Metabolic networks: how to identify key components in the regulation of metabolism and growth

Decoding the Tissue-Specific Profiles of Bioactive Compounds in Helvella leucopus Using Combined Transcriptomic and Metabolomic Approaches

Helvella leucopus, an endangered wild edible fungus, is renowned for its distinct health benefits and nutritional profile, with notable differences in the bioactive and nutritional properties between its cap and stipe. To investigate the molecular basis of these tissue-specific variations, we conducted integrative transcriptomic and metabolomic analyses. Metabolomic profiling showed that the cap is particularly rich in bioactive compounds, including sterols and alkaloids, while the stipe is abundant in essential nutrients, such as glycerophospholipids and amino acids. Transcriptomic analysis revealed a higher expression of genes involved in sterol biosynthesis (ERG1, ERG3, ERG6) and energy metabolism (PGK1, ENO1, PYK1) in the cap, suggesting a more active metabolic profile in this tissue. Pathway enrichment analysis highlighted tissue-specific metabolic pathways, including riboflavin metabolism, pantothenate and CoA biosynthesis, and terpenoid backbone biosynthesis, as key contributors to the unique functional properties of the cap and stipe. A detailed biosynthetic pathway network further illustrated how these pathways contribute to the production of crucial bioactive and nutritional compounds, such as sterols, alkaloids, linoleic acid derivatives, glycerophospholipids, and amino acids, in each tissue. These findings provide significant insights into the molecular mechanisms behind the health-promoting properties of the cap and the nutritional richness of the stipe, offering a theoretical foundation for utilizing H. leucopus in functional food development and broadening our understanding of bioactive and nutritional distribution in edible fungi.

Divergence in the effects of sugar feedback regulation on the major gene regulatory network and metabolism of photosynthesis in leaves between the two founding Saccharum species

Sugarcane is a crop that accumulates sucrose with high photosynthesis efficiency. Therefore, the feedback regulation of sucrose on photosynthesis is crucial for improving sugarcane yield. Saccharum spontaneum and Saccharum officinarum are the two founding Saccharum species for modern sugarcane hybrids. S. spontaneum exhibits a higher net photosynthetic rate but lower sucrose content than S. officinarum. However, the mechanism underlying the negative feedback regulation of photosynthesis by sucrose remains poorly understood. This study investigates the effects of exogenous sucrose treatment on S. spontaneum and S. officinarum. Exogenous sucrose treatment increases sucrose content in the leaf base but inhibits photosynthetic efficiency and the expression of photosynthesis-related pathway genes (including RBCS and PEPC) in both species. However, gene expression patterns differed significantly, with few differentially expressed genes (DEGs) shared between the two species, indicating a differential response to exogenous sucrose. The expression networks of key genes involved in sugar metabolism, sugar transport, and PEPC and RBCS showed divergence between two species. Additionally, DEGs involved in the pentose phosphate pathway and the metabolism of alanine, aspartate, and glutamate metabolism were uniquely enriched in S. spontaneum, potentially contributing to the differential changes in sucrose content in the tip between the two species. We propose a model of the mechanisms underlying the negative feedback regulation of photosynthesis by sucrose in the leaves of S. spontaneum and S. officinarum. Our findings enhance the understanding of sucrose feedback regulation on photosynthesis and provide insights into the divergent molecular mechanisms of sugar accumulation in Saccharum.

Understanding metabolic diversification in plants: branchpoints in the evolution of specialized metabolism

Plants are chemical engineers par excellence. Collectively they make a vast array of structurally diverse specialized metabolites. The raw materials for building new pathways (genes encoding biosynthetic enzymes) are commonly recruited directly or indirectly from primary metabolism. Little is known about how new metabolic pathways and networks evolve in plants, or what key nodes contribute to branches that lead to the biosynthesis of diverse chemicals. Here we review the molecular mechanisms underlying the generation of biosynthetic branchpoints. We also consider examples in which new metabolites are formed through the joining of precursor molecules arising from different biosynthetic routes, a scenario that greatly increases both the diversity and complexity of specialized metabolism. Given the emerging importance of metabolic gene clustering in helping to identify new enzymes and pathways, we further cover the significance of biosynthetic gene clusters in relation to metabolic networks and dedicated biosynthetic pathways. In conclusion, an improved understanding of the branchpoints between metabolic pathways will be key in order to be able to predict and illustrate the complex structure of metabolic networks and to better understand the plasticity of plant metabolism. This article is part of the theme issue 'The evolution of plant metabolism'.

6-Phosphogluconate dehydrogenase 2 bridges the OPP and shikimate pathways to enhance aromatic amino acid production in plants

The oxidative pentose phosphate (OPP) pathway provides metabolic intermediates for the shikimate pathway and directs carbon flow to the biosynthesis of aromatic amino acids (AAAs), which serve as basic protein building blocks and precursors of numerous metabolites essential for plant growth. However, genetic evidence linking the two pathways is largely unclear. In this study, we identified 6-phosphogluconate dehydrogenase 2 (PGD2), the rate-limiting enzyme of the cytosolic OPP pathway, through suppressor screening of arogenate dehydrogenase 2 (adh2) in Arabidopsis. Our data indicated that a single amino acid substitution at position 63 (glutamic acid to lysine) of PGD2 enhanced its enzyme activity by facilitating the dissociation of products from the active site of PGD2, thus increasing the accumulation of AAAs and partially restoring the defective phenotype of adh2. Phylogenetic analysis indicated that the point mutation occurred in a well-conserved amino acid residue. Plants with different amino acids at this conserved site of PGDs confer diverse catalytic activities, thus exhibiting distinct AAAs producing capability. These findings uncover the genetic link between the OPP pathway and AAAs biosynthesis through PGD2. The gain-of-function point mutation of PGD2 identified here could be considered as a potential engineering target to alter the metabolic flux for the production of AAAs and downstream compounds.

Multi-omics analysis uncovers the transcriptional regulatory mechanism of magnesium Ions in the synthesis of active ingredients in Sophora tonkinensis

Magnesium (Mg) plays a pivotal role as an essential component of plant chlorophyll and functions as a critical coenzyme. However, research exploring the regulatory mechanisms of magnesium ions on the synthesis of secondary metabolites is still in its early stages. Sophora tonkinensis is a widely utilized medicinal plant in China, recognized for its diverse secondary metabolites with active properties. This study investigates variations in these ingredients in tissue-cultured seedlings under varying magnesium concentrations. Simultaneously, an omics data analysis was conducted on tissue-cultured seedlings subjected to treatments with magnesium and low magnesium. These comprehensive omics analyses aimed to elucidate the mechanisms through which magnesium influences active components, growth, and development. Magnesium exerts a pervasive influence on various metabolic pathways, forming an intricate network. Research findings indicate that magnesium impacts diverse metabolic processes, including the absorption of potassium and calcium, as well as photosynthetic activity. Consequently, these influences lead to discernible changes in the levels of pharmacologically active compounds and the growth and developmental status.This study is the first to employ a multi-omics data analysis in S. tonkinensis. This methodology allows us to uncover the overarching impact of metabolic networks on the levels of various active ingredients and specific phenotypes.

