Impact of the carbon and nitrogen supply on relationships and connectivity between metabolism and biomass in a broad panel of Arabidopsis accessions

From dawn 'til dusk: daytime progression regulates primary and secondary metabolism in Cannabis glandular trichomes

Cannabis sativa L. glandular trichomes synthesize large amounts of secondary metabolites, predominantly cannabinoids and terpenoids. The associated demand for carbon and energy makes glandular trichomes strong sink tissues with indications that their secondary metabolism is coupled to the availability of photoassimilates. Many metabolites show diurnal patterns of flux, but it is unknown whether cannabinoids and terpenoids are regulated by time of day. We quantified cannabinoids, terpenoids, and the glandular trichome proteome over a 12 h light period in flowers of 'Hindu Kush', a high-tetrahydrocannabinol cultivar. Major cannabinoids changed significantly over the course of the day, resulting in an increase in total measured cannabinoids. Major terpenoids also changed, with sesquiterpenes generally decreasing with day progression. While monoterpenes generally did not decrease, the second most abundant, α-pinene, increased. The glandular trichome proteome changed the most within the first 6 h of the day, and analysis of differentially abundant proteins indicated up-regulation of primary metabolism. Surprisingly, key cannabinoid biosynthetic enzymes decreased with daytime progression despite increases in cannabinoid content, which indicates that daytime increases of photoassimilates are the main driver of cannabinoid regulation. This first reporting of variability of cannabinoid and terpenoid biosynthesis over the course of the day has implications for Cannabis research and production.

Carbon and nitrogen signaling regulate FLOWERING LOCUS C and impact flowering time in Arabidopsis

The timing of flowering in plants is modulated by both carbon (C) and nitrogen (N) signaling pathways. In a previous study, we established a pivotal role of the sucrose-signaling trehalose 6-phosphate pathway in regulating flowering under N-limited short-day conditions. In this work, we show that both wild-type Arabidopsis (Arabidopsis thaliana) plants grown under N-limited conditions and knock-down plants of TREHALOSE PHOSPHATE SYNTHASE 1 induce FLOWERING LOCUS C (FLC) expression, a well-known floral repressor associated with vernalization. When exposed to an extended period of cold, a flc mutant fails to respond to N availability and flowers at the same time under N-limited and full-nutrition conditions. Our data suggest that SUCROSE NON-FERMENTING 1 RELATED KINASE 1-dependent trehalose 6-phosphate-mediated C signaling and a mechanism downstream of N signaling (likely involving NIN-LIKE PROTEIN 7) impact the expression of FLC. Collectively, our data underscore the existence of a multi-factor regulatory system in which the C and N signaling pathways jointly govern the regulation of flowering in plants.

Do storage reserves contribute to plant phenotypic plasticity?

The widespread colonization of diverse habitats by plants is attributed to their ability to adapt to changing environments through environmental phenotypic plasticity. This flexibility, particularly in carbon turnover, allows plants to adjust their physiology and development. Plants store carbon reserves as a metabolic strategy to overcome adversity, with a variety of isozymes evolving to enhance metabolic plasticity. Among these isoforms, some with entirely new functions have emerged, involved in novel metabolic pathways for carbon storage. Here, we discuss the role of these carbon stores, their impact on plant plasticity, methods by which such metabolic plasticity can be analyzed, and evolutionary aspects that have led to well-characterized as well as less well-known molecular mechanisms underlying carbon storage.

Natural variation in response to combined water and nitrogen deficiencies in Arabidopsis

Understanding plant responses to individual stresses does not mean that we understand real-world situations, where stresses usually combine and interact. These interactions arise at different levels, from stress exposure to the molecular networks of the stress response. Here, we built an in-depth multiomic description of plant responses to mild water (W) and nitrogen (N) limitations, either individually or combined, among 5 genetically different Arabidopsis (Arabidopsis thaliana) accessions. We highlight the different dynamics in stress response through integrative traits such as rosette growth and the physiological status of the plants. We also used transcriptomic and metabolomic profiling during a stage when the plant response was stabilized to determine the wide diversity in stress-induced changes among accessions, highlighting the limited reality of a "universal" stress response. The main effect of the W × N interaction was an attenuation of the N-deficiency syndrome when combined with mild drought, but to a variable extent depending on the accession. Other traits subject to W × N interactions are often accession specific. Multiomic analyses identified a subset of transcript-metabolite clusters that are critical to stress responses but essentially variable according to the genotype factor. Including intraspecific diversity in our descriptions of plant stress response places our findings in perspective.

