Plant metabolic modeling: achieving new insight into metabolism and metabolic engineering

A Guide to Metabolic Network Modeling for Plant Biology

Plants produce a diverse array of compounds that play crucial roles in growth, in development, and in responses to abiotic and biotic stresses. Understanding the fluxes within metabolic pathways is essential for guiding strategies aimed at directing metabolism for crop improvement and the plant natural product industry. Over the past decade, metabolic network modeling has emerged as a predominant tool for the integration, quantification, and prediction of the spatial and temporal distribution of metabolic flows. In this review, we present the primary methods for constructing mathematical models of metabolic systems and highlight recent achievements in plant metabolism using metabolic modeling. Furthermore, we discuss current challenges in applying network flux analysis in plants and explore the potential use of machine learning technologies in plant metabolic modeling. The practical application of mathematical modeling is expected to provide significant insights into the structure and regulation of plant metabolic networks.

Reprogrammed Plant Metabolism During Viral Infections: Mechanisms, Pathways and Implications

Plant viruses pose a significant threat to global agriculture, leading to substantial crop losses that jeopardise food security and disrupt ecosystem stability. These viral infections often reprogramme plant metabolism, compromising key pathways critical for growth and defence. For instance, infections by cucumber mosaic virus alter amino acid and secondary metabolite biosynthesis, including flavonoid and phenylpropanoid pathways, thereby weakening plant defences. Similarly, tomato bushy stunt virus disrupts lipid metabolism by altering the synthesis and accumulation of sterols and phospholipids, which are essential for viral replication and compromise membrane integrity. Recent advancements in gene-editing technologies, such as CRISPR/Cas9, and metabolomics offer innovative strategies to mitigate these impacts. Precise genetic modifications can restore or optimise disrupted metabolic pathways, enhancing crop resilience to viral infections. Metabolomics further aids in identifying metabolic biomarkers linked to viral resistance, guiding breeding programmes aimed at developing virus-resistant plants. By reducing the susceptibility of crops to viral infections, these approaches hold significant potential to reduce dependence on chemical pesticides, increase crop yields and promote sustainable agricultural practices. Future research should focus on expanding our understanding of virus-host interactions at the molecular level while exploring the long-term ecological impacts of viral infections. Interdisciplinary approaches integrating multi-omics technologies and sustainable management strategies will be critical in addressing the challenges posed by plant viruses and ensuring global agricultural stability.

Model-assisted analysis for tuning anthocyanin composition in grape berries

Anthocyanin composition is responsible for the red colour of grape berries and wines, and contributes to their organoleptic quality. However, anthocyanin biosynthesis is under genetic, developmental and environmental regulation, making its targeted fine-tuning challenging. We constructed a mechanistic model to simulate the dynamics of anthocyanin composition throughout grape ripening in Vitis vinifera, employing a consensus anthocyanin biosynthesis pathway. The model was calibrated and validated using six datasets from eight cultivars and 37 growth conditions. Tuning the transformation and degradation parameters allowed us to accurately simulate the accumulation process of each individual anthocyanin under different environmental conditions. The model parameters were robust across environments for each genotype. The coefficients of determination (R2) for the simulated versus observed values for the six datasets ranged from 0.92 to 0.99, while the relative root mean square errors (RRMSEs) were between 16.8 and 42.1 %. The leave-one-out cross-validation for three datasets showed R2 values of 0.99, 0.96 and 0.91, and RRMSE values of 28.8, 32.9 and 26.4 %, respectively, suggesting a high prediction quality of the model. Model analysis showed that the anthocyanin profiles of diverse genotypes are relatively stable in response to parameter perturbations. Virtual experiments further suggested that targeted anthocyanin profiles may be reached by manipulating a minimum of three parameters, in a genotype-dependent manner. This model presents a promising methodology for characterizing the temporal progression of anthocyanin composition, while also offering a logical foundation for bioengineering endeavours focused on precisely adjusting the anthocyanin composition of grapes.

