription factors (TFs) mediate different developmental processes in plants. Here, we identified and characterized Ripening Inducing Factor (FaRIF), a NAC TF that is highly expressed and induced in strawberry receptacles during ripening. Functional analyses based on stable transgenic lines aimed at silencing FaRIF by RNA interference, either from a constitutive promoter or the ripe receptacle-specific EXP2 promoter, as well as overexpression lines showed that FaRIF controls critical ripening-related processes such as fruit softening and pigment and sugar accumulation. Physiological, metabolome, and transcriptome analyses of receptacles of FaRIF-silenced and overexpression lines point to FaRIF as a key regulator of strawberry fruit ripening from early developmental stages, controlling abscisic acid biosynthesis and signaling, cell-wall degradation, and modification, the phenylpropanoid pathway, volatiles production, and the balance of the aerobic/anaerobic metabolism. FaRIF is therefore a target to be modified/edited to control the quality of strawberry fruits.

Modelling predicts tomatoes can be bigger and sweeter if biophysical factors and transmembrane transports are fine-tuned during fruit development

The trade-off between yield and quality, a major problem for the production of fleshy fruits, involves fruit expansive growth and sugar metabolism. Here we developed an integrative model by coupling a biophysical model of fleshy fruit growth processes, including water and carbon fluxes and organ expansion, with an enzyme-based kinetic model of sugar metabolism to better understand the interactions between these two processes. The integrative model was initially tested on tomato fruit, a model system for fleshy fruit. The integrative model closely simulated the biomass and major carbon metabolites of tomato fruit developing under optimal or stress conditions. The model also performed robustly when simulating the fruit size and sugar concentrations of different tomato genotypes including wild species. The validated model was used to explore ways of uncoupling the size-sweetness trade-off in fruit. Model-based virtual experiments suggested that larger sweeter tomatoes could be obtained by simultaneously manipulating certain biophysical factors and transmembrane transports. The integrative fleshy fruit model provides a promising tool to facilitate the targeted bioengineering and breeding of tomatoes and other fruits.

Exogenous DA-6 Improves the Low Night Temperature Tolerance of Tomato Through Regulating Cytokinin

Low night temperature (LNT) causes environmental stress and has a severe and negative impact on plant growth and productivity. Synthetic elicitors can regulate plant growth and induce defense mechanisms from this type of stress. Here, we evaluated the effect of the exogenous growth regulator diethyl aminoethyl hexanoate (DA-6) in tomato leaf response to LNT stress. Our results showed that exogenous DA-6 activates the expression of chlorophyll synthesis and photosystem-related genes, and results in higher photosynthetic activity and chlorophyll production. Furthermore, DA-6 can regulate the synthesis of endogenous cytokinin (CTK) and the expression of decomposition genes to stabilize chloroplast structure, reduce oxidative damage, and maintain the photochemical activity of tomato leaves under LNT stress. DA-6 maintains a high level of ABA content and induces the expression of CBF genes, indicating that DA-6 may participate in the cold response signaling pathway and induce the expression of downstream low temperature response genes and accumulation of compatible osmolytes. This study unravels a mode of action by which plant growth regulators can improve low temperature tolerance and provides important considerations for their application to alleviate the harmful effects of cold stress.

Biomass composition explains fruit relative growth rate and discriminates climacteric from non-climacteric species

Fleshy fruits are very varied, whether in terms of their composition, physiology, or rate and duration of growth. To understand the mechanisms that link metabolism to phenotypes, which would help the targeting of breeding strategies, we compared eight fleshy fruit species during development and ripening. Three herbaceous (eggplant, pepper, and cucumber), three tree (apple, peach, and clementine) and two vine (kiwifruit and grape) species were selected for their diversity. Fruit fresh weight and biomass composition, including the major soluble and insoluble components, were determined throughout fruit development and ripening. Best-fitting models of fruit weight were used to estimate relative growth rate (RGR), which was significantly correlated with several biomass components, especially protein content (R=84), stearate (R=0.72), palmitate (R=0.72), and lignocerate (R=0.68). The strong link between biomass composition and RGR was further evidenced by generalized linear models that predicted RGR with R-values exceeding 0.9. Comparison of the fruit also showed that climacteric fruit (apple, peach, kiwifruit) contained more non-cellulosic cell-wall glucose and fucose, and more starch, than non-climacteric fruit. The rate of starch net accumulation was also higher in climacteric fruit. These results suggest that the way biomass is constructed has a major influence on performance, especially growth rate.