Predicting plasticity of rosette growth and metabolic fluxes in Arabidopsis thaliana

Plants can rapidly mitigate the effects of suboptimal growth environments by phenotypic plasticity of fitness-traits. While genetic variation for phenotypic plasticity offers the means for breeding climate-resilient crop lines, accurate genomic prediction models for plasticity of fitness-related traits are still lacking. Here, we employed condition- and accession-specific metabolic models for 67 Arabidopsis thaliana accessions to dissect and predict plasticity of rosette growth to changes in nitrogen availability. We showed that specific reactions in photorespiration, linking carbon and nitrogen metabolism, as well as key pathways of central carbon metabolism exhibited substantial genetic variation for flux plasticity. We also demonstrated that, in comparison with a genomic prediction model for fresh weight (FW), genomic prediction of growth plasticity improves the predictability of FW under low nitrogen by 58.9% and by additional 15.4% when further integrating data on plasticity of metabolic fluxes. Therefore, the combination of metabolic and statistical modeling provides a stepping stone in understanding the molecular mechanisms and improving the predictability of plasticity for fitness-related traits.

Identification of gene function based on models capturing natural variability of Arabidopsis thaliana lipid metabolism

Lipids play fundamental roles in regulating agronomically important traits. Advances in plant lipid metabolism have until recently largely been based on reductionist approaches, although modulation of its components can have system-wide effects. However, existing models of plant lipid metabolism provide lumped representations, hindering detailed study of component modulation. Here, we present the Plant Lipid Module (PLM) which provides a mechanistic description of lipid metabolism in the Arabidopsis thaliana rosette. We demonstrate that the PLM can be readily integrated in models of A. thaliana Col-0 metabolism, yielding accurate predictions (83%) of single lethal knock-outs and 75% concordance between measured transcript and predicted flux changes under extended darkness. Genome-wide associations with fluxes obtained by integrating the PLM in diel condition- and accession-specific models identify up to 65 candidate genes modulating A. thaliana lipid metabolism. Using mutant lines, we validate up to 40% of the candidates, paving the way for identification of metabolic gene function based on models capturing natural variability in metabolism.

A Bayesian model for genomic prediction using metabolic networks

Motivation

Genomic prediction is now an essential technique in breeding and medicine, and it is interesting to see how omics data can be used to improve prediction accuracy. Precedent work proposed a metabolic network-based method in biomass prediction of Arabidopsis; however, the method consists of multiple steps that possibly degrade prediction accuracy.

Results

We proposed a Bayesian model that integrates all steps and jointly infers all fluxes of reactions related to biomass production. The proposed model showed higher accuracies than methods compared both in simulated and real data. The findings support the previous excellent idea that metabolic network information can be used for prediction.

Availability and implementation

All R and stan scripts to reproduce the results of this study are available at https://github.com/Onogi/MetabolicModeling.

The Metabolic Profile of Young, Watered Chickpea Plants Can Be Used as a Biomarker to Predict Seed Number under Terminal Drought

Chickpea is the second-most-cultivated legume globally, with India and Australia being the two largest producers. In both of these locations, the crop is sown on residual summer soil moisture and left to grow on progressively depleting water content, finally maturing under terminal drought conditions. The metabolic profile of plants is commonly, correlatively associated with performance or stress responses, e.g., the accumulation of osmoprotective metabolites during cold stress. In animals and humans, metabolites are also prognostically used to predict the likelihood of an event (usually a disease) before it occurs, e.g., blood cholesterol and heart disease. We sought to discover metabolic biomarkers in chickpea that could be used to predict grain yield traits under terminal drought, from the leaf tissue of young, watered, healthy plants. The metabolic profile (GC-MS and enzyme assays) of field-grown chickpea leaves was analysed over two growing seasons, and then predictive modelling was applied to associate the most strongly correlated metabolites with the final seed number plant^-1. Pinitol (negatively), sucrose (negatively) and GABA (positively) were significantly correlated with seed number in both years of study. The feature selection algorithm of the model selected a larger range of metabolites including carbohydrates, sugar alcohols and GABA. The correlation between the predicted seed number and actual seed number was R² adj = 0.62, demonstrating that the metabolic profile could be used to predict a complex trait with a high degree of accuracy. A previously unknown association between D-pinitol and hundred-kernel weight was also discovered and may provide a single metabolic marker with which to predict large seeded chickpea varieties from new crosses. The use of metabolic biomarkers could be used by breeders to identify superior-performing genotypes before maturity is reached.