Elucidating the Mesocarp Drupe Transcriptome of Açai (Euterpe oleracea Mart.): An Amazonian Tree Palm Producer of Bioactive Compounds

Euterpe oleracea palm, endemic to the Amazon region, is well known for açai, a fruit violet beverage with nutritional and medicinal properties. During E. oleracea fruit ripening, anthocyanin accumulation is not related to sugar production, contrarily to grape and blueberry. Ripened fruits have a high content of anthocyanins, isoprenoids, fibers, and proteins, and are poor in sugars. E. oleracea is proposed as a new genetic model for metabolism partitioning in the fruit. Approximately 255 million single-end-oriented reads were generated on an Ion Proton NGS platform combining fruit cDNA libraries at four ripening stages. The de novo transcriptome assembly was tested using six assemblers and 46 different combinations of parameters, a pre-processing and a post-processing step. The multiple k-mer approach with TransABySS as an assembler and Evidential Gene as a post-processer have shown the best results, with an N50 of 959 bp, a read coverage mean of 70x, a BUSCO complete sequence recovery of 36% and an RBMT of 61%. The fruit transcriptome dataset included 22,486 transcripts representing 18 Mbp, of which a proportion of 87% had significant homology with other plant sequences. Approximately 904 new EST-SSRs were described, and were common and transferable to Phoenix dactylifera and Elaeis guineensis, two other palm trees. The global GO classification of transcripts showed similar categories to that in P. dactylifera and E. guineensis fruit transcriptomes. For an accurate annotation and functional description of metabolism genes, a bioinformatic pipeline was developed to precisely identify orthologs, such as one-to-one orthologs between species, and to infer multigenic family evolution. The phylogenetic inference confirmed an occurrence of duplication events in the Arecaceae lineage and the presence of orphan genes in E. oleracea. Anthocyanin and tocopherol pathways were annotated entirely. Interestingly, the anthocyanin pathway showed a high number of paralogs, similar to in grape, whereas the tocopherol pathway exhibited a low and conserved gene number and the prediction of several splicing forms. The release of this exhaustively annotated molecular dataset of E. oleracea constitutes a valuable tool for further studies in metabolism partitioning and opens new great perspectives to study fruit physiology with açai as a model.

Suppression of metabolite shuttles for export of chloroplast and mitochondrial ATP and NADPH increases the cytosolic NADH:NAD+ ratio in tobacco leaves in the dark

The communication between chloroplasts and mitochondria, which depends on the inter-organellar exchange of carbon skeletons, energy, and reducing equivalents, is essential for maintaining efficient respiratory metabolism and photosynthesis. We devised a multi-transgene approach to manipulate the leaf energy and redox balance in tobacco (Nicotiana tabacum) while monitoring the in vivo cytosolic redox status of NAD(H) using the biosensor c-Peredox-mCherry. Our strategy involved altering the shuttling capacity of the chloroplast by (1) increasing the chloroplast malate valve capacity by overexpression of the chloroplast malate valve transporter pOMT from Arabidopsis (AtpOMT1) while (2) reducing the activity of the chloroplast triose-phosphate/3-phosphoglycerate shuttle by knocking down the cytosolic NAD-dependent glyceraldehyde 3-phosphate dehydrogenase (NtGAPC). This was accompanied by (3) alterations to the export of reducing equivalents in the mitochondria by knocking down the mitochondrial malate dehydrogenase (NtmMDH) and (4) an increased expression of the mitochondrial fission regulator FIS1A from Arabidopsis (AtFIS1A). The multi-transgene tobacco plants were analysed in glasshouse conditions and showed significant increases in the cytosolic NADH:NAD+ in the dark when transcript levels for NtGAPC or NtmMDH were knocked down. In addition, principal component analysis and Spearman correlation analyses showed negative correlations between average transcript levels for the gene targets and parameters related to chlorophyll fluorescence and plant growth. Our results highlight the importance of the shuttling of energy and reducing equivalents from chloroplasts and mitochondria to support photosynthesis and growth and suggest an important role for the dual 2-oxoglutarate/malate and oxaloacetate/malate transporter (pOMT).

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.

