Contrasting nutrient-disease relationships: Potassium gradients in barley leaves have opposite effects on two fungal pathogens with different sensitivities to jasmonic acid.

Understanding the interactions between mineral nutrition and disease is essential for crop management. Our previous studies with Arabidopsis thaliana demonstrated that potassium (K) deprivation induced the biosynthesis of jasmonic acid (JA) and increased the plant's resistance to herbivorous insects. Here, we addressed the question of how tissue K affects the development of fungal pathogens and whether sensitivity of the pathogens to JA could play a role for the K-disease relationship in barley (Hordeum vulgare cv. Optic). We report that K-deprived barley plants showed increased leaf concentrations of JA and other oxylipins. Furthermore, a natural tip-to-base K-concentration gradient within leaves of K-sufficient plants was quantitatively mirrored by the transcript levels of JA-responsive genes. The local leaf tissue K concentrations affected the development of two economically important fungi in opposite ways, showing a positive correlation with powdery mildew (Blumeria graminis) and a negative correlation with leaf scald (Rhynchosporium commune) disease symptoms. B. graminis induced a JA response in the plant and was sensitive to methyl-JA treatment whereas R. commune initiated no JA response and was JA insensitive. Our study challenges the view that high K generally improves plant health and suggests that JA sensitivity of pathogens could be an important factor in determining the exact K-disease relationship.

Exploiting the Genetic Diversity of Maize Using a Combined Metabolomic, Enzyme Activity Profiling, and Metabolic Modeling Approach to Link Leaf Physiology to Kernel Yield.

A combined metabolomic, biochemical, fluxomic, and metabolic modeling approach was developed using 19 genetically distant maize (Zea mays) lines from Europe and America. Considerable differences were detected between the lines when leaf metabolic profiles and activities of the main enzymes involved in primary metabolism were compared. During grain filling, the leaf metabolic composition appeared to be a reliable marker, allowing a classification matching the genetic diversity of the lines. During the same period, there was a significant correlation between the genetic distance of the lines and the activities of enzymes involved in carbon metabolism, notably glycolysis. Although large differences were observed in terms of leaf metabolic fluxes, these variations were not tightly linked to the genome structure of the lines. Both correlation studies and metabolic network analyses allowed the description of a maize ideotype with a high grain yield potential. Such an ideotype is characterized by low accumulation of soluble amino acids and carbohydrates in the leaves and high activity of enzymes involved in the C4 photosynthetic pathway and in the biosynthesis of amino acids derived from glutamate. Chlorogenates appear to be important markers that can be used to select for maize lines that produce larger kernels.

Genetic variability of the phloem sap metabolite content of maize (Zea mays L.) during the kernel-filling period.

Using a metabolomic approach, we have quantified the metabolite composition of the phloem sap exudate of seventeen European and American lines of maize that had been previously classified into five main groups on the basis of molecular marker polymorphisms. In addition to sucrose, glutamate and aspartate, which are abundant in the phloem sap of many plant species, large quantities of aconitate and alanine were also found in the phloem sap exudates of maize. Genetic variability of the phloem sap composition was observed in the different maize lines, although there was no obvious relationship between the phloem sap composition and the five previously classified groups. However, following hierarchical clustering analysis there was a clear relationship between two of the subclusters of lines defined on the basis of the composition of the phloem sap exudate and the earliness of silking date. A comparison between the metabolite contents of the ear leaves and the phloem sap exudates of each genotype, revealed that the relative content of most of the carbon- and nitrogen-containing metabolites was similar. Correlation studies performed between the metabolite content of the phloem sap exudates and yield-related traits also revealed that for some carbohydrates such as arabitol and sucrose there was a negative or positive correlation with kernel yield and kernel weight respectively. A posititive correlation was also found between kernel number and soluble histidine.

Nitrogen-use efficiency in maize (Zea mays L.): from 'omics' studies to metabolic modelling.

In this review, we will present the latest developments in systems biology with particular emphasis on improving nitrogen-use efficiency (NUE) in crops such as maize and demonstrating the application of metabolic models. The review highlights the importance of improving NUE in crops and provides an overview of the transcriptome, proteome, and metabolome datasets available, focusing on a comprehensive understanding of nitrogen regulation. 'Omics' data are hard to interpret in the absence of metabolic flux information within genome-scale models. These models, when integrated with 'omics' data, can serve as a basis for generating predictions that focus and guide further experimental studies. By simulating different nitrogen (N) conditions at a pseudo-steady state, the reactions affecting NUE and additional gene regulations can be determined. Such models thus provide a framework for improving our understanding of the metabolic processes underlying the more efficient use of N-based fertilizers.