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

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

Natural variation in the long-distance transport of nutrients and photoassimilates in response to N availability

Phloem and xylem tissues are necessary for the allocation of nutrients and photoassimilates. However, how the long-distance transport of carbon (C) and nitrogen (N) is coordinated with the central metabolism is largely unknown. To better understand how the genetic and environmental factors influence C and N transport, we analysed the metabolite profiles of phloem exudates and xylem saps of five Arabidopsis thaliana accessions grown in low or non-limiting N supply. We observed that xylem saps were composed of 46 or 56% carbohydrates, 27 or 45% amino acids, and 5 or 13% organic acids in low or non-limiting N supply, respectively. In contrast, phloem exudates were composed of 76 or 86% carbohydrates, 7 or 18% amino acids, and 5 or 6% organic acids. Variation in N supply impacted amino acid, organic acid and sugar contents. When comparing low N and non-limiting N, the most striking differences were variations of glutamine, aspartate, and succinate abundance in the xylem saps and citrate and fumarate abundance in phloem exudates. In addition, we observed a substantial variation of metabolite content between genotypes, particularly under high N. The content of several organic acids, such as malate, citrate, fumarate, and succinate was affected by the genotype alone or by the interaction between genotype and N supply. This study confirmed that the response of the transport of nutrients in the phloem and the xylem to N availability is associated with the regulation of the central metabolism and could be an adaptive trait.

Nitrogen fertilization stimulates nitrogen assimilation and modifies nitrogen partitioning in the spring shoot leaves of citrus (Citrus reticulata Blanco) trees

The spring shoot leaves are important sites of nitrogen (N) metabolism in citrus trees. Understanding the physiological and metabolic response of the spring shoot leaves under varying N fertilization is fundamental to the fertilization management in citrus orchards. Thus, the processes affecting N composition, the activities of N metabolism related enzymes, and the expression of relevant genes were explored in spring shoot leaves under four N levels (0, 207, 275, 413 g N tree^-1 y^-1, as N0, N207, N275, N413). The results showed that, compared with N0, N275 significantly increased total N by 24.81%, which was mainly attributed to enhancement of structural N by 30.92%, free amino acid N by 40.91% and nitrate N by 41.33%. The relative expression of nitrate reductase (NR) and glutamate dehydrogenase (GDH) under N275 increased by 19.32% and 73.48%, respectively, compared with that under N0 treatment. Compared with N0 treatment, the NR transcription level under N275 treatment increased by 381%. The relative transcription levels of NADP-GDH and GDH1 also increased with increasing N fertilization. However, compared with that under N275, the relative transcription of GDH2 under N413 treatment was inhibited. Therefore, the transcript abundance of NR, NADP-GDH,GDH1 and GDH2 affected the activities of NR and GDH and thereby contributed to the regulation of N composition in the leaves. In addition, the activities of glutamine synthetase and nitrite reductase were largely unaffected or even declined in the N207, N275 and N413 treatments compared with the N0. This study elucidated the mechanism of primary N metabolism and partitioning in citrus leaves and provided a theoretical basis for N management in citrus orchards.

The metabolomic landscape of rice heterosis highlights pathway biomarkers for predicting complex phenotypes

Understanding the molecular mechanisms underlying complex phenotypes requires systematic analyses of complicated metabolic networks and contributes to improvements in the breeding efficiency of staple cereal crops and diagnostic accuracy for human diseases. Here, we selected rice (Oryza sativa) heterosis as a complex phenotype and investigated the mechanisms of both vegetative and reproductive traits using an untargeted metabolomics strategy. Heterosis-associated analytes were identified, and the overlapping analytes were shown to underlie the association patterns for six agronomic traits. The heterosis-associated analytes of four yield components and plant height collectively contributed to yield heterosis, and the degree of contribution differed among the five traits. We performed dysregulated network analyses of the high- and low-better parent heterosis hybrids and found multiple types of metabolic pathways involved in heterosis. The metabolite levels of the significantly enriched pathways (especially those from amino acid and carbohydrate metabolism) were predictive of yield heterosis (area under the curve = 0.907 with 10 features), and the predictability of these pathway biomarkers was validated with hybrids across environments and populations. Our findings elucidate the metabolomic landscape of rice heterosis and highlight the potential application of pathway biomarkers in achieving accurate predictions of complex phenotypes.