Multi-omics approaches explain the growth-promoting effect of the apocarotenoid growth regulator zaxinone in rice

The apocarotenoid zaxinone promotes growth and suppresses strigolactone biosynthesis in rice. To shed light on the mechanisms underlying its growth-promoting effect, we employed a combined omics approach integrating transcriptomics and metabolomics analysis of rice seedlings treated with zaxinone, and determined the resulting changes at the cellular and hormonal levels. Metabolites as well as transcripts analysis demonstrate that zaxinone application increased sugar content and triggered glycolysis, the tricarboxylic acid cycle and other sugar-related metabolic processes in rice roots. In addition, zaxinone treatment led to an increased root starch content and induced glycosylation of cytokinins. The transcriptomic, metabolic and hormonal changes were accompanied by striking alterations of roots at cellular level, which showed an increase in apex length, diameter, and the number of cells and cortex cell layers. Remarkably, zaxinone did not affect the metabolism of roots in a strigolactone deficient mutant, suggesting an essential role of strigolactone in the zaxinone growth-promoting activity. Taken together, our results unravel zaxinone as a global regulator of the transcriptome and metabolome, as well as of hormonal and cellular composition of rice roots. Moreover, they suggest that zaxinone promotes rice growth most likely by increasing sugar uptake and metabolism, and reinforce the potential of this compound in increasing rice performance.

Wang et al. report zaxinone as a global regulator of the transcriptome and metabolome, as well as of hormonal and cellular composition of rice roots. This study shows that zaxinone promotes rice growth by enhancing root sugar uptake and metabolism and modulation of cytokinin content, indicating the potential application of this compound in increasing rice performance.

Shining a light on NAD- and NADP-based metabolism in plants

The pyridine nucleotides nicotinamide adenine dinucleotide [NAD(H)] and nicotinamide adenine dinucleotide phosphate [NADP(H)] simultaneously act as energy transducers, signalling molecules, and redox couples. Recent research into photosynthetic optimisation, photorespiration, immunity, hypoxia/oxygen signalling, development, and post-harvest metabolism have all identified pyridine nucleotides as key metabolites. Further understanding will require accurate description of NAD(P)(H) metabolism, and genetically encoded fluorescent biosensors have recently become available for this purpose. Although these biosensors have begun to provide novel biological insights, their limitations must be considered and the information they provide appropriately interpreted. We provide a framework for understanding NAD(P)(H) metabolism and explore what fluorescent biosensors can, and cannot, tell us about plant biology, looking ahead to the pressing questions that could be answered with further development of these tools.

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.

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.

Recent Advances in Carbon and Nitrogen Metabolism in C3 Plants

C and N are the most important essential elements constituting organic compounds in plants. The shoots and roots depend on each other by exchanging C and N through the xylem and phloem transport systems. Complex mechanisms regulate C and N metabolism to optimize plant growth, agricultural crop production, and maintenance of the agroecosystem. In this paper, we cover the recent advances in understanding C and N metabolism, regulation, and transport in plants, as well as their underlying molecular mechanisms. Special emphasis is given to the mechanisms of starch metabolism in plastids and the changes in responses to environmental stress that were previously overlooked, since these changes provide an essential store of C that fuels plant metabolism and growth. We present general insights into the system biology approaches that have expanded our understanding of core biological questions related to C and N metabolism. Finally, this review synthesizes recent advances in our understanding of the trade-off concept that links C and N status to the plant's response to microorganisms.

Next-generation metabolic engineering approaches towards development of plant cell suspension cultures as specialized metabolite producing biofactories

Plant cell suspension culture (PCSC) has emerged as a viable technology to produce plant specialized metabolites (PSM). While Taxol® and ginsenoside are two examples of successfully commercialized PCSC-derived PSM, widespread utilization of the PCSC platform has yet to be realized primarily due to a lack of understanding of the molecular genetics of PSM biosynthesis. Recent advances in computational, molecular and synthetic biology tools provide the opportunity to rapidly characterize and harness the specialized metabolic potential of plants. Here, we discuss the prospects of integrating computational modeling, artificial intelligence, and precision genome editing (CRISPR/Cas and its variants) toolboxes to discover the genetic regulators of PSM. We also explore how synthetic biology can be applied to develop metabolically optimized PSM-producing native and heterologous PCSC systems. Taken together, this review provides an interdisciplinary approach to realize and link the potential of next-generation computational and molecular tools to convert PCSC into commercially viable PSM-producing biofactories.