Decreased sink/source ratio enhances hexose transport in the fruits of greenhouse tomatoes: integration of gene expression and biochemical analyses

To examine the physiological role of hexose transporters in determining the sink strength of individual fruits, the regulation of hexose transporters gene expression was studied when the sink/source ratio was artificially altered under the greenhouse condition; this was done in two cultivars of tomato, i.e. Grandella and Isabella. The sink/source ratio treatments included: saving one fruit per truss (1F), two fruits per truss (2F), three fruits per truss (3F) and no fruit pruning (control). The results showed that fruit thinning could increase starch, sucrose, and hexose contents in the fruits; it could also modulate the activity of the key enzymes and the expression of tomato hexose transporter genes (LeHTs). Based on the relative transcript levels, all examined LeHTs were unregulated at the end of cell division and the cell expansion stage of fruit development, but the strongest expression level observed at the onset of ripening was related to LeHT1 and LeHT2. Given the concomitancy of cell wall invertase (EC 3.2.1.26) activity and the LeHTs relative expression cell wall, invertase activity seemed to be involved in the expression level of LeHTs. The increased trends of the LeHTs expression with the decrease of the sink/source ratio confirmed the role of hexose transporters in determining the sink strength of the tomato fruits.

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.

Model-assisted comparison of sugar accumulation patterns in ten fleshy fruits highlights differences between herbaceous and woody species

BACKGROUND AND AIMS

Sugar concentration is a key determinant of fruit quality. Soluble sugars and starch concentrations in fruits vary greatly from one species to another. The aim of this study was to investigate similarities and differences in sugar accumulation strategies across ten contrasting fruit species using a modelling approach.

METHODS

We developed a coarse-grained model of primary metabolism based on the description of the main metabolic and hydraulic processes (synthesis of compounds other than sugar and starch, synthesis and hydrolysis of starch, and water dilution) involved in the accumulation of soluble sugars during fruit development.

KEY RESULTS

Statistical analyses based on metabolic rates separated the species into six groups according to the rate of synthesis of compounds other than sugar and starch. Herbaceous species (cucumber, tomato, eggplant, pepper and strawberry) were characterized by a higher synthesis rate than woody species (apple, nectarine, clementine, grape and kiwifruit). Inspection of the dynamics of the processes involved in sugar accumulation revealed that net sugar importation, metabolism and dilution processes were remarkably synchronous in most herbaceous plants, whereas in kiwifruit, apple and nectarine, processes related to starch metabolism were temporally separated from other processes. Strawberry, clementine and grape showed a distinct dynamic compared with all other species.

CONCLUSIONS

Overall, these results provide fresh insights into species-specific regulatory strategies and into the role of starch metabolism in the accumulation of soluble sugars in fleshy fruits. In particular, inter-specific differences in development period shape the co-ordination of metabolic processes and affect priorities for carbon allocation across species. The six metabolic groups identified by our analysis do not show a clear separation into climacteric and non-climacteric species, possibly suggesting that the metabolic processes related to sugar concentration are not greatly affected by ethylene-associated events.

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.

Multiscale computational models can guide experimentation and targeted measurements for crop improvement

Computational models of plants have identified gaps in our understanding of biological systems, and have revealed ways to optimize cellular processes or organ-level architecture to increase productivity. Thus, computational models are learning tools that help direct experimentation and measurements. Models are simplifications of complex systems, and often simulate specific processes at single scales (e.g. temporal, spatial, organizational, etc.). Consequently, single-scale models are unable to capture the critical cross-scale interactions that result in emergent properties of the system. In this perspective article, we contend that to accurately predict how a plant will respond in an untested environment, it is necessary to integrate mathematical models across biological scales. Computationally mimicking the flow of biological information from the genome to the phenome is an important step in discovering new experimental strategies to improve crops. A key challenge is to connect models across biological, temporal and computational (e.g. CPU versus GPU) scales, and then to visualize and interpret integrated model outputs. We address this challenge by describing the efforts of the international Crops in silico consortium.

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.

Unraveling dynamic metabolomes underlying different maturation stages of berries harvested from Panax ginseng

BACKGROUND

Ginseng berries (GBs) show temporal metabolic variations among different maturation stages, determining their organoleptic and functional properties.

METHODS

We analyzed metabolic variations concomitant to five different maturation stages of GBs including immature green (IG), mature green (MG), partially red (PR), fully red (FR), and overmature red (OR) using mass spectrometry (MS)-based metabolomic profiling and multivariate analyses.