Analysis of the Root System Architecture of Arabidopsis Provides a Quantitative Readout of Crosstalk between Nutritional Signals.

As plant roots forage the soil for food and water, they translate a multifactorial input of environmental stimuli into a multifactorial developmental output that manifests itself as root system architecture (RSA). Our current understanding of the underlying regulatory network is limited because root responses have traditionally been studied separately for individual nutrient deficiencies. In this study, we quantified 13 RSA parameters of Arabidopsis thaliana in 32 binary combinations of N, P, K, S, and light. Analysis of variance showed that each RSA parameter was determined by a typical pattern of environmental signals and their interactions. P caused the most important single-nutrient effects, while N-effects were strongly light dependent. Effects of K and S occurred mostly through nutrient interactions in paired or multiple combinations. Several RSA parameters were selected for further analysis through mutant phenotyping, which revealed combinations of transporters, receptors, and kinases acting as signaling modules in K-N interactions. Furthermore, nutrient response profiles of individual RSA features across NPK combinations could be assigned to transcriptionally coregulated clusters of nutrient-responsive genes in the roots and to ionome patterns in the shoots. The obtained data set provides a quantitative basis for understanding how plants integrate multiple nutritional stimuli into complex developmental programs.

Characterization of a NADH-dependent glutamate dehydrogenase mutant of Arabidopsis demonstrates the key role of this enzyme in root carbon and nitrogen metabolism.

The role of NADH-dependent glutamate dehydrogenase (GDH) was investigated by studying the physiological impact of a complete lack of enzyme activity in an Arabidopsis thaliana plant deficient in three genes encoding the enzyme. This study was conducted following the discovery that a third GDH gene is expressed in the mitochondria of the root companion cells, where all three active GDH enzyme proteins were shown to be present. A gdh1-2-3 triple mutant was constructed and exhibited major differences from the wild type in gene transcription and metabolite concentrations, and these differences appeared to originate in the roots. By placing the gdh triple mutant under continuous darkness for several days and comparing it to the wild type, the evidence strongly suggested that the main physiological function of NADH-GDH is to provide 2-oxoglutarate for the tricarboxylic acid cycle. The differences in key metabolites of the tricarboxylic acid cycle in the triple mutant versus the wild type indicated that, through metabolic processes operating mainly in roots, there was a strong impact on amino acid accumulation, in particular alanine, γ-aminobutyrate, and aspartate in both roots and leaves. These results are discussed in relation to the possible signaling and physiological functions of the enzyme at the interface of carbon and nitrogen metabolism.

The use of metabolomics integrated with transcriptomic and proteomic studies for identifying key steps involved in the control of nitrogen metabolism in crops such as maize.

Linking plant phenotype to gene and protein expression and also to metabolite synthesis and accumulation is one of the main challenges for improving agricultural production worldwide. Such a challenge is particularly relevant to crop nitrogen use efficiency (NUE). Here, the differences in leaf gene transcript, protein, and metabolite accumulation in maize subjected to long-term nitrogen (N)-deficient growth conditions at two important stages of plant development have been studied. The impact of N deficiency was examined at the transcriptomic, proteomic, and metabolomic levels. It was found that a number of key plant biological functions were either up- or down-regulated when N was limiting, including major alterations to photosynthesis, carbon (C) metabolism, and, to a lesser extent, downstream metabolic pathways. It was also found that the impact of the N deficiency stress resembled the response of plants to a number of other biotic and abiotic stresses, in terms of transcript, protein, and metabolite accumulation. The genetic and metabolic alterations were different during the N assimilation and the grain-filling period, indicating that plant development is an important component for identifying the key elements involved in the control of plant NUE. It was also found that integration of the three 'omics' studies is not straightforward, since different levels of regulation seem to occur in a stepwise manner from gene expression to metabolite accumulation. The potential use of these 'omics' studies is discussed with a view to improve our understanding of whole plant nitrogen economics, which should have applications in breeding and agronomy.

From the soil to the seeds: the long journey of nitrate in plants.