Vacuolar sucrose homeostasis is critical for plant development, seed properties, and night-time survival in Arabidopsis

Most cellular sucrose is present in the cytosol and vacuoles of plant cells; however, little is known about the effect of this sucrose compartmentation on plant properties. Here, we examined the effects of altered intracellular sucrose compartmentation in Arabidopsis thaliana leaves by heterologously expressing the sugar beet (Beta vulgaris) vacuolar sucrose loader BvTST2.1 and by generating lines with reduced vacuolar invertase activity (amiR vi1-2). Heterologous expression of BvTST2.1 led to increased monosaccharide levels in leaves, whereas sucrose levels remained constant, indicating that vacuolar invertase activity in mesophyll vacuoles exceeds sucrose uptake. This notion was supported by analysis of tobacco (Nicotiana benthamiana) leaves transiently expressing BvTST2.1 and the invertase inhibitor NbVIF. However, sucrose levels were strongly elevated in leaf extracts from amiR vi1-2 lines, and experiments confirmed that sucrose accumulated in the corresponding vacuoles. The amiR vi1-2 lines exhibited impaired early development and reduced seed weight. When germinated in the dark, amiR vi1-2 seedlings were less able to convert sucrose into monosaccharides than the wild type. Cold temperatures strongly down-regulated both VI genes, but the amiR vi1-2 lines showed normal frost tolerance. These observations indicate that increased vacuolar sucrose levels fully compensate for the effects of low monosaccharide concentrations on frost tolerance.

Hierarchical and Dynamic Regulation of Defense-Responsive Specialized Metabolism by WRKY and MYB Transcription Factors

The plant kingdom produces hundreds of thousands of specialized bioactive metabolites, some with pharmaceutical and biotechnological importance. Their biosynthesis and function have been studied for decades, but comparatively less is known about how transcription factors with overlapping functions and contrasting regulatory activities coordinately control the dynamics and output of plant specialized metabolism. Here, we performed temporal studies on pathogen-infected intact host plants with perturbed transcription factors. We identified WRKY33 as the condition-dependent master regulator and MYB51 as the dual functional regulator in a hierarchical gene network likely responsible for the gene expression dynamics and metabolic fluxes in the camalexin and 4-hydroxy-indole-3-carbonylnitrile (4OH-ICN) pathways. This network may have also facilitated the regulatory capture of the newly evolved 4OH-ICN pathway in Arabidopsis thaliana by the more-conserved transcription factor MYB51. It has long been held that the plasticity of plant specialized metabolism and the canalization of development should be differently regulated; our findings imply a common hierarchical regulatory architecture orchestrated by transcription factors for specialized metabolism and development, making it an attractive target for metabolic engineering.

Leaf Energy Balance Requires Mitochondrial Respiration and Export of Chloroplast NADPH in the Light

Key aspects of leaf mitochondrial metabolism in the light remain unresolved. For example, there is debate about the relative importance of exporting reducing equivalents from mitochondria for the peroxisomal steps of photorespiration versus oxidation of NADH to generate ATP by oxidative phosphorylation. Here, we address this and explore energetic coupling between organelles in the light using a diel flux balance analysis model. The model included more than 600 reactions of central metabolism with full stoichiometric accounting of energy production and consumption. Different scenarios of energy availability (light intensity) and demand (source leaf versus a growing leaf) were considered, and the model was constrained by the nonlinear relationship between light and CO2 assimilation rate. The analysis demonstrated that the chloroplast can theoretically generate sufficient ATP to satisfy the energy requirements of the rest of the cell in addition to its own. However, this requires unrealistic high light use efficiency and, in practice, the availability of chloroplast-derived ATP is limited by chloroplast energy dissipation systems, such as nonphotochemical quenching, and the capacity of the chloroplast ATP export shuttles. Given these limitations, substantial mitochondrial ATP synthesis is required to fulfill cytosolic ATP requirements, with only minimal, or zero, export of mitochondrial reducing equivalents. The analysis also revealed the importance of exporting reducing equivalents from chloroplasts to sustain photorespiration. Hence, the chloroplast malate valve and triose phosphate-3-phosphoglycerate shuttle are predicted to have important metabolic roles, in addition to their more commonly discussed contribution to the avoidance of photooxidative stress.