Navigating the microalgal maze: a comprehensive review of recent advances and future perspectives in biological networks

MAIN CONCLUSION

PPI analysis deepens our knowledge in critical processes like carbon fixation and nutrient sensing. Moreover, signaling networks, including pathways like MAPK/ERK and TOR, provide valuable information in how microalgae respond to environmental changes and stress. Additionally, species-species interaction networks for microalgae provide a comprehensive understanding of how different species interact within their environments. This review examines recent advancements in the study of biological networks within microalgae, with a focus on the intricate interactions that define these organisms. It emphasizes how network biology, an interdisciplinary field, offers valuable insights into microalgae functions through various methodologies. Crucial approaches, such as protein-protein interaction (PPI) mapping utilizing yeast two-hybrid screening and mass spectrometry, are essential for comprehending cellular processes and optimizing functions, such as photosynthesis and fatty acid biosynthesis. The application of advanced computational methods and information mining has significantly improved PPI analysis, revealing networks involved in critical processes like carbon fixation and nutrient sensing. The review also encompasses transcriptional networks, which play a role in gene regulation and stress responses, as well as metabolic networks represented by genome-scale metabolic models (GEMs), which aid in strain optimization and the prediction of metabolic outcomes. Furthermore, signaling networks, including pathways like MAPK/ERK and TOR, are crucial for understanding how microalgae respond to environmental changes and stress. Additionally, species-species interaction networks for microalgae provide a comprehensive understanding of how different species interact within their environments. The integration of these network biology approaches has deepened our understanding of microalgal interactions, paving the way for more efficient cultivation and new industrial applications.

The marriage between stable isotope ecology and plant metabolomics - new perspectives for metabolic flux analysis and the interpretation of ecological archives

Even though they share many thematical overlaps, plant metabolomics and stable isotope ecology have been rather separate fields mainly due to different mass spectrometry demands. New high-resolution bioanalytical mass spectrometers are now not only offering high-throughput metabolite identification but are also suitable for compound- and intramolecular position-specific isotope analysis in the natural isotope abundance range. In plant metabolomics, label-free metabolic pathway and metabolic flux analysis might become possible when applying this new technology. This is because changes in the commitment of substrates to particular metabolic pathways and the activation or deactivation of others alter enzyme-specific isotope effects. This leads to differences in intramolecular and compound-specific isotope compositions. In plant isotope ecology, position-specific isotope analysis in plant archives informed by metabolic pathway analysis could be used to reconstruct and separate environmental impacts on complex metabolic processes. A technology-driven linkage between the two disciplines could allow us to extract information on environment-metabolism interaction from plant archives such as tree rings but also within ecosystems. This would contribute to a holistic understanding of how plants react to environmental drivers, thus also providing helpful information on the trajectories of the vegetation under the conditions to come.

Metabolite Profiling of Hydroponic Lettuce Roots Affected by Nutrient Solution Flow: Insights from Comprehensive Analysis Using Widely Targeted Metabolomics and MALDI Mass Spectrometry Imaging Approaches

Root morphology, an important determinant of nutrient absorption and plant growth, can adapt to various growth environments to promote survival. Solution flow under hydroponic conditions provides a mechanical stimulus, triggering adaptive biological responses, including altered root morphology and enhanced root growth and surface area to facilitate nutrient absorption. To clarify these mechanisms, we applied untargeted metabolomics technology, detecting 1737 substances in lettuce root samples under different flow rates, including 17 common differential metabolites. The abscisic acid metabolic pathway product dihydrophaseic acid and the amino and nucleotide sugar metabolism factor N-acetyl-d-mannosamine suggest that nutrient solution flow rate affects root organic acid and sugar metabolism to regulate root growth. Spatial metabolomics analysis of the most stressed root bases revealed significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways: "biosynthesis of cofactors" and "amino sugar and nucleotide sugar metabolism". Colocalization analysis of pathway metabolites revealed a flow-dependent spatial distribution, with higher flavin mononucleotide, adenosine-5'-diphosphate, hydrogenobyrinic acid, and D-glucosamine 6-phosphate under flow conditions, the latter two showing downstream-side enrichment. In contrast, phosphoenolpyruvate, 1-phospho-alpha-D-galacturonic acid, 3-hydroxyanthranilic acid, and N-acetyl-D-galactosamine were more abundant under no-flow conditions, with the latter two concentrated on the upstream side. As metabolite distribution is associated with function, observing their spatial distribution in the basal roots will provide a more comprehensive understanding of how metabolites influence plant morphology and response to environmental changes than what is currently available in the literature.

NtGCN2 confers cadmium tolerance in Nicotiana tabacum L. by regulating cadmium uptake, efflux, and subcellular distribution

General control non-derepressible-2 (GCN2) is widely expressed in eukaryotes and responds to biotic and abiotic stressors. However, the precise function and mechanism of action of GCN2 in response to cadmium (Cd) stress in Nicotiana tabacum L. (tobacco) remains unclear. We investigated the role of NtGCN2 in Cd tolerance and explored the mechanism by which NtGCN2 responds to Cd stress in tobacco by exposing NtGCN2 transgenic tobacco lines to different concentrations of CdCl2. NtGCN2 was activated under 50 μmol·L-1 CdCl2 stress and enhanced the Cd tolerance and photosynthetic capacities of tobacco by increasing chlorophyll content and antioxidant capacity by upregulating NtSOD, NtPOD, and NtCAT expression and corresponding enzyme activities and decreasing malondialdehyde and O2·- contents. NtGCN2 enhanced the osmoregulatory capacity of tobacco by elevating proline (Pro) and soluble sugar contents and maintaining low levels of relative conductivity. Finally, NtGCN2 enhanced Cd tolerance in tobacco by reducing Cd uptake and translocation, promoting Cd efflux, and regulating Cd subcellular distribution. In conclusion, NtGCN2 improves the tolerance of tobacco to Cd through a series of mechanisms, namely, increasing antioxidant, photosynthetic, and osmoregulation capacities and regulating Cd uptake, translocation, efflux, and subcellular distribution. This study provides a scientific basis for further exploration of the role of NtGCN2 in plant responses to Cd stress and enhancement of the Cd stress signaling network in tobacco.

Models and molecular mechanisms for trade-offs in the context of metabolism

Accumulating evidence for trade-offs involving metabolic traits has demonstrated their importance in the evolution of organisms. Metabolic models with different levels of complexity have already been considered when investigating mechanisms that explain various metabolic trade-offs. Here we provide a systematic review of modelling approaches that have been used to study and explain trade-offs between: (i) the kinetic properties of individual enzymes, (ii) rates of metabolic reactions, (iii) the rate and yield of metabolic pathways and networks, (iv) different metabolic objectives in single organisms and in metabolic communities, and (v) metabolic concentrations. In providing insights into the mechanisms underlying these five types of metabolic trade-offs obtained from constraint-based metabolic modelling, we emphasize the relationship of metabolic trade-offs to the classical black box Y-model that provides a conceptual explanation for resource acquisition-allocation trade-offs. In addition, we identify several pressing concerns and offer a perspective for future research in the identification and manipulation of metabolic trade-offs by relying on the toolbox provided by constraint-based metabolic modelling for single organisms and microbial communities.