Plasticity of rosette size in response to nitrogen availability is controlled by an RCC1-family protein

Nitrogen (N) is fundamental to plant growth, development and yield. Genes underlying N utilization and assimilation are well-characterized, but mechanisms underpinning plasticity of different phenotypes in response to N remain elusive. Here, using Arabidopsis thaliana accessions, we dissected the genetic architecture of plasticity in early and late rosette diameter, flowering time and yield, in response to three levels of N in the soil. Furthermore, we found that the plasticity in levels of primary metabolites were related with the plasticities of the studied traits. Genome-wide association analysis identified three significant associations for phenotypic plasticity, one for early rosette diameter and two for flowering time. We confirmed that the gene At1g19880, hereafter named as PLASTICITY OF ROSETTE TO NITROGEN 1 (PROTON1), encoding for a regulator of chromatin condensation 1 (RCC1) family protein, conferred plasticity of rosette diameter in response to N. Treatment of PROTON1 T-DNA line with salt implied that the reduced plasticity of early rosette diameter was not a general growth response to stress. We further showed that plasticities of growth and flowering-related traits differed between environmental cues, indicating decoupled genetic programs regulating these traits. Our findings provide a prospective to identify genes that stabilize performance under fluctuating environments.

Metabolic Profile Discriminates and Predicts Arabidopsis Susceptibility to Virus under Field Conditions

As obligatory parasites, plant viruses alter host cellular metabolism. There is a lack of information on the variability of virus-induced metabolic responses among genetically diverse plants in a natural context with daily changing conditions. To decipher the metabolic landscape of plant-virus interactions in a natural setting, twenty-six and ten accessions of Arabidopsis thaliana were inoculated with Turnip mosaic virus (TuMV), in two field experiments over 2 years. The accessions were measured for viral accumulation, above-ground biomass, targeted and untargeted metabolic profiles. The phenotypes of the accessions ranged from susceptibility to resistance. Susceptible and resistant accessions were shown to have different metabolic routes after inoculation. Susceptible genotypes accumulate primary and secondary metabolites upon infection, at the cost of hindered growth. Twenty-one metabolic signatures significantly accumulated in resistant accessions whereas they maintained their growth as mock-inoculated plants without biomass penalty. Metabolic content was demonstrated to discriminate and be highly predictive of the susceptibility of inoculated Arabidopsis. This study is the first to describe the metabolic landscape of plant-virus interactions in a natural setting and its predictive link to susceptibility. It provides new insights on plant-virus interactions. In this undomesticated species and in ecologically realistic conditions, growth and resistance are in a permanent conversation.

Integrated transcript and metabolite profiling reveals coordination between biomass size and nitrogen metabolism in Arabidopsis F1 hybrids

Heterosis refers to the improved agronomic performance of F₁ hybrids relative to their parents. Although this phenomenon is widely employed to increase biomass, yield, and stress tolerance of plants, the underlying molecular mechanisms remain unclear. To dissect the metabolic fluctuations derived from genomic and/or environmental differences contributing to the improved biomass of F₁ hybrids relative to their parents, we optimized the growth condition for Arabidopsis thaliana F₁ hybrids and their parents. Modest but statistically significant increase in the biomass of F₁ hybrids was observed. Plant samples grown under the optimized condition were also utilized for integrated omics analysis to capture specific changes in the F₁ hybrids. Metabolite profiling of F₁ hybrids and parent plants was performed using gas chromatography-mass spectrometry. Among the detected 237 metabolites, 2-oxoglutarate (2-OG) and malate levels were lower and the level of aspartate was higher in the F₁ hybrids than in each parent. In addition, microarray analysis revealed that there were 44 up-regulated and 12 down-regulated genes with more than 1.5-fold changes in expression levels in the F₁ hybrid compared to each parent. Gene ontology (GO) analyses indicated that genes up-regulated in the F₁ hybrids were largely related to organic nitrogen (N) process. Quantitative PCR verified that glutamine synthetase 2 (AtGLN2) was upregulated in the F₁ hybrids, while other genes encoding enzymes in the GS-GOGAT cycle showed no significant differences between the hybrid and parent lines. These results suggested the existence of metabolic regulation that coordinates biomass and N metabolism involving AtGLN2 in F₁ hybrids.

Improved photosynthetic characteristics correlated with enhanced biomass in a heterotic F1 hybrid of maize (Zea mays L.)

Heterosis is a phenomenon wherein F₁ hybrid often displays phenotypic superiority and surpasses its parents in terms of growth and agronomic traits. Investigations on the physiological and biochemical properties of the heterotic F₁ hybrid are important to uncover the mechanisms underlying heterosis in plants. In the present study, the photosynthetic capacity of a heterotic F₁ hybrid of Zea mays L. (DHM 117) that exhibited a higher growth rate and increased biomass was compared with its parental inbreds at vegetative and reproductive stages in the field during 2017 and 2018. The net photosynthetic rate (P_n), stomatal conductance (g_s), transpiration rate (E) as well as foliar carbohydrates were higher in F₁ hybrid than parental inbreds at vegetative and reproductive stages. An increase in total chlorophyll content along with better chlorophyll a fluorescence characteristics including effective quantum yield of photosystem II (ΔF/F_m'), maximum quantum yield of PSII (F_v/F_m), photochemical quenching (q_p) and decreased non-photochemical quenching (NPQ) was observed in F₁ hybrid than the parental inbreds. Further, the expression of potential genes related to C₄ photosynthesis was considerably upregulated in F₁ hybrid than the parental inbreds during vegetative and reproductive stages. Moreover, the F₁ hybrid exhibited distinct heterosis in yield with 63% and 62% increase relative to parental inbreds during 2017 and 2018. We conclude that improved photosynthetic efficiency associated with increased foliar carbohydrates could have contributed to higher growth rate, biomass and yield in the F₁ hybrid.