RESULTS

The partial least squares discriminant analysis score plot based on gas chromatography-MS datasets highlighted metabolic disparity between preharvest (IG and MG) and harvest/postharvest (PR, FR, and OR) GB extracts along PLS1 (34.9%) with MG distinctly segregated across PLS2 (18.2%). Forty-three significantly discriminant primary metabolites were identified encompassing five developmental stages (variable importance in projection > 1.0, p < 0.05). Among them, most amino acids, organic acids, 5-C sugars, ethanolamines, purines, and palmitic acid were detected in preharvest GB extracts, whereas 6-C sugars, phenolic acid, and oleamide levels were distinctly higher during later maturation stages. Similarly, the partial least squares discriminant analysis based on liquid chromatography-MS datasets displayed preharvest and harvest/postharvest stages clustered across PLS1 (11.1 %); however, MG and PR were separated from IG, FR, and OR along PLS2 (5.6 %). Overall, 24 secondary metabolites were observed significantly discriminant (variable importance in projection > 1.0, p < 0.05), with most displaying higher relative abundance during preharvest stages excluding ginsenosides Rg1 and Re. Furthermore, we observed strong positive correlations between total flavonoid and phenolic metabolite contents in GB extracts and antioxidant activity.

CONCLUSION

Comprehending the dynamic metabolic variations associated with GB maturation stages rationalize their optimal harvest time per se the related agroeconomic traits.

Metabolomics to Exploit the Primed Immune System of Tomato Fruit

Tomato is a major crop suffering substantial yield losses from diseases, as fruit decay at a postharvest level can claim up to 50% of the total production worldwide. Due to the environmental risks of fungicides, there is an increasing interest in exploiting plant immunity through priming, which is an adaptive strategy that improves plant defensive capacity by stimulating induced mechanisms. Broad-spectrum defence priming can be triggered by the compound ß-aminobutyric acid (BABA). In tomato plants, BABA induces resistance against various fungal and bacterial pathogens and different methods of application result in durable protection. Here, we demonstrate that the treatment of tomato plants with BABA resulted in a durable induced resistance in tomato fruit against Botrytis cinerea, Phytophthora infestans and Pseudomonas syringae. Targeted and untargeted metabolomics were used to investigate the metabolic regulations that underpin the priming of tomato fruit against pathogenic microbes that present different infection strategies. Metabolomic analyses revealed major changes after BABA treatment and after inoculation. Remarkably, primed responses seemed specific to the type of infection, rather than showing a common fingerprint of BABA-induced priming. Furthermore, top-down modelling from the detected metabolic markers allowed for the accurate prediction of the measured resistance to fruit pathogens and demonstrated that soluble sugars are essential to predict resistance to fruit pathogens. Altogether, our results demonstrate that metabolomics is particularly insightful for a better understanding of defence priming in fruit. Further experiments are underway in order to identify key metabolites that mediate broad-spectrum BABA-induced priming in tomato fruit.

Organ-wide and ploidy-dependent regulation both contribute to cell-size determination: evidence from a computational model of tomato fruit

The development of a new organ is the result of coordinated events of cell division and expansion, in strong interaction with each other. This study presents a dynamic model of tomato fruit development that includes cell division, endoreduplication, and expansion processes. The model is used to investigate the potential interactions among these developmental processes within the context of the neo-cellular theory. In particular, different control schemes (either cell-autonomous or organ-controlled) are tested and compared to experimental data from two contrasting genotypes. The model shows that a pure cell-autonomous control fails to reproduce the observed cell-size distribution, and that an organ-wide control is required in order to get realistic cell-size variations. The model also supports the role of endoreduplication as an important determinant of the final cell size and suggests that a direct effect of endoreduplication on cell expansion is needed in order to obtain a significant correlation between size and ploidy, as observed in real data.

Regulation of Pyridine Nucleotide Metabolism During Tomato Fruit Development Through Transcript and Protein Profiling