Nitrogen fixation and phytohormone stimulation of sugarcane plant through plant growth promoting diazotrophic Pseudomonas

Diazotrophic microorganisms are free-living groups of organisms that can convert atmospheric nitrogen (N) into bioavailable nitrogen for plants, which increases crop development and production. The purpose of the current study was to ascertain how diazotrophic plant growth promoting (PGP) Pseudomonas strains (P. koreensis CY4 and P. entomophila CN11) enhanced nitrogen fixation, defense activity, and PGP attributes of sugarcane varieties; GT11 and G×B9. A 15N isotope-dilution study was conducted to confirm the sugarcane strains' capacity to fix nitrogen, and the results indicated that between 21 to 35% of plant, nitrogen is fixed biologically by selected rhizobacteria. In comparison to the control, after 30, 60, and 90 days, both CY4 and CN11 strains significantly increased defense-related enzymes (catalase, peroxidase, phenylalanine ammonia-lyase, superoxide dismutase, glucanase, and chitinase) and phytohormones (abscisic acid, ABA, cytokinin, etc.) in GT11 and GXB. Additionally, the expression of SuCHI, SuGLU, SuCAT, SuSOD, and SuPAL genes was found to be elevated in Pseudomonas strains inoculated plants using real-time quantitative polymerase chain reaction (RT-qPCR). Both bacterial strains increased all physiological parameters and chlorophyll content in sugarcane plants more than their control. The effects of P. koreensis CY4 and P. entomophila CN11 strains on sugarcane growth promotion and nitrogen fixation under greenhouse conditions are described here for the first time systematically. The results of confirmation studies demonstrated that P. koreensis CY4 and P. entomophila are PGP bacterial strains with the potential to be employed as a biofertilizer for sugarcane growth, nitrogen nutrient absorption, and reduced application of chemical nitrogenous fertilizers in agricultural fields.  .

Decoding the metabolomic responses of Caragana tibetica to livestock grazing in fragile ecosystems

The population of Caragana tibetica, situated on the edge of the typical grassland-to-desert transition in the Mu Us Sandy Land, plays a vital ecological role in maintaining stability within the regional fragile ecosystem. Despite the consistent growth of C. tibetica following animal grazing, the biological mechanisms underlying its compensatory growth in response to livestock consumption remain unclear. Analyzing 48 metabolomic profiles from C. tibetica, our study reveals that the grazing process induces significant changes in the metabolic pathways of C. tibetica branches. Differential metabolites show correlations with soluble protein content, catalase, peroxidase, superoxide dismutase, malondialdehyde, and proline levels. Moreover, machine learning models built on these differential metabolites accurately predict the intensity of C. tibetica grazing (with an accuracy of 83.3%). The content of various metabolites, indicative of plant stress responses, including Enterolactone, Narceine, and Folcepri, exhibits significant variations in response to varying grazing intensities (P<0.05). Our investigation reveals that elevated grazing intensity intensifies the stress response in C. tibetica, triggering heightened antioxidative defenses and stress-induced biochemical activities. Distinctive metabolites play a pivotal role in responding to stress, facilitating the plant's adaptation to environmental challenges and fostering regeneration.

Robustness and Complexity of Directed and Weighted Metabolic Hypergraphs

Metabolic networks are probably among the most challenging and important biological networks. Their study provides insight into how biological pathways work and how robust a specific organism is against an environment or therapy. Here, we propose a directed hypergraph with edge-dependent vertex weight as a novel framework to represent metabolic networks. This hypergraph-based representation captures higher-order interactions among metabolites and reactions, as well as the directionalities of reactions and stoichiometric weights, preserving all essential information. Within this framework, we propose the communicability and the search information as metrics to quantify the robustness and complexity of directed hypergraphs. We explore the implications of network directionality on these measures and illustrate a practical example by applying them to a small-scale E. coli core model. Additionally, we compare the robustness and the complexity of 30 different models of metabolism, connecting structural and biological properties. Our findings show that antibiotic resistance is associated with high structural robustness, while the complexity can distinguish between eukaryotic and prokaryotic organisms.

Integrated Analysis of Transcriptomics and Metabolomics Unveil the Novel Insight of One-Year-Old Precocious Mechanism in the Chinese Mitten Crab, Eriocheir sinensis

Eriocheir sinensis is traditionally a native high-value crab that is widely distributed in eastern Asia, and the precocity is considered the bottleneck problem affecting the development of the industry. The precocious E. sinensis is defined as a crab that reaches complete sexual maturation during the first year of its lifespan rather than as normally in the second year. However, the exact regulatory mechanisms underlying the precocity are still unclear to date. This study is the first to explore the mechanism of precocity with transcriptome-metabolome association analysis between the precocious and normal sexually mature E. sinensis. Our results indicated that the phenylalanine metabolism (map00360) and neuroactive ligand-receptor interaction (map04080) pathways play an important role in the precocity in the ovary of E. sinensis. In map00360, the predicted aromatic-L-amino-acid decarboxylase and 4-hydroxyphenylpyruvate dioxygenase isoform X1 genes and the phenethylamine, phenylethyl alcohol, trans-2-hydroxycinnamate, and L-tyrosine metabolites were all down-regulated in the ovary of the precocious E. sinensis. The map04080 was the common KEGG pathway in the ovary and hepatopancreas between the precocious and normal crab. In the ovary, the predicted growth hormone secretagogue receptor type 1 gene was up-regulated, and the L-glutamate metabolite was down-regulated in the precocious E. sinensis. In the hepatopancreas, the predicted forkhead box protein I2 gene and taurine metabolite were up-regulated and the the L-glutamate metabolite was down-regulated in the precocious crab. There was no common pathway in the testis. Numerous common pathways in the hepatopancreas between male precocious and normal crab were identified. The specific amino acids, fatty acids and flavorful nucleotide (inosine monophosphate (MP), cytidine MP, adenosine MP, uridine MP, and guanosine MP) contents in the hepatopancreas and gonads further confirmed the above omics results. Our results suggest that the phenylalanine metabolism may affect the ovarian development by changing the contents of the neurotransmitter and tyrosine. The neuroactive ligand-receptor interaction pathway may affect the growth by changing the expressions of related genes and affect the umami taste of the gonads and hepatopancreas through the differences of L-glutamate metabolite in the precocious E. sinensis. The results provided valuable and novel insights on the precocious mechanism and may have a significant impact on the development of the E. sinensis aquaculture industry.

Integrated Transcriptomics and Metabolomics Analysis of the Fructan Metabolism Response to Low-Temperature Stress in Garlic

As the main reserve carbohydrate in garlic, fructan contributes to garlic's yield and quality formation. Numerous studies have shown that plant fructan metabolism induces a stress response to adverse environments. However, the transcriptional regulation mechanism of garlic fructan in low-temperature environments is still unknown. In this study, the fructan metabolism of garlic seedlings under low-temperature stress was revealed by transcriptome and metabolome approaches. With the extension of stress time, the number of differentially expressed genes and metabolites increased. Using weighted gene co-expression network analysis (WGCNA), three key enzyme genes related to fructan metabolism were screened (a total of 12 transcripts): sucrose: sucrose 1-fructosyltransferase (1-SST) gene; fructan: fructan 6G fructosyltransferase (6G-FFT) gene; and fructan 1-exohydrolase (1-FEH) gene. Finally, two hub genes were obtained, namely Cluster-4573.161559 (6G-FFT) and Cluster-4573.153574 (1-FEH). The correlation network and metabolic heat map analysis between fructan genes and carbohydrate metabolites indicate that the expression of key enzyme genes in fructan metabolism plays a positive promoting role in the fructan response to low temperatures in garlic. The number of genes associated with the key enzyme of fructan metabolism in trehalose 6-phosphate was the highest, and the accumulation of trehalose 6-phosphate content may mainly depend on the key enzyme genes of fructan metabolism rather than the enzyme genes in its own synthesis pathway. This study not only obtained the key genes of fructan metabolism in garlic seedlings responding to low temperatures but also preliminarily analyzed its regulatory mechanism, providing an important theoretical basis for further elucidating the cold resistance mechanism of garlic fructan metabolism.