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.

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.

Evolutionary Diversification of Primary Metabolism and Its Contribution to Plant Chemical Diversity

Plants produce a diverse array of lineage-specific specialized (secondary) metabolites, which are synthesized from primary metabolites. Plant specialized metabolites play crucial roles in plant adaptation as well as in human nutrition and medicine. Unlike well-documented diversification of plant specialized metabolic enzymes, primary metabolism that provides essential compounds for cellular homeostasis is under strong selection pressure and generally assumed to be conserved across the plant kingdom. Yet, some alterations in primary metabolic pathways have been reported in plants. The biosynthetic pathways of certain amino acids and lipids have been altered in specific plant lineages. Also, two alternative pathways exist in plants for synthesizing primary precursors of the two major classes of plant specialized metabolites, terpenoids and phenylpropanoids. Such primary metabolic diversities likely underlie major evolutionary changes in plant metabolism and chemical diversity by acting as enabling or associated traits for the evolution of specialized metabolic pathways.

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.

Recent advances and effective strategies in the discovery and applications of natural products

Natural products are the most representative form of conventional therapy as compared to any other traditional or alternative medicine systems.

Overcoming antibiotic resistance: Is siderophore Trojan horse conjugation an answer to evolving resistance in microbial pathogens?

Comparative study of siderophore biosynthesis pathway in pathogens provides potential targets for antibiotics and host drug delivery as a part of computationally feasible microbial therapy. Iron acquisition using siderophore models is an essential and well established model in all microorganisms and microbial infections a known to cause great havoc to both plant and animal. Rapid development of antibiotic resistance in bacterial as well as fungal pathogens has drawn us at a verge where one has to get rid of the traditional way of obstructing pathogen using single or multiple antibiotic/chemical inhibitors or drugs. 'Trojan horse' strategy is an answer to this imperative call where antibiotic are by far sneaked into the pathogenic cell via the siderophore receptors at cell and outer membrane. This antibiotic once gets inside, generates a 'black hole' scenario within the opportunistic pathogens via iron scarcity. For pathogens whose siderophore are not compatible to smuggle drug due to their complex conformation and stiff valence bonds, there is another approach. By means of the siderophore biosynthesis pathways, potential targets for inhibition of these siderophores in pathogenic bacteria could be achieved and thus control pathogenic virulence. Method to design artificial exogenous siderophores for pathogens that would compete and succeed the battle of intake is also covered with this review. These manipulated siderophore would enter pathogenic cell like any other siderophore but will not disperse iron due to which iron inadequacy and hence pathogens control be accomplished. The aim of this review is to offer strategies to overcome the microbial infections/pathogens using siderophore.

UV-B irradiation differentially regulates terpene synthases and terpene content of peach

Plants generate protective molecules in response to ultraviolet (UV) light. In laboratory experiments, 48 h UV-B irradiation of peach fruits and leaves reduced the flavour-related monoterpene linalool by 60%. No isoprene was detected, but other terpenoids increased significantly, including a threefold accumulation of the sesquiterpene (E,E)-α-farnesene, which was also increased by jasmonic acid treatment. RNA sequencing revealed altered transcript levels for two terpene synthases (TPSs): PpTPS1, a TPS-g subfamily member, decreased by 86% and PpTPS2, a TPS-b subfamily member, increased 80-fold. Heterologous expression in Escherichia coli and transient overexpression in tobacco and peach fruits showed PpTPS1 was localized in plastids and associated with production of linalool, while PpTPS2 was responsible for (E,E)-α-farnesene biosynthesis in the cytoplasm. Candidate regulatory genes for these responses were identified. Commercial peach production in Asia involves fruit bagging to maintain marketable yield and quality. TPS gene expression and volatile terpenoid production in field experiments, using bags transmitting high UV-B radiation, showed similar effects on peach volatiles to those from laboratory experiments. Bags transmitting less UV-B light ameliorated the reduction in the flavour volatile linalool, indicating that flavour components of peach fruits can be modulated by selecting an appropriate source of environmental screening material.