Developmental stage-specific metabolite signatures in Arabidopsis thaliana under optimal and mild nitrogen limitation

Metabolites influence flowering time, and thus are among the major determinants of yield. Despite the reported role of trehalose 6-phosphate and nitrate signaling on the transition from the vegetative to the reproductive phase, little is known about other metabolites contributing and responding to developmental phase changes. To increase our understanding which metabolic traits change throughout development in Arabidopsis thaliana and to identify metabolic markers for the vegetative and reproductive phases, especially among individual amino acids (AA), we profiled metabolites of plants grown in optimal (ON) and limited nitrogen (N) (LN) conditions, the latter providing a mild but consistent limitation of N. We found that although LN plants adapt their growth to a decreased level of N, their metabolite profiles are strongly distinct from ON plant profiles, with N as the driving factor for the observed differences. We demonstrate that the vegetative and the reproductive phase are not only marked by growth parameters such as biomass and rosette area, but also by specific metabolite signatures including specific single AA. In summary, we identified N-dependent and -independent indicators manifesting developmental stages, indicating that the plant's metabolic status also reports on the developmental phases.

Identification of Putative Interactors of Arabidopsis Sugar Transporters

Hexoses and disaccharides are the key carbon sources for essentially all physiological processes across kingdoms. In plants, sucrose, and in some cases raffinose and stachyose, are transported from the site of synthesis in leaves, the sources, to all other organs that depend on import, the sinks. Sugars also play key roles in interactions with beneficial and pathogenic microbes. Sugar transport is mediated by transport proteins that fall into super-families. Sugar transporter (ST) activity is tuned at different levels, including transcriptional and posttranslational levels. Understanding the ST interactome has a great potential to uncover important players in biologically and physiologically relevant processes, including, but not limited to Arabidopsis thaliana. Here, we combined ST interactions and coexpression studies to identify potentially relevant interaction networks.

The Arabidopsis Transcription Factor CDF3 Is Involved in Nitrogen Responses and Improves Nitrogen Use Efficiency in Tomato

Nitrate is an essential macronutrient and a signal molecule that regulates the expression of multiple genes involved in plant growth and development. Here, we describe the participation of Arabidopsis DNA binding with one finger (DOF) transcription factor CDF3 in nitrate responses and shows that CDF3 gene is induced under nitrate starvation. Moreover, knockout cdf3 mutant plants exhibit nitrate-dependent lateral and primary root modifications, whereas CDF3 overexpression plants show increased biomass and enhanced root development under both nitrogen poor and rich conditions. Expression analyses of 35S::CDF3 lines reveled that CDF3 regulates the expression of an important set of nitrate responsive genes including, glutamine synthetase-1, glutamate synthase-2, nitrate reductase-1, and nitrate transporters NRT2.1, NRT2.4, and NRT2.5 as well as carbon assimilation genes like PK1 and PEPC1 in response to N availability. Consistently, metabolite profiling disclosed that the total amount of key N metabolites like glutamate, glutamine, and asparagine were higher in CDF3-overexpressing plants, but lower in cdf3-1 in N limiting conditions. Moreover, overexpression of CDF3 in tomato increased N accumulation and yield efficiency under both optimum and limiting N supply. These results highlight CDF3 as an important regulatory factor for the nitrate response, and its potential for improving N use efficiency in crops.

Multi-gene metabolic engineering of tomato plants results in increased fruit yield up to 23%

The capacity to assimilate carbon and nitrogen, to transport the resultant sugars and amino acids to sink tissues, and to convert the incoming sugars and amino acids into storage compounds in the sink tissues, are key determinants of crop yield. Given that all of these processes have the potential to co-limit growth, multiple genetic interventions in source and sink tissues, plus transport processes may be necessary to reach the full yield potential of a crop. We used biolistic combinatorial co-transformation (up to 20 transgenes) for increasing C and N flows with the purpose of increasing tomato fruit yield. We observed an increased fruit yield of up to 23%. To better explore the reconfiguration of metabolic networks in these transformants, we generated a dataset encompassing physiological parameters, gene expression and metabolite profiling on plants grown under glasshouse or polytunnel conditions. A Sparse Partial Least Squares regression model was able to explain the combination of genes that contributed to increased fruit yield. This combinatorial study of multiple transgenes targeting primary metabolism thus offers opportunities to probe the genetic basis of metabolic and phenotypic variation, providing insight into the difficulties in choosing the correct combination of targets for engineering increased fruit yield.