Systematic comparison of local approaches for isotopically nonstationary metabolic flux analysis

Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determine cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA) that relies on the patterns of isotope labeling of metabolites in the network. For metabolic systems, typical for plants, where all potentially labeled atoms effectively have only one source atom pool, only isotopically nonstationary MFA can provide information about intracellular fluxes. There are several global approaches that implement MFA for an entire metabolic network and estimate, at once, a steady-state flux distribution for all reactions with identifiable fluxes in the network. In contrast, local approaches deal with estimation of fluxes for a subset of reactions, with smaller data demand for flux estimation. Here we present a systematic comparative review and benchmarking of the existing local approaches for isotopically nonstationary MFA. The comparison is conducted with respect to the required data and underlying computational problems solved on a synthetic network example. Furthermore, we benchmark the performance of these approaches in estimating fluxes for a subset of reactions using data obtained from the simulation of nitrogen fluxes in the Arabidopsis thaliana core metabolism. The findings pinpoint practical aspects that need to be considered when applying local approaches for flux estimation in large-scale plant metabolic networks.

Effects of glycosidase on glycoside-bound aroma compounds in grape and cherry juice

This paper reports the occurrence of six kinds of commercial enzyme hydrolysis effects for use in grape juice and cherry juice, which provide a basis for studying the bound aroma compounds in fruit juice and their application in production. Using headspace solid-phase microextraction combined with GC-MS, a reliable procedure for determining the free and glycosidic-bound volatile compounds has been established. Comparison of these free and bound aroma compounds revealed that non-volatile glycosides, known as aroma precursors, occur at high concentrations in grape and cherry juice. Using six different glycosidase enzymes, 67 volatile compounds were identified in these two juices, including terpenes, C13-norisoprenoids, higher alcohols, esters, C6-compounds, C9-compounds, and phenols. The different enzymes had significant effects on varietal aroma. Creative and AR2000 had similar hydrolysis effects, which contribute greatly to the characteristic aroma of grape juice and cherry juice, significantly enhance the floral and fruity features of fruit juice, and improve aroma complexity in the system. The Creative enzyme can be used as a new choice for studying juice-bound aroma and hydrolysis-bound aroma in fruit and wine production.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-022-05662-3.

Response of sugar metabolism in the cotyledons and roots of Ricinus communis subjected to salt stress

Ricinus communis is an important oilseed crop worldwide and is also considered one of the best potential plants for salt-affected soil improvement in northeast China. However, little is known about photosynthesis and carbohydrate metabolism in this plant, nor the distribution of carbohydrates in cotyledons and roots under salinity stress. In the present study, seedling growth, gas exchange parameters (P_N , E, g_s and C_i ), carbohydrate (fructose, sucrose, glucose, soluble sugar and starch) metabolism and related enzymes and genes were measured in Ricinus plants. Under salt stress, P_N of cotyledons decreased significantly (P < 0.05), resulting in weak photosynthetic capacity. Furthermore, salt stress increased sucrose and glucose content in cotyledons, but decreased soluble sugar and starch content. However, sucrose increased and starch decreased in roots. This may be correlated with the increasing sugar metabolism under salinity, including notable changes in sugar-related enzyme activities (SPS, SuSy, α-amylase and β-amylase) and gene expression of RcINV, RcSUS, RcAmY, RcBAM and RcGBE1. The results suggest that salinity reduces photosynthesis of cotyledons, alters carbohydrate allocation between cotyledons and roots and also promotes starch utilization in cotyledons and starch biosynthesis in roots, leading to a functional imbalance between cotyledons and roots. Together, these findings provide insights into the crucial role of sugar metabolism in improving salt-tolerance of Ricinus during the early seedling growth stage.

H2 S improves salt-stress recovery via organic acid turn-over in apple seedlings

Signalling roles of hydrogen sulphide (H₂ S) in stress biology are widely reported but not sufficiently established to urge its use in agronomic practice. Our lack of quantitative understanding of the metabolic rewiring in H₂ S signalling makes it difficult to elucidate its functions in stress tolerance on the biochemical level. Here, Malus hupehensis Rehd. var. pingyiensis seedlings were first treated with salt stress for 2 weeks and then treated with four different concentrations of NaHS. Through vigorous investigations, including phenotypic analysis, ¹³ C transient labelling and targeted metabolic and transcriptomic analysis, for the first time in the seedlings of a woody fruit crop, we found out that H₂ S recycles fixed carbons through glycolysis and tricarboxylic acid cycle to inhibit the futile accumulation of carbohydrates, to maintain an efficient CO₂ assimilation, to keep a balanced starch metabolism, to produce sufficient H₂ O₂ , to maintain malate/γ-aminobutyric acid homeostasis via an H₂ O₂ -induced anion channel (aluminium-activated malate transporter) and eventually to improve salt-stress recovery. Our results systematically demonstrate the vital roles of central carbon metabolism in H₂ S signalling and clarify the mode of action of H₂ S in apple seedlings. We conclude that H₂ S signalling interacts with central carbon metabolism in a bottom-up manner to recover plant growth after salt stress.

An automated workflow that generates atom mappings for large-scale metabolic models and its application to Arabidopsis thaliana

Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating ¹⁵ N isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future ¹⁵ N-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.

Transcriptomic Profile Analysis of Populus talassica × Populus euphratica Response and Tolerance under Salt Stress Conditions

A new Populus variety with a strong salt tolerance was obtained from cross breeding P. talassica as the female parent and P. euphratica as the male parent. In order to elucidate the molecular mechanism and find out the major differentially expressed genes of salt tolerance of P. talassica × P. euphratica, after being subjected to salt stress, at 0, 200, and 400 mmol/L NaCl, the root, stem, and leaf transcriptomes (denoted as R0, S0, and L0; R200, S200, and L200; and R400, S400, and L400, respectively) of P. talassica × P. euphratica were sequenced. In total, 41,617 differentially expressed genes (DEGs) were identified in all the comparison groups with 21,603 differentially upregulated genes and 20,014 differentially downregulated genes. Gene Ontology analysis showed that DEGs were significantly enriched in biological processes that may be involved in salt stress, such as ‘cell communication’, ‘ion transport’, ‘signaling’, and signal ‘transmission’. Kyoto Encyclopedia of Genes and Genomes analysis showed that DEGs were mainly enriched in pathways of ‘plant–pathogen interaction’, ‘carbon metabolism’, and ‘plant hormone signal transmission’. The pathways and related gene information formed a basis for future research on the mechanisms of salt stress, the development of molecular markers, and the cloning of key genes in P. talassica × P. euphratica.