Engineering central metabolism - a grand challenge for plant biologists

The goal of increasing crop productivity and nutrient-use efficiency is being addressed by a number of ambitious research projects seeking to re-engineer photosynthetic biochemistry. Many of these projects will require the engineering of substantial changes in fluxes of central metabolism. However, as has been amply demonstrated in simpler systems such as microbes, central metabolism is extremely difficult to rationally engineer. This is because of multiple layers of regulation that operate to maintain metabolic steady state and because of the highly connected nature of central metabolism. In this review we discuss new approaches for metabolic engineering that have the potential to address these problems and dramatically improve the success with which we can rationally engineer central metabolism in plants. In particular, we advocate the adoption of an iterative 'design-build-test-learn' cycle using fast-to-transform model plants as test beds. This approach can be realised by coupling new molecular tools to incorporate multiple transgenes in nuclear and plastid genomes with computational modelling to design the engineering strategy and to understand the metabolic phenotype of the engineered organism. We also envisage that mutagenesis could be used to fine-tune the balance between the endogenous metabolic network and the introduced enzymes. Finally, we emphasise the importance of considering the plant as a whole system and not isolated organs: the greatest increase in crop productivity will be achieved if both source and sink metabolism are engineered.

Increasing ascorbate levels in crops to enhance human nutrition and plant abiotic stress tolerance

Ascorbate (or vitamin C) is an essential human micronutrient predominantly obtained from plants. In addition to preventing scurvy, it is now known to have broader roles in human health, for example as a cofactor for enzymes involved in epigenetic programming and as regulator of cellular iron uptake. Furthermore, ascorbate is the major antioxidant in plants and underpins many environmentally induced abiotic stress responses. Biotechnological approaches to enhance the ascorbate content of crops therefore have potential to improve both human health and abiotic stress tolerance of crops. Identifying the genetic basis of ascorbate variation between plant varieties and discovering how some 'super fruits' accumulate extremely high levels of ascorbate should reveal new ways to more effectively manipulate the production of ascorbate in crops.

Metabolic network modeling with model organisms

Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions.

Metabolic model of central carbon and energy metabolisms of growing Arabidopsis thaliana in relation to sucrose translocation

BACKGROUND

Sucrose translocation between plant tissues is crucial for growth, development and reproduction of plants. Systemic analysis of these metabolic and underlying regulatory processes allow a detailed understanding of carbon distribution within the plant and the formation of associated phenotypic traits. Sucrose translocation from 'source' tissues (e.g. mesophyll) to 'sink' tissues (e.g. root) is tightly bound to the proton gradient across the membranes. The plant sucrose transporters are grouped into efflux exporters (SWEET family) and proton-symport importers (SUC, STP families). To better understand regulation of sucrose export from source tissues and sucrose import into sink tissues, there is a need for a metabolic model that takes in account the tissue organisation of Arabidopsis thaliana with corresponding metabolic specificities of respective tissues in terms of sucrose and proton production/utilization. An ability of the model to operate under different light modes ('light' and 'dark') and correspondingly in different energy producing modes is particularly important in understanding regulatory modules.

RESULTS

Here, we describe a multi-compartmental model consisting of a mesophyll cell with plastid and mitochondrion, a phloem cell, as well as a root cell with mitochondrion. In this model, the phloem was considered as a non-growing transport compartment, the mesophyll compartment was considered as both autotrophic (growing on CO₂ under light) and heterotrophic (growing on starch in darkness), and the root was always considered as heterotrophic tissue dependent on sucrose supply from the mesophyll compartment. In total, the model includes 413 balanced compounds interconnected by 400 transformers. The structured metabolic model accounts for central carbon metabolism, photosynthesis, photorespiration, carbohydrate metabolism, energy and redox metabolisms, proton metabolism, biomass growth, nutrients uptake, proton gradient generation and sucrose translocation between tissues. Biochemical processes in the model were associated with gene-products (742 ORFs). Flux Balance Analysis (FBA) of the model resulted in balanced carbon, nitrogen, proton, energy and redox states under both light and dark conditions. The main H⁺-fluxes were reconstructed and their directions matched with proton-dependent sucrose translocation from 'source' to 'sink' under any light condition.