Integrated analysis on biochemical profiling and transcriptome revealed nitrogen-driven difference in accumulation of saponins in a medicinal plant Panax notoginseng

The medicinal plant Panax notoginseng is considered a promising source of secondary metabolites due to its saponins. However, there are relatively few studies on the response of saponins to nitrogen (N) availability and the mechanisms underlying the N-driven regulation of saponins. Saponins content and saponins -related genes were analyzed in roots of P. notoginseng grown under low N (LN), moderate N (MN) and high N (HN). Saponins was obviously increased in LN individuals with a reduction in β-glucosidase activity. LN facilitated root architecture and N uptake rate. Compared with the LN individuals, 2872 and 1122 genes were incorporated into as differently expressed genes (DEGs) in the MN and HN individuals. Clustering and enrichment showed that DEGs related to "carbohydrate biosynthesis", "plant hormone signal transduction", "terpenoid backbone biosynthesis", "sesquiterpenoid and triterpenoid biosynthesis" were enriched. The up-regulation of some saponins-related genes and microelement transporters was found in LN plants. Whereas the expression of IPT3, AHK4 and GS2 in LN plants fell far short of that in HN ones. Anyways, LN-induced accumulation of C-based metabolites as saponins might derive from the interaction between N and phytohormones in processing of N acquisition, and HN-induced reduction of saponins might be result from an increase in the form of β-glucosidase activity and N-dependent cytokinins (CKs) biosynthesis.

Integrating molecular markers into metabolic models improves genomic selection for Arabidopsis growth

The current trends of crop yield improvements are not expected to meet the projected rise in demand. Genomic selection uses molecular markers and machine learning to identify superior genotypes with improved traits, such as growth. Plant growth directly depends on rates of metabolic reactions which transform nutrients into the building blocks of biomass. Here, we predict growth of Arabidopsis thaliana accessions by employing genomic prediction of reaction rates estimated from accession-specific metabolic models. We demonstrate that, comparing to classical genomic selection on the available data sets for 67 accessions, our approach improves the prediction accuracy for growth within and across nitrogen environments by 32.6% and 51.4%, respectively, and from optimal nitrogen to low carbon environment by 50.4%. Therefore, integration of molecular markers into metabolic models offers an approach to predict traits directly related to metabolism, and its usefulness in breeding can be examined by gathering matching datasets in crops.

An increase in genomic selection (GS) accuracy can accelerate genetic gain by shortening the breeding cycles. Here, the authors introduce a network-based GS method that uses metabolic models and improves the prediction accuracy of Arabidopsis growth within and across environments.

Biomarkers for grain yield stability in rice under drought stress

Crop yield stability requires an attenuation of the reduction of yield losses caused by environmental stresses such as drought. Using a combination of metabolomics and high-throughput colorimetric assays, we analysed central metabolism and oxidative stress status in the flag leaf of 292 indica rice (Oryza sativa) accessions. Plants were grown in the field and were, at the reproductive stage, exposed to either well-watered or drought conditions to identify the metabolic processes associated with drought-induced grain yield loss. Photorespiration, protein degradation, and nitrogen recycling were the main processes involved in the drought-induced leaf metabolic reprogramming. Molecular markers of drought tolerance and sensitivity in terms of grain yield were identified using a multivariate model based on the values of the metabolites and enzyme activities across the population. The model highlights the central role of the ascorbate-glutathione cycle, particularly dehydroascorbate reductase, in minimizing drought-induced grain yield loss. In contrast, malondialdehyde was an accurate biomarker for grain yield loss, suggesting that drought-induced lipid peroxidation is the major constraint under these conditions. These findings highlight new breeding targets for improved rice grain yield stability under drought.