Can biochemical traits bridge the gap between genomics and plant performance? A study in rice under drought

The possibility of introducing metabolic/biochemical phenotyping to complement genomics-based predictions in breeding pipelines has been considered for years. Here we examine to what extent and under what environmental conditions metabolic/biochemical traits can effectively contribute to understanding and predicting plant performance. In this study, multivariable statistical models based on flag leaf central metabolism and oxidative stress status were used to predict grain yield (GY) performance for 271 indica rice (Oryza sativa) accessions grown in the field under well-watered and reproductive stage drought conditions. The resulting models displayed significantly higher predictability than multivariable models based on genomic data for the prediction of GY under drought (Q2 = 0.54-0.56 versus 0.35) and for stress-induced GY loss (Q2 = 0.59-0.64 versus 0.03-0.06). Models based on the combined datasets showed predictabilities similar to metabolic/biochemical-based models alone. In contrast to genetic markers, models with enzyme activities and metabolite values also quantitatively integrated the effect of physiological differences such as plant height on GY. The models highlighted antioxidant enzymes of the ascorbate-glutathione cycle and a lipid oxidation stress marker as important predictors of rice GY stability under drought at the reproductive stage, and these stress-related variables were more predictive than leaf central metabolites. These findings provide evidence that metabolic/biochemical traits can integrate dynamic cellular and physiological responses to the environment and can help bridge the gap between the genome and the phenome of crops as predictors of GY performance under drought.

Sucrose synthases are not involved in starch synthesis in Arabidopsis leaves

Many plants accumulate transitory starch reserves in their leaves during the day to buffer their carbohydrate supply against fluctuating light conditions, and to provide carbon and energy for survival at night. It is universally accepted that transitory starch is synthesized from ADP-glucose (ADPG) in the chloroplasts. However, the consensus that ADPG is made in the chloroplasts by ADPG pyrophosphorylase has been challenged by a controversial proposal that ADPG is made primarily in the cytosol, probably by sucrose synthase (SUS), and then imported into the chloroplasts. To resolve this long-standing controversy, we critically re-examined the experimental evidence that appears to conflict with the consensus pathway. We show that when precautions are taken to avoid artefactual changes during leaf sampling, Arabidopsis thaliana mutants that lack SUS activity in mesophyll cells (quadruple sus1234) or have no SUS activity (sextuple sus123456) have wild-type levels of ADPG and starch, while ADPG is 20 times lower in the pgm and adg1 mutants that are blocked in the consensus chloroplastic pathway of starch synthesis. We conclude that the ADPG needed for starch synthesis in leaves is synthesized primarily by ADPG pyrophosphorylase in the chloroplasts.

Potential metabolic mechanisms for inhibited chloroplast nitrogen assimilation under high CO2

Improving photosynthesis is considered a major and feasible option to dramatically increase crop yield potential. Increased atmospheric CO2 concentration often stimulates both photosynthesis and crop yield, but decreases protein content in the main C3 cereal crops. This decreased protein content in crops constrains the benefits of elevated CO2 on crop yield and affects their nutritional value for humans. To support studies of photosynthetic nitrogen assimilation and its complex interaction with photosynthetic carbon metabolism for crop improvement, we developed a dynamic systems model of plant primary metabolism, which includes the Calvin-Benson cycle, the photorespiration pathway, starch synthesis, glycolysis-gluconeogenesis, the tricarboxylic acid cycle, and chloroplastic nitrogen assimilation. This model successfully captures responses of net photosynthetic CO2 uptake rate (A), respiration rate, and nitrogen assimilation rate to different irradiance and CO2 levels. We then used this model to predict inhibition of nitrogen assimilation under elevated CO2. The potential mechanisms underlying inhibited nitrogen assimilation under elevated CO2 were further explored with this model. Simulations suggest that enhancing the supply of α-ketoglutarate is a potential strategy to maintain high rates of nitrogen assimilation under elevated CO2. This model can be used as a heuristic tool to support research on interactions between photosynthesis, respiration, and nitrogen assimilation. It also provides a basic framework to support the design and engineering of C3 plant primary metabolism for enhanced photosynthetic efficiency and nitrogen assimilation in the coming high-CO2 world.

Optimising the use of gene expression data to predict plant metabolic pathway memberships

Plant metabolites from diverse pathways are important for plant survival, human nutrition and medicine. The pathway memberships of most plant enzyme genes are unknown. While co-expression is useful for assigning genes to pathways, expression correlation may exist only under specific spatiotemporal and conditional contexts. Utilising > 600 tomato (Solanum lycopersicum) expression data combinations, three strategies for predicting memberships in 85 pathways were explored. Optimal predictions for different pathways require distinct data combinations indicative of pathway functions. Naive prediction (i.e. identifying pathways with the most similarly expressed genes) is error prone. In 52 pathways, unsupervised learning performed better than supervised approaches, possibly due to limited training data availability. Using gene-to-pathway expression similarities led to prediction models that outperformed those based simply on expression levels. Using 36 experimental validated genes, the pathway-best model prediction accuracy is 58.3%, significantly better compared with that for predicting annotated genes without experimental evidence (37.0%) or random guess (1.2%), demonstrating the importance of data quality. Our study highlights the need to extensively explore expression-based features and prediction strategies to maximise the accuracy of metabolic pathway membership assignment. The prediction framework outlined here can be applied to other species and serves as a baseline model for future comparisons.

Discovery of network motifs based on induced subgraphs using a dynamic expansion tree

Biological networks are powerful representations of topological features in biological systems. Finding network motifs in biological networks is a computationally hard problem due to their huge size and abrupt increase of search space with the increase of motif size. Motivated by the computational challenges of network motif discovery and considering the importance of this topic, an efficient and scalable network motif discovery algorithm based on induced subgraphs in a dynamic expansion tree is proposed. This algorithm uses a pruning strategy to overcome the space limitation of the static expansion tree. The proposed algorithm can identify large network motifs up to size 15 by significantly reducing the computationally expensive subgraph isomorphism checks. Further, the present work avoids the unnecessary growth of patterns that do not have any statistical significance. The runtime performance of the proposed algorithm outperforms most of the existing algorithms for large network motifs.

Metabolic networks of the Nicotiana genus in the spotlight: content, progress and outlook

Manually curated metabolic databases residing at the Sol Genomics Network comprise two taxon-specific databases for the Solanaceae family, i.e. SolanaCyc and the genus Nicotiana, i.e. NicotianaCyc as well as six species-specific databases for Nicotiana tabacum TN90, N. tabacum K326, Nicotiana benthamiana, N. sylvestris, N. tomentosiformis and N. attenuata. New pathways were created through the extraction, examination and verification of related data from the literature and the aid of external database guided by an expert-led curation process. Here we describe the curation progress that has been achieved in these databases since the first release version 1.0 in 2016, the curation flow and the curation process using the example metabolic pathway for cholesterol in plants. The current content of our databases comprises 266 pathways and 36 superpathways in SolanaCyc and 143 pathways plus 21 superpathways in NicotianaCyc, manually curated and validated specifically for the Solanaceae family and Nicotiana genus, respectively. The curated data have been propagated to the respective Nicotiana-specific databases, which resulted in the enrichment and more accurate presentation of their metabolic networks. The quality and coverage in those databases have been compared with related external databases and discussed in terms of literature support and metabolic content.