CONCLUSIONS

The model quantified the translocation of sucrose between plant tissues in association with an integral balance of protons, which in turn is defined by operational modes of the energy metabolism.

Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability

In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes.

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.

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.

Metabolic Architecture of the Cereal Grain and Its Relevance to Maximize Carbon Use Efficiency

Here, we have characterized the spatial heterogeneity of the cereal grain's metabolism and demonstrated how, by integrating a distinct set of metabolic strategies, the grain has evolved to become an almost perfect entity for carbon storage. In vivo imaging revealed light-induced cycles in assimilate supply toward the ear/grain of barley (Hordeum vulgare) and wheat (Triticum aestivum). In silico modeling predicted that, in the two grain storage organs (the endosperm and embryo), the light-induced shift in solute influx does cause adjustment in metabolic flux without changes in pathway utilization patterns. The enveloping, leaf-like pericarp, in contrast, shows major shifts in flux distribution (starch metabolism, photosynthesis, remobilization, and tricarboxylic acid cycle activity) allow to refix 79% of the CO2 released by the endosperm and embryo, allowing the grain to achieve an extraordinary high carbon conversion efficiency of 95%. Shading experiments demonstrated that ears are autonomously able to raise the influx of solutes in response to light, but with little effect on the steady-state levels of metabolites or transcripts or on the pattern of sugar distribution within the grain. The finding suggests the presence of a mechanism(s) able to ensure metabolic homeostasis in the face of short-term environmental fluctuation. The proposed multicomponent modeling approach is informative for predicting the metabolic effects of either an altered level of incident light or a momentary change in the supply of sucrose. It is therefore of potential value for assessing the impact of either breeding and/or biotechnological interventions aimed at increasing grain yield.

Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants

Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions.

Plant phenomics and the need for physiological phenotyping across scales to narrow the genotype-to-phenotype knowledge gap

Plants are affected by complex genome×environment×management interactions which determine phenotypic plasticity as a result of the variability of genetic components. Whereas great advances have been made in the cost-efficient and high-throughput analyses of genetic information and non-invasive phenotyping, the large-scale analyses of the underlying physiological mechanisms lag behind. The external phenotype is determined by the sum of the complex interactions of metabolic pathways and intracellular regulatory networks that is reflected in an internal, physiological, and biochemical phenotype. These various scales of dynamic physiological responses need to be considered, and genotyping and external phenotyping should be linked to the physiology at the cellular and tissue level. A high-dimensional physiological phenotyping across scales is needed that integrates the precise characterization of the internal phenotype into high-throughput phenotyping of whole plants and canopies. By this means, complex traits can be broken down into individual components of physiological traits. Since the higher resolution of physiological phenotyping by 'wet chemistry' is inherently limited in throughput, high-throughput non-invasive phenotyping needs to be validated and verified across scales to be used as proxy for the underlying processes. Armed with this interdisciplinary and multidimensional phenomics approach, plant physiology, non-invasive phenotyping, and functional genomics will complement each other, ultimately enabling the in silico assessment of responses under defined environments with advanced crop models. This will allow generation of robust physiological predictors also for complex traits to bridge the knowledge gap between genotype and phenotype for applications in breeding, precision farming, and basic research.

Mapping complex traits as a dynamic system

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a "system" in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states.

Crop yield: challenges from a metabolic perspective

Considering the dual use of plants, as bio-factories for foods and feedstock for bio-refining, along with a rising world population, the plant biotechnology field is currently facing a dramatic challenge to develop crops with higher yield. Furthermore, convergent studies predict that global changes in climate will influence crop productivity by modifying most yield-associated traits. Here, we review recent advances in the understanding of plant metabolism directly or indirectly impacting on yield and provide an update of the different pathways proposed as targets for metabolic engineering aiming to optimize source-sink relationships.