Central metabolism is the engine of plant biomass, supplying fruit growth with building blocks, energy, and biochemical cofactors. Among metabolic cornerstones, nicotinamide adenine dinucleotide (NAD) is particularly pivotal for electron transfer through reduction-oxidation (redox) reactions, thus participating in a myriad of biochemical processes. Besides redox functions, NAD is now assumed to act as an integral regulator of signaling cascades involved in growth and environmental responses. However, the regulation of NAD metabolism and signaling during fruit development remains poorly studied and understood. Here, we benefit from RNAseq and proteomic data obtained from nine growth stages of tomato fruit (var. Moneymaker) to dissect mRNA and protein profiles that link to NAD metabolism, including de novo biosynthesis, recycling, utilization, and putative transport. As expected for a cofactor synthesis pathway, protein profiles failed to detect enzymes involved in NAD synthesis or utilization, except for nicotinic acid phosphoribosyltransferase (NaPT) and nicotinamidase (NIC), which suggested that most NAD metabolic enzymes were poorly represented quantitatively. Further investigations on transcript data unveiled differential expression patterns during fruit development. Interestingly, among specific NAD metabolism-related genes, early de novo biosynthetic genes were transcriptionally induced in very young fruits, in association with NAD kinase, while later stages of fruit growth rather showed an accumulation of transcripts involved in later stages of de novo synthesis and in NAD recycling, which agreed with augmented NAD(P) levels. In addition, a more global overview of 119 mRNA and 78 protein significant markers for NAD(P)-dependent enzymes revealed differential patterns during tomato growth that evidenced clear regulations of primary metabolism, notably with respect to mitochondrial functions. Overall, we propose that NAD metabolism and signaling are very dynamic in the developing tomato fruit and that its differential regulation is certainly critical to fuel central metabolism linking to growth mechanisms.

A Genome-Scale Metabolic Model of Soybean (Glycine max) Highlights Metabolic Fluxes in Seedlings

Until they become photoautotrophic juvenile plants, seedlings depend upon the reserves stored in seed tissues. These reserves must be mobilized and metabolized, and their breakdown products must be distributed to the different organs of the growing seedling. Here, we investigated the mobilization of soybean (Glycine max) seed reserves during seedling growth by initially constructing a genome-scale stoichiometric model for this important crop plant and then adapting the model to reflect metabolism in the cotyledons and hypocotyl/root axis (HRA). A detailed analysis of seedling growth and alterations in biomass composition was performed over 4 d of postgerminative growth and used to constrain the stoichiometric model. Flux balance analysis revealed marked differences in metabolism between the two organs, together with shifts in primary metabolism occurring during different periods postgermination. In particular, from 48 h onward, cotyledons were characterized by the oxidation of fatty acids to supply carbon for the tricarboxylic acid cycle as well as production of sucrose and glutamate for export to the HRA, while the HRA was characterized by the use of a range of imported amino acids in protein synthesis and catabolic processes. Overall, the use of flux balance modeling provided new insight into well-characterized metabolic processes in an important crop plant due to their analysis within the context of a metabolic network and reinforces the relevance of the application of this technique to the analysis of complex plant metabolic systems.

Fruit Salad in the Lab: Comparing Botanical Species to Help Deciphering Fruit Primary Metabolism

Although fleshy fruit species are economically important worldwide and crucial for human nutrition, the regulation of their fruit metabolism remains to be described finely. Fruit species differ in the origin of the tissue constituting the flesh, duration of fruit development, coordination of ripening changes (climacteric vs. non-climacteric type) and biochemical composition at ripeness is linked to sweetness and acidity. The main constituents of mature fruit result from different strategies of carbon transport and metabolism. Thus, the timing and nature of phloem loading and unloading can largely differ from one species to another. Furthermore, accumulations and transformations of major soluble sugars, organic acids, amino acids, starch and cell walls are very variable among fruit species. Comparing fruit species therefore appears as a valuable way to get a better understanding of metabolism. On the one hand, the comparison of results of studies about species of different botanical families allows pointing the drivers of sugar or organic acid accumulation but this kind of comparison is often hampered by heterogeneous analysis approaches applied in each study and incomplete dataset. On the other hand, cross-species studies remain rare but have brought new insights into key aspects of primary metabolism regulation. In addition, new tools for multi-species comparisons are currently emerging, including meta-analyses or re-use of shared metabolic or genomic data, and comparative metabolic flux or process-based modeling. All these approaches contribute to the identification of the metabolic factors that influence fruit growth and quality, in order to adjust their levels with breeding or cultural practices, with respect to improving fruit traits.

Extended Utilization of Constraint-Based Metabolic Model in a Long-Growing Crop

The constraint-based rMeCBM-KU50 model of cassava storage root growth was analyzed to evaluate its sensitivity, with respect to reaction flux distribution and storage root growth rate, to changes in model inputted data and constraints, including sucrose uptake rate-related data—photosynthetic rate, total leaf area, total photosynthetic rate, storage root dry weight, and biomass function-related data. These mainly varied within ±90% of the model default values, although exceptions were made for the carbohydrate (−90% to 8%) and starch (−90% to 9%) contents. The results indicated that the predicted storage root growth rate was highly affected by specific sucrose uptake rates through the total photosynthetic rate and storage root dry weight variations; whereas the carbon flux distribution, direction and partitioning inclusive, was more sensitive to the variation in biomass content, particularly the carbohydrate content. This study showed that the specific sucrose uptake rate based on the total photosynthetic rate, storage root dry weight, and carbohydrate content were critical to the constraint-based metabolic modeling and deepened our understanding of the input–output relationship—specifically regarding the rMeCBM-KU50 model—providing a valuable platform for the modeling of plant metabolic systems, especially long-growing crops.