Cytochrome respiration pathway and sulphur metabolism sustain stress tolerance to low temperature in the Antarctic species Colobanthus quitensis

Understanding the strategies employed by plant species that live in extreme environments offers the possibility to discover stress tolerance mechanisms. We studied the physiological, antioxidant and metabolic responses to three temperature conditions (4, 15, and 23°C) of Colobanthus quitensis (CQ), one of the only two native vascular species in Antarctica. We also employed Dianthus chinensis (DC), to assess the effects of the treatments in a non-Antarctic species from the same family. Using fused LASSO modelling, we associated physiological and biochemical antioxidant responses with primary metabolism. This approach allowed us to highlight the metabolic pathways driving the response specific to CQ. Low temperature imposed dramatic reductions in photosynthesis (up to 88%) but not in respiration (sustaining rates of 3.0-4.2 μmol CO₂  m^-2  s^-1 ) in CQ, and no change in the physiological stress parameters was found. Its notable antioxidant capacity and mitochondrial cytochrome respiratory activity (20 and two times higher than DC, respectively), which ensure ATP production even at low temperature, was significantly associated with sulphur-containing metabolites and polyamines. Our findings potentially open new biotechnological opportunities regarding the role of antioxidant compounds and respiratory mechanisms associated with sulphur metabolism in stress tolerance strategies to low temperature.

Association analysis of phenotypic and metabolomic changes in Arabidopsis accessions and their F1 hybrids affected by different photoperiod and sucrose supply

Photoperiod and sucrose (Suc) assimilation play important roles in the regulation of plant growth and development. However, it remains unclear how natural variation of plants could contribute to metabolic changes under various growth conditions. Here, we investigated the developmental and metabolomic responses of two natural accessions of Arabidopsis thaliana, Columbia (Col) and C24, and their reciprocal F₁ hybrids grown under four carbon source regimens, i.e., two different photoperiods and the presence or absence of exogenous Suc supply. The effect of exogenous Suc clearly appeared in the growth of Col and the F₁ hybrid but not in C24, whereas long-day conditions had significant positive effects on the growth of all lines. Comparative metabolite profiling of Col, C24, and the F₁ hybrid revealed that changes in metabolite levels, particularly sugars, were highly dependent on genotype-specific responses rather than growth conditions. The presence of Suc led to over-accumulation of seven metabolites, including four sugars, a polyamine, and two amino acids in C24, whereas no such accumulation was observed in the profiles of Col and the F₁ hybrid. Thus, the comparative metabolite profiling revealed that the two parental lines of the hybrid show a distinct difference in sugar metabolism.

Selenium downregulates auxin and ethylene biosynthesis in rice seedlings to modify primary metabolism and root architecture

Selenium modulates the formation of primary and lateral roots through alterations in auxin and ethylene, leading to new patterns of root architecture in rice seedlings. Selenium (Se) at low concentrations can control root growth through interaction with hormone biosynthesis. Auxin and ethylene have been shown to control the root architecture, with most of the information obtained from the eudicots such Arabidopsis and Nicotiana tabacum. Here, we presented the effects of Se on auxin and ethylene pathways and examined their impact on primary metabolism and root system architecture in rice (Oryza sativa L.) seedlings. Se treatment increased elongation of primary root, but decreased the number and length of lateral roots. Se led to decreased expression of genes associated with the biosynthesis of auxin and ethylene, concomitantly with reduced production of these hormones by the roots. Moreover, Se decreased the abundance of transcripts encoding auxin transport proteins. Indole-3-acetic acid (IAA) treatment overrode the repressive effect of Se on lateral root growth. The ethylene synthesis inhibitor L-α-(2-aminoethoxyvinyl)-glycine (AVG) increased elongation of primary root, whereas the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC) resulted in the opposite effect. Soluble sugars accumulate in roots of rice seedlings under Se treatment. Thus, Se modulates the formation of primary and lateral roots through alterations in auxin and ethylene, leading to new patterns of root architecture in rice seedlings.

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 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.

Response of the Circadian Clock and Diel Starch Turnover to One Day of Low Light or Low CO2

Diel starch turnover responds rapidly to changes in the light regime. We investigated if these responses require changes in the temporal dynamics of the circadian clock. Arabidopsis (Arabidopsis thaliana) was grown in a 12-h photoperiod for 19 d, shifted to three different reduced light levels or to low CO₂ for one light period, and returned to growth conditions. The treatments produced widespread changes in clock transcript abundance. However, almost all of the changes were restricted to extreme treatments that led to carbon starvation and were small compared to the magnitude of the circadian oscillation. Changes included repression of EARLY FLOWERNG 4, slower decay of dusk components, and a slight phase delay at the next dawn, possibly due to abrogated Evening Complex function and sustained expression of PHYTOCHROME INTERACTING FACTORs and REVEILLEs during the night. Mobilization of starch in the night occurred in a linear manner and was paced to dawn, both in moderate treatments that did not alter clock transcripts and in extreme treatments that led to severe carbon starvation. We conclude that pacing of starch mobilization to dawn does not require retrograde carbon signaling to the transcriptional clock. On the following day, growth decreased, sugars rose, and starch accumulation was stimulated in low-light-treated plants compared to controls. This adaptive response was marked after moderate treatments and occurred independently of changes in the transcriptional clock. It is probably a time-delayed response to low-C signaling in the preceding 24-h cycle, possibly including changes in PHYTOCHROME INTERACTING FACTOR and REVEILLE expression.