Characterization of effects of genetic variants via genome-scale metabolic modelling

Genome-scale metabolic networks for model plants and crops in combination with approaches from the constraint-based modelling framework have been used to predict metabolic traits and design metabolic engineering strategies for their manipulation. With the advances in technologies to generate large-scale genotyping data from natural diversity panels and other populations, genome-wide association and genomic selection have emerged as statistical approaches to determine genetic variants associated with and predictive of traits. Here, we review recent advances in constraint-based approaches that integrate genetic variants in genome-scale metabolic models to characterize their effects on reaction fluxes. Since some of these approaches have been applied in organisms other than plants, we provide a critical assessment of their applicability particularly in crops. In addition, we further dissect the inferred effects of genetic variants with respect to reaction rate constants, abundances of enzymes, and concentrations of metabolites, as main determinants of reaction fluxes and relate them with their combined effects on complex traits, like growth. Through this systematic review, we also provide a roadmap for future research to increase the predictive power of statistical approaches by coupling them with mechanistic models of metabolism.

Plant synthetic biology for producing potent phyto-antimicrobials to combat antimicrobial resistance

Inappropriate and injudicious use of antimicrobial drugs in human health, hygiene, agriculture, animal husbandry and food industries has contributed significantly to rapid emergence and persistence of antimicrobial resistance (AMR), one of the serious global public health threats. The crisis of AMR versus slower discovery of newer antibiotics put forth a daunting task to control these drug-resistant superbugs. Several phyto-antimicrobials have been identified in recent years with direct-killing (bactericidal) and/or drug-resistance reversal (re-sensitization of AMR phenotypes) potencies. Phyto-antimicrobials may hold the key in combating AMR owing to their abilities to target major microbial drug-resistance determinants including cell membrane, drug-efflux pumps, cell communication and biofilms. However, limited distribution, low intracellular concentrations, eco-geographical variations, beside other considerations like dynamic environments, climate change and over-exploitation of plant-resources are major blockades in full potential exploration phyto-antimicrobials. Synthetic biology (SynBio) strategies integrating metabolic engineering, RNA-interference, genome editing/engineering and/or systems biology approaches using plant chassis (as engineerable platforms) offer prospective tools for production of phyto-antimicrobials. With expanding SynBio toolkit, successful attempts towards introduction of entire gene cluster, reconstituting the metabolic pathway or transferring an entire metabolic (or synthetic) pathway into heterologous plant systems highlight the potential of this field. Through this perspective review, we are presenting herein the current situation and options for addressing AMR, emphasizing on the significance of phyto-antimicrobials in this apparently post-antibiotic era, and effective use of plant chassis for phyto-antimicrobial production at industrial scales along with major SynBio tools and useful databases. Current knowledge, recent success stories, associated challenges and prospects of translational success are also discussed.

Mass spectrometry-based forest tree metabolomics

Research in forest tree species has advanced slowly when compared with other agricultural crops and model organisms, mainly due to the long-life cycles, large genome sizes, and lack of genomic tools. Additionally, trees are complex matrices, and the presence of interferents (e.g., oleoresins and cellulose) challenges the analysis of tree tissues with mass spectrometry (MS)-based analytical platforms. In this review, advances in MS-based forest tree metabolomics are discussed. Given their economic and ecological significance, particular focus is given to Pinus, Quercus, and Eucalyptus forest tree species to better understand their metabolite responses to abiotic and biotic stresses in the current climate change scenario. Furthermore, MS-based metabolomics technologies produce large and complex datasets that require expertize to adequately manage, process, analyze, and store the data in dedicated repositories. To ensure that the full potential of forest tree metabolomics data are translated into new knowledge, these data should comply with the FAIR principles (i.e., Findable, Accessible, Interoperable, and Re-usable). It is essential that adequate standards are implemented to annotate metadata from forest tree metabolomics studies as is already required by many science and governmental agencies and some major scientific publishers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev 40:126-157, 2021.

LC-MS based plant metabolic profiles of thirteen grassland species grown in diverse neighbourhoods

In plants, secondary metabolite profiles provide a unique opportunity to explore seasonal variation and responses to the environment. These include both abiotic and biotic factors. In field experiments, such stress factors occur in combination. This variation alters the plant metabolic profiles in yet uninvestigated ways. This data set contains trait and mass spectrometry data of thirteen grassland species collected at four time points in the growing season in 2017. We collected above-ground vegetative material of seven grass and six herb species that were grown in plant communities with different levels of diversity in the Jena Experiment. For each sample, we recorded visible traits and acquired shoot metabolic profiles on a UPLC-ESI-Qq-TOF-MS. We performed the raw data pre-processing in Galaxy-W4M and prepared the data for statistical analysis in R by applying missing data imputation, batch correction, and validity checks on the features. This comprehensive data set provides the opportunity to investigate environmental dynamics across diverse neighbourhoods that are reflected in the metabolomic profile.

Effect of sugar feedback regulation on major genes and proteins of photosynthesis in sugarcane leaves

Productivity of sugarcane (Saccharum spp.) relies upon sucrose production in leaves and movement to sinks. The feedback regulatory effect of sugar upon photosynthesis balances this process involving Phosphoenolpyruvate carboxylase (PEPCase) and Rubisco where greater understanding in this area may allow manipulation to achieve higher yields. Accumulation of sucrose in leaves and decreased photosynthesis are early symptoms of the condition called yellow canopy syndrome (YCS) in sugarcane, which presents as a system in which to study sucrose feedback regulation. This work investigates changes in gene expression and protein abundance which coincide with the sugar accumulation in the leaves of YCS symptomatic sugarcane. During the early-stage of sugar accumulation, the levels of the Photosystem II core protein D1, and PsbQ of the oxygen-evolving complex decreased significantly. Transcript levels of these proteins also decreased, suggesting both nuclear and chloroplast gene expression were affected early in sugar build-up of YCS development. Transcript level of primary carbon fixation reactions enzyme NADP malate dehydrogenase was especially downregulated. However, PEPCase, decarboxylation and re-fixation (Rubisco) enzymes were not negatively regulated at the transcript or protein abundance level. Phosphoenolpyruvate carboxykinase was upregulated in both gene expression and protein abundance. The Calvin cycle in the bundle sheath was sensitive through the CP12 protein. Two isoforms of CP12 were found, one of which showed downregulation which coincided with a decrease in CP12 protein. This suggests transcript and protein decrease of PEPCase and Rubisco may be secondary regulation points of the sugar feedback regulation process upon photosynthesis in sugarcane leaves.

Identification of the gene network modules highly associated with the synthesis of phenolics compounds in barley by transcriptome and metabolome analysis

Phenolic compounds in barley grains have an important influence on beer flavor and stability. Drought condition enhances the content of phenolics in barley grains, leading to reduced malt quality. In this study, two barley genotypes, XZ20 and XZ25 with different total phenolics content were used to investigate the effect of drought on phenolic compounds during grain developing stage. Totally, 118 phenolic metabolites were affected by drought stress. A weighted gene co-expression network analysis (WGCNA) of 17,424 highly expressed genes uncovered black (two hub genes belonged to UGT family) and turquoise modules (three hub genes belonged to phenolics pathway) that are significantly associated with the variation of phenolics. All these results reveal the changes of phenolic metabolites during grain development and provide a new insight into the regulation network of phenolic compounds under drought stress.