Under temperate climates and in cultivated soils, nitrate is the most important source of nitrogen (N) available for crops and, before its reduction and assimilation into amino acids, must enter the root cells and then move in the whole plant. The aim of this review is to provide an overall picture of the numerous membrane proteins that achieve these processes by being localized in different compartments and in different tissues. Nitrate transporters (NRT) from the NRT1 and NRT2 families ensure the capacity of root cells to take up nitrate, through high- and low-affinity systems (HATS and LATS) depending on nitrate concentrations in the soil solution. Other members of the NRT1 family are involved subsequently in loading and unloading of nitrate to and from the xylem vessels, allowing its distribution to aerial organs or its remobilization from old leaves. Once in the cell, nitrate can be stored in the vacuole by passing through the tonoplast, a step that involves chloride channels (CLC) or a NRT2 member. Finally, with the exception of one NRT1 member, the transport of nitrite towards the chloroplast is still largely unknown. All these fluxes are controlled by key factors, the 'major tour operators' like the internal nutritional status of the plant but also by external abiotic factors.

Potassium deficiency induces the biosynthesis of oxylipins and glucosinolates in Arabidopsis thaliana.

BACKGROUND: Mineral fertilization and pest control are essential and costly requirements for modern crop production. The two measures go hand in hand because plant mineral status affects plant susceptibility to pests and vice versa. Nutrient deficiency triggers specific responses in plants that optimize nutrient acquisition and reprogram metabolism. K-deficient plants illustrate these strategies by inducing high-affinity K-uptake and adjusting primary metabolism. Whether and how K deficient plants also alter their secondary metabolism for nutrient management and defense is not known. RESULTS: Here we show that K-deficient plants contain higher levels of the phytohormone jasmonic acid (JA), hydroxy-12-oxo-octadecadienoic acids (HODs) and 12-oxo-phytodienoic acid (OPDA) than K-sufficient plants. Up-regulation of the 13-LOX pathway in response to low K was evident in increased transcript levels of several biosynthetic enzymes. Indole and aliphatic glucosinolates accumulated in response to K-deficiency in a manner that was respectively dependent or independent on signaling through Coronatine-Insensitive 1 (COI1). Transcript and glucosinolate profiles of K-deficient plants resembled those of herbivore attacked plants. CONCLUSIONS: Based on our results we propose that under K-deficiency plants produce oxylipins and glucosinolates to enhance their defense potential against herbivorous insects and create reversible storage for excess S and N.

Coronatine-insensitive 1 (COI1) mediates transcriptional responses of Arabidopsis thaliana to external potassium supply.

The ability to adjust growth and development to the availability of mineral nutrients in the soil is an essential life skill of plants but the underlying signaling pathways are poorly understood. In Arabidopsis thaliana, shortage of potassium (K) induces a number of genes related to the phytohormone jasmonic acid (JA). Using comparative microarray analysis of wild-type and coi1-16 mutant plants, we classified transcriptional responses to K with respect to their dependence on COI1, a central component of oxylipin signaling. Expression profiles obtained in a short-term experiment clearly distinguished between COI1-dependent and COI1-independent K-responsive genes, and identified both known and novel targets of JA-COI1-signaling. During long-term K-deficiency, coi-16 mutants displayed de novo responses covering similar functions as COI1-targets except for defense. A putative role of JA for enhancing the defense potential of K-deficient plants was further supported by the observation that plants grown on low K were less damaged by thrips than plants grown with sufficient K.

EZ-Rhizo software: the gateway to root architecture analysis.

Plants are sessile organisms that have to cope with the available nutritional resources and environmental constraints in the place where they germinate. To fully exploit their nearby resources, they have evolved a highly plastic and responsive root system. Adaptations to limited nutrients include a wide range of specific root responses, e.g., the emergence of new root types, root branching or specific growth of lateral roots. These root system architecture (RSA) features are of utmost importance when investigating the underlying mechanisms by forward, reverse or quantitative genetic approaches. The EZ-Rhizo software was developed to facilitate such root measurements in a fast, simple and accurate way. The performances of EZ-Rhizo in providing about 20 primary and derived RSA parameters were illustrated by looking at natural variability across 23 Arabidopsis accessions. The different RSA profiles obtained from plants grown in favorable condition illustrated the wide reservoir of natural genetic resources underlying specific features of root growth. This diversity was used here to correlate the RSA genetic variability with growth, development and environmental properties of accession origins.