Understanding carbon utilization routes between high and low starch-producing cultivars of cassava through Flux Balance Analysis

Analysis of metabolic flux was used for system level assessment of carbon partitioning in Kasetsart 50 (KU50) and Hanatee (HN) cassava cultivars to understand the metabolic routes for their distinct phenotypes. First, the constraint-based metabolic model of cassava storage roots, rMeCBM, was developed based on the carbon assimilation pathway of cassava. Following the subcellular compartmentalization and curation to ensure full network connectivity and reflect the complexity of eukaryotic cells, cultivar specific data on sucrose uptake and biomass synthesis were input, and rMeCBM model was used to simulate storage root growth in KU50 and HN. Results showed that rMeCBM-KU50 and rMeCBM-HN models well imitated the storage root growth. The flux-sum analysis revealed that both cultivars utilized different metabolic precursors to produce energy in plastid. More carbon flux was invested in the syntheses of carbohydrates and amino acids in KU50 than in HN. Also, KU50 utilized less flux for respiration and less energy to synthesize one gram of dry storage root. These results may disclose metabolic potential of KU50 underlying its higher storage root and starch yield over HN. Moreover, sensitivity analysis indicated the robustness of rMeCBM model. The knowledge gained might be useful for identifying engineering targets for cassava yield improvement.

Integration of Plant Metabolomics Data with Metabolic Networks: Progresses and Challenges

In the last decade, plant genome-scale modeling has developed rapidly and modeling efforts have advanced from representing metabolic behavior of plant heterotrophic cell suspensions to studying the complex interplay of cell types, tissues, and organs. A crucial driving force for such developments is the availability and integration of "omics" data (e.g., transcriptomics, proteomics, and metabolomics) which enable the reconstruction, extraction, and application of context-specific metabolic networks. In this chapter, we demonstrate a workflow to integrate gas chromatography coupled to mass spectrometry (GC-MS)-based metabolomics data of tomato fruit pericarp (flesh) tissue, at five developmental stages, with a genome-scale reconstruction of tomato metabolism. This method allows for the extraction of context-specific networks reflecting changing activities of metabolic pathways throughout fruit development and maturation.

Assessing the potential of quantitative 2D HSQC NMR in 13C enriched living organisms

In vivo Nuclear Magnetic Resonance (NMR) spectroscopy has great potential to interpret the biochemical response of organisms to their environment, thus making it an essential tool in understanding toxic mechanisms. However, magnetic susceptibility distortions lead to 1D NMR spectra of living organisms with lines that are too broad to identify and quantify metabolites, necessitating the use of 2D ¹H-¹³C Heteronuclear Single Quantum Coherence (HSQC) as a primary tool. While quantitative 2D HSQC is well established, to our knowledge it has yet to be applied in vivo. This study represents a simple pilot study that compares two of the most popular quantitative 2D HSQC approaches to determine if quantitative results can be directly obtained in vivo in isotopically enriched Daphnia magna (water flea). The results show the perfect-HSQC experiment performs very well in vivo, but the decoupling scheme used is critical for accurate quantitation. An improved decoupling approach derived using optimal control theory is presented here that improves the accuracy of metabolite concentrations that can be extracted in vivo down to micromolar concentrations. When combined with 2D Electronic Reference To access In vivo Concentrations (ERETIC) protocols, the protocol allows for the direct extraction of in vivo metabolite concentrations without the use of internal standards that can be detrimental to living organisms. Extracting absolute metabolic concentrations in vivo is an important first step and should, for example, be important for the parameterization as well as the validation of metabolic flux models in the future.

Get the Balance Right: ROS Homeostasis and Redox Signalling in Fruit

Plant central metabolism generates reactive oxygen species (ROS), which are key regulators that mediate signalling pathways involved in developmental processes and plant responses to environmental fluctuations. These highly reactive metabolites can lead to cellular damage when the reduction-oxidation (redox) homeostasis becomes unbalanced. Whilst decades of research have studied redox homeostasis in leaves, fundamental knowledge in fruit biology is still fragmentary. This is even more surprising when considering the natural profusion of fruit antioxidants that can process ROS and benefit human health. In this review, we explore redox biology in fruit and provide an overview of fruit antioxidants with recent examples. We further examine the central role of the redox hub in signalling during development and stress, with particular emphasis on ascorbate, also referred to as vitamin C. Progress in understanding the molecular mechanisms involved in the redox regulations that are linked to central metabolism and stress pathways will help to define novel strategies for optimising fruit nutritional quality, fruit production and storage.