Growth promoting effects of Pluronic F-68 on callus proliferation of recalcitrant rice cultivar

This study was undertaken to evaluate growth-promoting effects of Pluronic F-68 (PF-68) on recalcitrant MR 219 rice callus. Our study shows that calli grown on Murashige and Skoog medium supplemented with 0.04% PF-68 significantly increased callus proliferation by 58.80% (fresh weight) and 23.98% (dry weight) while root formation from callus was enhanced by 28.57%. Enhanced callus proliferation was supported by biochemical analysis, whereby highest amount of soluble sugar (1.77 mg/mL) and protein (0.17 mg/mL) contents were recorded in calli grown on 0.04% PF-68. Furthermore, enhanced expression of sucrose synthase (2.65-folds) and NADH-dependent glutamate synthase (1.86-folds) genes in calli grown on 0.04% PF-68 also correlates with enhanced callus proliferation. In contrast, high concentration of PF-68 (0.10%) recorded highest amount of phenolic (0.74 mg/mL), flavonoid (0.08 mg/mL), and hydrogen peroxide content (0.06 mg/mL) as compared to other treatment groups indicates activation of plant defence mechanism towards stress. Similarly, high expression of 4-coumarate:CoA ligase 3 (1.28-folds), chalcone-flavonone isomerase (1.65-folds) and ascorbate peroxidase (1.61-folds) genes were observed in calli grown on 0.10% PF-68 further supports increasing stress caused by the high concentration of PF-68. Taken together, our study revealed that optimum concentration of PF-68 could improve recalcitrant rice callus proliferation via enhanced sugar metabolism and amino acid biosynthesis which are crucial towards plant growth and development. However, at high concentration, PF-68 induces stress in plant which enhance the production of secondary metabolite to maintain cellular homeostasis.

Differential Proteome Analysis of Hybrid Bamboo (Bambusa pervariabilis × Dendrocalamopsis grandis) Under Fungal Stress (Arthrinium phaeospermum)

In this study, TMT (tandem mass tag)-labeled quantitative protein technology combined with LC–MS/MS (liquid chromatography-mass spectrometry/mass spectrometry) was used to isolate and identify the proteins of the hybrid bamboo (Bambusa pervariabilis × Dendrocalamopsis grandis) and the bamboo inoculated with the pathogenic fungi Arthrinium phaeospermum. A total of 3320 unique peptide fragments were identified after inoculation with either A. phaeospermum or sterile water, and 1791 proteins were quantified. A total of 102 differentially expressed proteins were obtained, of which 66 differential proteins were upregulated and 36 downregulated in the treatment group. Annotation and enrichment analysis of these peptides and proteins using the GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases with bioinformatics software showed that the differentially expressed protein functional annotation items were mainly concentrated on biological processes and cell components. The LC–PRM/MS (liquid chromatography-parallel reaction monitoring/mass spectrometry) quantitative analysis technique was used to quantitatively analyze 11 differential candidate proteins obtained by TMT combined with LC–MS/MS. The up–down trend of 10 differential proteins in the PRM results was consistent with that of the TMT quantitative analysis. The coincidence rate of the two results was 91%, which confirmed the reliability of the proteomic results. Therefore, the differentially expressed proteins and signaling pathways discovered here may be the further concern for the bamboo-pathogen interaction studies.

Source Strength Modulates Fruit Set by Starch Turnover and Export of Both Sucrose and Amino Acids in Pepper

Fruit set is an important yield-related parameter, which varies drastically due to genetic and environmental factors. Here, two commercial cultivars of Capsicum chinense (Biquinho and Habanero) were evaluated in response to light intensity (unshaded and shaded) and N supply (deficiency and sufficiency) to understand the role of source strength on fruit set at the metabolic level. We assessed the metabolic balance of primary metabolites in source leaves during the flowering period. Furthermore, we investigated the metabolic balance of the same metabolites in flowers to gain more insights into their influence on fruit set. Genotype and N supply had a strong effect on fruit set and the levels of primary metabolites, whereas light intensity had a moderate effect. Higher fruit set was mainly related to the export of both sucrose and amino acids from source leaves to flowers. Additionally, starch turnover in source leaves, but not in flowers, had a central role on the sucrose supply to sink organs at night. In flowers, our results not only confirmed the role of the daily supply of carbohydrates on fruit set but also indicated a potential role of the balance of amino acids and malate.

Differential responses of molecular mechanisms and physiochemical characters in wild and cultivated soybeans against invasion by the pathogenic Fusarium oxysporum Schltdl

Cultivated soybean (Glycine max) was derived from the wild soybean (Glycine soja), which has genetic resources that can be critically important for improving plant stress resistance. However, little information is available pertaining to the molecular and physiochemical comparison between the cultivated and wild soybeans in response to the pathogenic Fusarium oxysporum Schltdl. In this study, we first used comparative phenotypic and paraffin section analyses to indicate that wild soybean is indeed more resistant to F. oxysporum than cultivated soybean. Genome-wide RNA-sequencing approach was then used to elucidate the genetic mechanisms underlying the differential physiological and biochemical responses of the cultivated soybean, and its relative, to F. oxysporum. A greater number of genes related to cell wall synthesis and hormone metabolism were significantly altered in wild soybean than in cultivated soybean under F. oxysporum infection. Accordingly, a higher accumulation of lignins was observed in wild soybean than cultivated soybean under F. oxysporum infection. Collectively, these results indicated that secondary metabolites and plant hormones may play a vital role in differentiating the response between cultivated and wild soybeans against the pathogen. These important findings may provide future direction to breeding programs to improve resistance to F. oxysporum in the elite soybean cultivars by taking advantage of the genetic resources within wild soybean germplasm.

Metabolic acclimation-a key to enhancing photosynthesis in changing environments?

Plants adjust their photosynthetic capacity in response to their environment in a way that optimizes their yield and fitness. There is growing evidence that this acclimation is a response to changes in the leaf metabolome, but the extent to which these are linked and how this is optimized remain poorly understood. Using as an example the metabolic perturbations occurring in response to cold, we define the different stages required for acclimation, discuss the evidence for a metabolic temperature sensor, and suggest further work towards designing climate-smart crops. In particular, we discuss how constraint-based and kinetic metabolic modelling approaches can be used to generate targeted hypotheses about relevant pathways, and argue that a stronger integration of experimental and in silico studies will help us to understand the tightly regulated interplay of carbon partitioning and resource allocation required for photosynthetic acclimation to different environmental conditions.

Nitrogen in the defense system of Annona emarginata (Schltdl.) H. Rainer

The concentration of nitrogen can generate different strategies in plants in response to stress. In this study, we investigated how nitrogen concentration interferes with the defense system of Annona emarginata. Low concentrations of nitrogen increased the allocation of photosynthetic resources to carbon metabolism, resulting in an increase in the synthesis of volatile substances involved in signaling and defense that contributed to antioxidant enzymes in overcoming stress. The availability of nitrogen at 5.62 mM concentration might have helped to induce increased resistance in the plants because at this concentration, signaling substances and defense substances (monoterpenes and sesquiterpenes) were observed. Plants cultivated with the highest nitrate concentration displaced energy for the reduction of this ion, likely forming nitric oxide, a signaling molecule. This condition, together with the decrease in carbon skeletons, may have contributed to the lower synthesis of volatile substances of the specialized metabolism that are also involved with signaling. Varying the nitrogen in Annona emarginata cultivation revealed that depending on the concentration, volatile substances show higher or lower synthesis and participation in the system of signaling and defense in the plant. These results may suggest that volatile substances participate in resistance to pests and diseases, which is a necessary condition for Annona emarginata to be preferentially used as rootstock for Annona x atemoya.