Effects of N, P, K and S on metabolism: new knowledge gained from multi-level analysis.

Deficiency of mineral nutrients such as nitrate, phosphate, potassium and sulphate strongly affects the type and amount of metabolites produced by crops with knock-on effects on nutritional quality of the crop, its processing properties and disease resistance. Owing to the multitude of biochemical reactions underlying metabolism and the high degree of connectivity between biochemical pathways, predicting the output of the metabolic network in response to a change in nutrient input is an enormous challenge. Recently several studies have taken a systemic approach monitoring the response of plants to withdrawal and/or re-supply of mineral nutrients at the level of transcripts, metabolites and enzyme activities. These multi-level studies have provided important new insight into how plants re-prioritise different metabolic pathways during nutrient shortage and how they integrate metabolism with growth. On the basis of the obtained information we can formulate specific hypotheses about the causal relationships between changes in individual transcripts, proteins and metabolites.

Multilevel analysis of primary metabolism provides new insights into the role of potassium nutrition for glycolysis and nitrogen assimilation in Arabidopsis roots.

Potassium (K) is required in large quantities by growing crops, but faced with high fertilizer prices, farmers often neglect K application in favor of nitrogen and phosphorus. As a result, large areas of farmland are now depleted of K. K deficiency affects the metabolite content of crops with negative consequences for nutritional quality, mechanical stability, and pathogen/pest resistance. Known functions of K in solute transport, protein synthesis, and enzyme activation point to a close relationship between K and metabolism, but it is unclear which of these are the most critical ones and should be targeted in biotechnological efforts to improve K usage efficiency. To identify metabolic targets and signaling components of K stress, we adopted a multilevel approach combining transcript profiles with enzyme activities and metabolite profiles of Arabidopsis (Arabidopsis thaliana) plants subjected to low K and K resupply. Roots and shoots were analyzed separately. Our results show that regulation of enzymes at the level of transcripts and proteins is likely to play an important role in plant adaptation to K deficiency by (1) maintaining carbon flux into amino acids and proteins, (2) decreasing negative metabolic charge, and (3) increasing the nitrogen-carbon ratio in amino acids. However, changes in transcripts and enzyme activities do not explain the strong and reversible depletion of pyruvate and accumulation of sugars observed in the roots of low-K plants. We propose that the primary cause of metabolic disorders in low-K plants resides in the direct inhibition of pyruvate kinase activity by low cytoplasmic K in root cells.

EZ-Rhizo: integrated software for the fast and accurate measurement of root system architecture.

The root system is essential for the growth and development of plants. In addition to anchoring the plant in the ground, it is the site of uptake of water and minerals from the soil. Plant root systems show an astonishing plasticity in their architecture, which allows for optimal exploitation of diverse soil structures and conditions. The signalling pathways that enable plants to sense and respond to changes in soil conditions, in particular nutrient supply, are a topic of intensive research, and root system architecture (RSA) is an important and obvious phenotypic output. At present, the quantitative description of RSA is labour intensive and time consuming, even using the currently available software, and the lack of a fast RSA measuring tool hampers forward and quantitative genetics studies. Here, we describe EZ-Rhizo: a Windows-integrated and semi-automated computer program designed to detect and quantify multiple RSA parameters from plants growing on a solid support medium. The method is non-invasive, enabling the user to follow RSA development over time. We have successfully applied EZ-Rhizo to evaluate natural variation in RSA across 23 Arabidopsis thaliana accessions, and have identified new RSA determinants as a basis for future quantitative trait locus (QTL) analysis.

Adjustment of growth and central metabolism to a mild but sustained nitrogen-limitation in Arabidopsis.

We have established a simple soil-based experimental system that allows a small and sustained restriction of growth of Arabidopsis by low nitrogen (N). Plants were grown in a large volume of a peat-vermiculite mix that contained very low levels of inorganic N. As a control, inorganic N was added in solid form to the peat-vermiculite mix, or plants were grown in conventional nutrient-rich solids. The low N growth regime led to a sustained 20% decrease of the relative growth rate over a period of 2 weeks, resulting in a two- to threefold decrease in biomass in 35- to 40-day-old plants. Plants in the low N regime contained lower levels of nitrate, lower nitrate reductase activity, lower levels of malate, fumarate and other organic acids and slightly higher levels of starch, as expected from published studies of N-limited plants. However, their rosette protein content was unaltered, and total and many individual amino acid levels increased compared with N-replete plants. This metabolic phenotype reveals that Arabidopsis responds adaptively to low N by decreasing the rate of growth, while maintaining the overall protein content, and maintaining or even increasing the levels of many amino acids.