Putting primary metabolism into perspective to obtain better fruits

Background

One of the key goals of fruit biology is to understand the factors that influence fruit growth and quality, ultimately with a view to manipulating them for improvement of fruit traits.

Scope

Primary metabolism, which is not only essential for growth but is also a major component of fruit quality, is an obvious target for improvement. However, metabolism is a moving target that undergoes marked changes throughout fruit growth and ripening.

Conclusions

Agricultural practice and breeding have successfully improved fruit metabolic traits, but both face the complexity of the interplay between development, metabolism and the environment. Thus, more fundamental knowledge is needed to identify further strategies for the manipulation of fruit metabolism. Nearly two decades of post-genomics approaches involving transcriptomics, proteomics and/or metabolomics have generated a lot of information about the behaviour of fruit metabolic networks. Today, the emergence of modelling tools is providing the opportunity to turn this information into a mechanistic understanding of fruits, and ultimately to design better fruits. Since high-quality data are a key requirement in modelling, a range of must-have parameters and variables is proposed.

Next-generation strategies for understanding and influencing source-sink relations in crop plants

Whether plants are source or sink limited, that is, whether carbon assimilation or rather assimilate usage is ultimately responsible for crop yield, has been the subject of intense debate over several decades. Here we provide a short review of this debate before focusing on the use of transgenic intervention as a means to influence yield by modifying either source or sink function (or both). Given the relatively low success rates of strategies targeting single genes we highlight the success of multi-target transformations. The emergence of whole plant models and the potential impact that these will have in aiding yield improvement strategies are then discussed. We end by providing our perspective for next generation strategies for improving crop plants by means of manipulating their source-sink relations.

Model-based metabolism design: constraints for kinetic and stoichiometric models

The implementation of model-based designs in metabolic engineering and synthetic biology may fail. One of the reasons for this failure is that only a part of the real-world complexity is included in models. Still, some knowledge can be simplified and taken into account in the form of optimization constraints to improve the feasibility of model-based designs of metabolic pathways in organisms. Some constraints (mass balance, energy balance, and steady-state assumption) serve as a basis for many modelling approaches. There are others (total enzyme activity constraint and homeostatic constraint) proposed decades ago, but which are frequently ignored in design development. Several new approaches of cellular analysis have made possible the application of constraints like cell size, surface, and resource balance. Constraints for kinetic and stoichiometric models are grouped according to their applicability preconditions in (1) general constraints, (2) organism-level constraints, and (3) experiment-level constraints. General constraints are universal and are applicable for any system. Organism-level constraints are applicable for biological systems and usually are organism-specific, but these constraints can be applied without information about experimental conditions. To apply experimental-level constraints, peculiarities of the organism and the experimental set-up have to be taken into account to calculate the values of constraints. The limitations of applicability of particular constraints for kinetic and stoichiometric models are addressed.

Constraint-Based Modeling Highlights Cell Energy, Redox Status and α-Ketoglutarate Availability as Metabolic Drivers for Anthocyanin Accumulation in Grape Cells Under Nitrogen Limitation