Nitrogen differentially modulates photosynthesis, carbon allocation and yield related traits in two contrasting Capsicum chinense cultivars

Yield-related traits of Capsicum chinense are highly dependent on coordination between vegetative and reproductive growth, since the formation of reproductive tissues occurs iteratively in new sympodial bifurcations. In this study, we used two C. chinense cultivars (Biquinho and Habanero), contrasting for fruit size and fruit set, to investigate the responses of nitrogen (N) deficiency and excess on growth, photosynthesis, carbon (C) and N metabolisms as well as yield-related traits. Both cultivars increased biomass allocation to leaves in conditions of higher N supply and exhibited a parabolic behavior for fruit biomass allocation. Plants growing under N-deficiency produced a lower number of flowers and heavier fruits. Contrarily, plants under high N condition tended to decrease their CO₂ assimilation rate, harvest index and fruit weight. Biquinho, the cultivar with lower fruit size and higher fruit set, was initially less affected by excess of N due to its continuous formation of new reproductive sinks in relation to Habanero (which has lower fruit set and higher fruit size). The results suggest that N amount influences sucrose supply to different organs and can differentially affect yield-related traits between Capsicum cultivars with contrasting source-sink relations.

The magic 'hammer' of TOR: the multiple faces of a single pathway in the metabolic regulation of plant growth and development

The target of rapamycin (TOR) pathway has emerged as a central hub synchronizing plant growth according to the nutrient/energy status and environmental inputs. Molecular mechanisms through which TOR promotes plant growth involve the positive regulation of transcription of cell proliferation-associated genes, mRNA translation initiation and ribosome biogenesis, to cite a few examples. Phytohormones, light, sugars, and sulfur have been found to broadly regulate TOR activity. TOR operates as a metabolic homeostat to fine-tune anabolic processes and efficiently enable plant growth under different circumstances. However, little is known about the multiple effectors that act up- and downstream of TOR. Here, we mainly discuss recent findings related to the TOR pathway in the context of plant metabolism and highlight areas of interest that need to be addressed to keep unravelling the intricate networks governing the regulation of TOR and its function in controlling biosynthetic growth.

Consequences of photosystem-I damage and repair on photosynthesis and carbon use in Arabidopsis thaliana

Natural growth environments commonly include fluctuating conditions that can disrupt the photosynthetic energy balance and induce photoinhibition through inactivation of the photosynthetic apparatus. Photosystem II (PSII) photoinhibition is efficiently reversed by the PSII repair cycle, whereas photoinhibited photosystem I (PSI) recovers much more slowly. In the current study, treatment of the Arabidopsis thaliana mutant proton gradient regulation 5 (pgr5) with excess light was used to compromise PSI functionality in order to investigate the impact of photoinhibition and subsequent recovery on photosynthesis and carbon metabolism. The negative impact of PSI photoinhibition on CO₂ fixation was especially deleterious under low irradiance. Impaired starch accumulation after PSI photoinhibition was reflected in reduced respiration in the dark, but this was not attributed to impaired sugar synthesis. Normal chloroplast and mitochondrial metabolisms were shown to recover despite the persistence of substantial PSI photoinhibition for several days. The results of this study indicate that the recovery of PSI function involves the reorganization of the light-harvesting antennae, and suggest a pool of surplus PSI that can be recruited to support photosynthesis under demanding conditions.

Using a Multi-compartmental Metabolic Model to Predict Carbon Allocation in Arabidopsis thaliana

The molecular mechanism of loading/unloading of sucrose into/from the phloem plays an important role in sucrose translocation among plant tissues. Perturbation of this mechanism results in growth phenotypes of a plant. In order to better understand the coupling of sucrose translocation with metabolic processes a multi-compartmental metabolic network of Arabidopsis thaliana was reconstructed and optimized with respect to biomass growth, both in light and in dark conditions. The model can be used to perform flux balance analysis of metabolic fluxes through the central carbon metabolism and catabolic and anabolic pathways. Balances and turnover of energy (ATP/ADP) and redox metabolites (NAD(P)H/NAD(P)) as well as proton concentrations in different compartments can be estimated. Importantly, the model can be used to quantify the translocation of sucrose from source to sink tissues through phloem in association with an integral balance of protons, which in turn is defined by the operational modes of the energy metabolism (light and dark conditions). This chapter describes how a multi-compartmental model to predict carbon allocation is constructed and used.

Advances in metabolic flux analysis toward genome-scale profiling of higher organisms

Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.

Grape and Wine Metabolomics to Develop New Insights Using Untargeted and Targeted Approaches

Chemical analysis of grape juice and wine has been performed for over 50 years in a targeted manner to determine a limited number of compounds using Gas Chromatography, Mass-Spectrometry (GC-MS) and High Pressure Liquid Chromatography (HPLC). Therefore, it only allowed the determination of metabolites that are present in high concentration, including major sugars, amino acids and some important carboxylic acids. Thus, the roles of many significant but less concentrated metabolites during wine making process are still not known. This is where metabolomics shows its enormous potential, mainly because of its capability in analyzing over 1000 metabolites in a single run due to the recent advancements of high resolution and sensitive analytical instruments. Metabolomics has predominantly been adopted by many wine scientists as a hypothesis-generating tool in an unbiased and non-targeted way to address various issues, including characterization of geographical origin (terroir) and wine yeast metabolic traits, determination of biomarkers for aroma compounds, and the monitoring of growth developments of grape vines and grapes. The aim of this review is to explore the published literature that made use of both targeted and untargeted metabolomics to study grapes and wines and also the fermentation process. In addition, insights are also provided into many other possible avenues where metabolomics shows tremendous potential as a question-driven approach in grape and wine research.

Metabolite Profiles of Sugarcane Culm Reveal the Relationship Among Metabolism and Axillary Bud Outgrowth in Genetically Related Sugarcane Commercial Cultivars

Metabolic composition is known to exert influence on several important agronomic traits, and metabolomics, which represents the chemical composition in a cell, has long been recognized as a powerful tool for bridging phenotype-genotype interactions. In this work, sixteen truly representative sugarcane Brazilian varieties were selected to explore the metabolic networks in buds and culms, the tissues involved in the vegetative propagation of this species. Due to the fact that bud sprouting is a key trait determining crop establishment in the field, the sprouting potential among the genotypes was evaluated. The use of partial least square discriminant analysis indicated only mild differences on bud outgrowth potential under controlled environmental conditions. However, primary metabolite profiling provided information on the variability of metabolic features even under a narrow genetic background, typical for modern sugarcane cultivars. Metabolite-metabolite correlations within and between tissues revealed more complex patterns for culms in relation to buds, and enabled the recognition of key metabolites (e.g., sucrose, putrescine, glutamate, serine, and myo-inositol) affecting sprouting ability. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites can be potentially used as indicators for the genetic background.

The three-legged stool of understanding metabolism: integrating metabolomics with biochemical genetics and computational modeling

Traditional biochemical research has resulted in a good understanding of many aspects of metabolism. However, this reductionist approach is time consuming and requires substantial resources, thus raising the question whether modern metabolomics and genomics should take over and replace the targeted experiments of old. We proffer that such a replacement is neither feasible not desirable and propose instead the tight integration of modern, system-wide omics with traditional experimental bench science and dedicated computational approaches. This integration is an important prerequisite toward the optimal acquisition of knowledge regarding metabolism and physiology in health and disease. The commentary describes advantages and drawbacks of current approaches to assessing metabolism and highlights the challenges to be overcome as we strive to achieve a deeper level of metabolic understanding in the future.