The effect of potassium nutrition on pest and disease resistance in plants.

Providing a fast growing world population with sufficient food while preserving ecological and energy resources of our planet is one of the biggest challenges in this century. Optimized management of chemical fertilizers and pesticides will be essential for achieving sustainability of intensive farming and requires both empirical data from field trials and advanced fundamental understanding of the molecular processes controlling plant growth. Genes involved in plant responses to nutrient deficiency and pathogen/herbivore attack have been identified, but we are lacking information about the cross-talk between signalling pathways when plants are exposed to a combination of abiotic and biotic stress factors. The focus of this review is on the relationship between the potassium status of plants and their susceptibility to pathogens and herbivorous insects. We combine field evidence on potassium-disease interaction with existing knowledge on metabolic and physiological factors that could explain such interaction, and present new data on metabolite profiles and hormonal pathways from the model plant Arabidopsis thaliana. The latter provides evidence that facilitated entry and development of pathogens or insects in(to) potassium-deficient plants as a result of physical and metabolic changes is counteracted by an increased defence. A genetic approach should now be applied to establish a causal relationship between disease susceptibility on the one hand and individual enzymatic and signal components on the other. Once identified, these can be used to design agricultural strategies that support the nutritional status of the crops while exploiting their inherent potential for defence.

Vector analysis as a fast and easy method to compare gene expression responses between different experimental backgrounds.

BACKGROUND: Gene expression studies increasingly compare expression responses between different experimental backgrounds (genetic, physiological, or phylogenetic). By focusing on dynamic responses rather than a direct comparison of static expression levels, this type of study allows a finer dissection of primary and secondary regulatory effects in the various backgrounds. Usually, results of such experiments are presented in the form of Venn diagrams, which are intuitive and visually appealing, but lack a statistical foundation. RESULTS: Here we introduce Vector Analysis (VA) as a simple, yet principled, approach to comparing expression responses in different experimental backgrounds. VA enables the automatic assignment of genes to response prototypes and provides statistical significance estimates to eliminate spurious response patterns. The application of VA to a real dataset, comparing nutrient starvation responses in wild type and mutant Arabidopsis plants, reveals that consistent patterns of expression behavior are present in the data and are reliably detected by the algorithm. CONCLUSION: Vector analysis is a flexible, easy-to-use technique to compare gene expression patterns in different experimental backgrounds. It compares favorably with the classical Venn diagram approach and can be implemented manually using spreadsheets, such as Excel, or automatically by using the supplied software.

The potassium-dependent transcriptome of Arabidopsis reveals a prominent role of jasmonic acid in nutrient signaling.

Full genome microarrays were used to assess transcriptional responses of Arabidopsis seedlings to changing external supply of the essential macronutrient potassium (K(+)). Rank product statistics and iterative group analysis were employed to identify differentially regulated genes and statistically significant coregulated sets of functionally related genes. The most prominent response was found for genes linked to the phytohormone jasmonic acid (JA). Transcript levels for the JA biosynthetic enzymes lipoxygenase, allene oxide synthase, and allene oxide cyclase were strongly increased during K(+) starvation and quickly decreased after K(+) resupply. A large number of well-known JA responsive genes showed the same expression profile, including genes involved in storage of amino acids (VSP), glucosinolate production (CYP79), polyamine biosynthesis (ADC2), and defense (PDF1.2). Our findings highlight a novel role of JA in nutrient signaling and stress management through a variety of physiological processes such as nutrient storage, recycling, and reallocation. Other highly significant K(+)-responsive genes discovered in our study encoded cell wall proteins (e.g. extensins and arabinogalactans) and ion transporters (e.g. the high-affinity K(+) transporter HAK5 and the nitrate transporter NRT2.1) as well as proteins with a putative role in Ca(2+) signaling (e.g. calmodulins). On the basis of our results, we propose candidate genes involved in K(+) perception and signaling as well as a network of molecular processes underlying plant adaptation to K(+) deficiency.