Anthocyanin biosynthesis is regulated by environmental factors (such as light, temperature, and water availability) and nutrient status (such as carbon, nitrogen, and phosphate nutrition). Previous reports show that low nitrogen availability strongly enhances anthocyanin accumulation in non carbon-limited plant organs or cell suspensions. It has been hypothesized that high carbon-to-nitrogen ratio would lead to an energy excess in plant cells, and that an increase in flavonoid pathway metabolic fluxes would act as an "energy escape valve," helping plant cells to cope with energy and carbon excess. However, this hypothesis has never been tested directly. To this end, we used the grapevine Vitis vinifera L. cultivar Gamay Teinturier (syn. Gamay Freaux or Freaux Tintorier, VIVC #4382) cell suspension line as a model system to study the regulation of anthocyanin accumulation in response to nitrogen supply. The cells were sub-cultured in the presence of either control (25 mM) or low (5 mM) nitrate concentration. Targeted metabolomics and enzyme activity determinations were used to parametrize a constraint-based model describing both the central carbon and nitrogen metabolisms and the flavonoid (phenylpropanoid) pathway connected by the energy (ATP) and reducing power equivalents (NADPH and NADH) cofactors. The flux analysis (2 flux maps generated, for control and low nitrogen in culture medium) clearly showed that in low nitrogen-fed cells all the metabolic fluxes of central metabolism were decreased, whereas fluxes that consume energy and reducing power, were either increased (upper part of glycolysis, shikimate, and flavonoid pathway) or maintained (pentose phosphate pathway). Also, fluxes of flavanone 3β-hydroxylase, flavonol synthase, and anthocyanidin synthase were strongly increased, advocating for a regulation of the flavonoid pathway by alpha-ketoglutarate levels. These results strongly support the hypothesis of anthocyanin biosynthesis acting as an energy escape valve in plant cells, and they open new possibilities to manipulate flavonoid production in plant cells. They do not, however, support a role of anthocyanins as an effective mechanism for coping with carbon excess in high carbon to nitrogen ratio situations in grape cells. Instead, constraint-based modeling output and biomass analysis indicate that carbon excess is dealt with by vacuolar storage of soluble sugars.

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.

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.

Respiration climacteric in tomato fruits elucidated by constraint-based modelling

Tomato is a model organism to study the development of fleshy fruit including ripening initiation. Unfortunately, few studies deal with the brief phase of accelerated ripening associated with the respiration climacteric because of practical problems involved in measuring fruit respiration. Because constraint-based modelling allows predicting accurate metabolic fluxes, we investigated the respiration and energy dissipation of fruit pericarp at the breaker stage using a detailed stoichiometric model of the respiratory pathway, including alternative oxidase and uncoupling proteins. Assuming steady-state, a metabolic dataset was transformed into constraints to solve the model on a daily basis throughout tomato fruit development. We detected a peak of CO₂ released and an excess of energy dissipated at 40 d post anthesis (DPA) just before the onset of ripening coinciding with the respiration climacteric. We demonstrated the unbalanced carbon allocation with the sharp slowdown of accumulation (for syntheses and storage) and the beginning of the degradation of starch and cell wall polysaccharides. Experiments with fruits harvested from plants cultivated under stress conditions confirmed the concept. We conclude that modelling with an accurate metabolic dataset is an efficient tool to bypass the difficulty of measuring fruit respiration and to elucidate the underlying mechanisms of ripening.

Rapid identification of causal mutations in tomato EMS populations via mapping-by-sequencing

The tomato is the model species of choice for fleshy fruit development and for the Solanaceae family. Ethyl methanesulfonate (EMS) mutants of tomato have already proven their utility for analysis of gene function in plants, leading to improved breeding stocks and superior tomato varieties. However, until recently, the identification of causal mutations that underlie particular phenotypes has been a very lengthy task that many laboratories could not afford because of spatial and technical limitations. Here, we describe a simple protocol for identifying causal mutations in tomato using a mapping-by-sequencing strategy. Plants displaying phenotypes of interest are first isolated by screening an EMS mutant collection generated in the miniature cultivar Micro-Tom. A recombinant F₂ population is then produced by crossing the mutant with a wild-type (WT; non-mutagenized) genotype, and F₂ segregants displaying the same phenotype are subsequently pooled. Finally, whole-genome sequencing and analysis of allele distributions in the pools allow for the identification of the causal mutation. The whole process, from the isolation of the tomato mutant to the identification of the causal mutation, takes 6-12 months. This strategy overcomes many previous limitations, is simple to use and can be applied in most laboratories with limited facilities for plant culture and genotyping.

Fruit metabolite networks in engineered and non-engineered tomato genotypes reveal fluidity in a hormone and agroecosystem specific manner

INTRODUCTION

Metabolomics provides a view of endogenous metabolic patterns not only during plant growth, development and senescence but also in response to genetic events, environment and disease. The effects of the field environment on plant hormone-specific metabolite profiles are largely unknown. Few studies have analyzed useful phenotypes generated by introducing single or multiple gene events alongside the non-engineered wild type control at field scale to determine the robustness of the genetic trait and its modulation in the metabolome as a function of specific agroecosystem environments.

OBJECTIVES

We evaluated the influence of genetic background (high polyamine lines; low methyl jasmonate line; low ethylene line; and isogenic genotypes carrying double transgenic events) and environments (hairy vetch, rye, plastic black mulch and bare soil mulching systems) on the metabolomic profile of isogenic reverse genetic mutations and selected mulch based cropping systems in tomato fruit. Net photosynthesis and fruit yield were also determined.

METHODS

NMR spectroscopy was used for quantifying metabolites that are central to primary metabolism. We analyzed both the first moment (means) of metabolic response to genotypes and agroecosystems by traditional univariate/multivariate methods, and the second moment (covariances) of responses by creating networks that depicted changes in correlations of paired metabolites. This particular approach is novel and was necessary because our experimental material yielded highly variable metabolic responses that could not be easily understood using the traditional analytical approaches for first moment statistics.

RESULTS

High endogenous spermidine and spermine content exhibited strong effects on amino acids, Krebs cycle intermediates and energy molecules (ADP + ATP) in ripening fruits of plants grown under different agroecosystem environments. The metabolic response to high polyamine genotypes was similar to the response to hairy vetch cover crop mulch; supported by the pattern of changes in correlation between metabolites. Changes in primary metabolites of genotypes mutated for the deficiency of ethylene or methyl jasmonate were unique under all growth conditions and opposite of high polyamine genotype results. The high polyamine trait was found to dominate the low ethylene and low jasmonate mutations under field conditions. For several metabolites low ethylene and low methyl jasmonate genotypes had an inverse relationship. Collectively, these results affirm that interactions between metabolite pathways and growth environments are affected by genotype, and influence the metabolite quality of a crop.

CONCLUSION

This study portrays how metabolite relationships change, both in mean and in correlation, under different genotypic and environmental conditions. Although these networks are surprisingly dynamic, we also find examples of selectively conserved associations.

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.

Modeling Rice Metabolism: From Elucidating Environmental Effects on Cellular Phenotype to Guiding Crop Improvement

Crop productivity is severely limited by various biotic and abiotic stresses. Thus, it is highly needed to understand the underlying mechanisms of environmental stress response and tolerance in plants, which could be addressed by systems biology approach. To this end, high-throughput omics profiling and in silico modeling can be considered to explore the environmental effects on phenotypic states and metabolic behaviors of rice crops at the systems level. Especially, the advent of constraint-based metabolic reconstruction and analysis paves a way to characterize the plant cellular physiology under various stresses by combining the mathematical network models with multi-omics data. Rice metabolic networks have been reconstructed since 2013 and currently six such networks are available, where five are at genome-scale. Since their publication, these models have been utilized to systematically elucidate the rice abiotic stress responses and identify agronomic traits for crop improvement. In this review, we summarize the current status of the existing rice metabolic networks and models with their applications. Furthermore, we also highlight future directions of rice modeling studies, particularly stressing how these models can be used to contextualize the affluent multi-omics data that are readily available in the public domain. Overall, we envisage a number of studies in the future, exploiting the available metabolic models to enhance the yield and quality of rice and other food crops.

A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism

Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome-scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome-scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses.

WITHDRAWN: Physiological and biochemical characterization of tomato transgenic lines overexpressing Arabidopsis thaliana cold responsive-element binding factor 3 (AtCBF3) gene under chilling stress

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Mathematical models of plant metabolism

Among various modeling approaches in plant metabolic research, applications of Constraint-Based modeling are fast increasing in recent years, apparently driven by current advances in genomics and genome sequencing. Constraint-Based modeling, the functional analysis of metabolic networks at the whole cell or genome scale, is more difficult to apply to plants than to microbes. Here we discuss recent developments in Constraint-Based modeling in plants with focus on issues of model reconstruction and flux prediction. Another topic is the emerging application of integration of Constraint-Based modeling with omics data to increase predictive power. Furthermore, advances in experimental measurements of cellular fluxes by (13)C-Metabolic Flux Analysis are highlighted, including instationary (13)C-MFA used to probe autotrophic metabolism in photosynthetic tissue in the light.

Inference and Prediction of Metabolic Network Fluxes

In this Update, we cover the basic principles of the estimation and prediction of the rates of the many interconnected biochemical reactions that constitute plant metabolic networks. This includes metabolic flux analysis approaches that utilize the rates or patterns of redistribution of stable isotopes of carbon and other atoms to estimate fluxes, as well as constraints-based optimization approaches such as flux balance analysis. Some of the major insights that have been gained from analysis of fluxes in plants are discussed, including the functioning of metabolic pathways in a network context, the robustness of the metabolic phenotype, the importance of cell maintenance costs, and the mechanisms that enable energy and redox balancing at steady state. We also discuss methodologies to exploit 'omic data sets for the construction of tissue-specific metabolic network models and to constrain the range of permissible fluxes in such models. Finally, we consider the future directions and challenges faced by the field of metabolic network flux phenotyping.