Nonlinear phenotypic variation uncovers the emergence of heterosis in Arabidopsis thaliana

Heterosis describes the phenotypic superiority of hybrids over their parents in traits related to agronomic performance and fitness. Understanding and predicting nonadditive inheritance such as heterosis is crucial for evolutionary biology as well as for plant and animal breeding. However, the physiological bases of heterosis remain debated. Moreover, empirical data in various species have shown that diverse genetic and molecular mechanisms are likely to explain heterosis, making it difficult to predict its emergence and amplitude from parental genotypes alone. In this study, we examined a model of physiological dominance initially proposed by Sewall Wright to explain the nonadditive inheritance of traits like metabolic fluxes at the cellular level. We evaluated Wright's model for two fitness-related traits at the whole-plant level, growth rate and fruit number, using 450 hybrids derived from crosses among natural accessions of A. thaliana. We found that allometric relationships between traits constrain phenotypic variation in a nonlinear and similar manner in hybrids and accessions. These allometric relationships behave predictably, explaining up to 75% of heterosis amplitude, while genetic distance among parents at best explains 7%. Thus, our findings are consistent with Wright's model of physiological dominance and suggest that the emergence of heterosis on plant performance is an intrinsic property of nonlinear relationships between traits. Furthermore, our study highlights the potential of a geometric approach of phenotypic relationships for predicting heterosis of major components of crop productivity and yield.

Metabolite profiles reveal interspecific variation in operation of the Calvin-Benson cycle in both C4 and C3 plants

Low atmospheric CO2 in recent geological time led to the evolution of carbon-concentrating mechanisms (CCMs) such as C4 photosynthesis in >65 terrestrial plant lineages. We know little about the impact of low CO2 on the Calvin-Benson cycle (CBC) in C3 species that did not evolve CCMs, representing >90% of terrestrial plant species. Metabolite profiling provides a top-down strategy to investigate the operational balance in a pathway. We profiled CBC intermediates in a panel of C4 (Zea mays, Setaria viridis, Flaveria bidentis, and F. trinervia) and C3 species (Oryza sativa, Triticium aestivum, Arabidopsis thaliana, Nicotiana tabacum, and Manihot esculenta). Principal component analysis revealed differences between C4 and C3 species that were driven by many metabolites, including lower ribulose 1,5-bisphosphate in C4 species. Strikingly, there was also considerable variation between C3 species. This was partly due to different chlorophyll and protein contents, but mainly to differences in relative levels of metabolites. Correlation analysis indicated that one contributory factor was the balance between fructose-1,6-bisphosphatase, sedoheptulose-1,7-bisphosphatase, phosphoribulokinase, and Rubisco. Our results point to the CBC having experienced different evolutionary trajectories in C3 species since the ancestors of modern plant lineages diverged. They underline the need to understand CBC operation in a wide range of species.

Effect of nitrogen supply on nitrogen metabolism in the citrus cultivar 'Huangguogan'

Nitrogen metabolism in citrus has received increased attention due to its effects on plant growth and productivity. However, little is known about the effects of nitrogen fertilization on nitrogen metabolism in young trees of citrus cultivar ‘Huangguogan’ (Citrus reticulata × Citrus sinensis). Here, genes encoding nitrate reductase (NR), nitrite reductase (NiR), glutamine synthetase (GS), glutamate dehydrogenase (GDH), and asparagine synthetase (AS), represented as HgNR, HgNiR, HgGS, HgGDH, and HgAS, respectively, were cloned from Huangguogan. Deduced protein sequences were analyzed and proteins were confirmed to be localized in their respective cellular organelles. Moreover, pot-cultured ‘Huangguogan’ seedlings were fertilized with 0 (N₁), 1.36 (N₂), 1.81 (N₃), 2.26 (N₄), or 2.72 (N₅) kg N/year, for 12 months. Enzyme activity and enzyme-gene expression were studied in roots, leaves, and fruits at different stages. Finally, the effects of N application rate on root activity, leaf N, soluble protein, yield, and fruit quality at the ripening stage were measured. The results showed that: 1) HgNR, HgNiR, HgGDH, and HgAS gene products were found mainly in the cytoplasm and plasma membrane, while HgGS gene product was found mainly in cytoplasm and mitochondria. 2) Gene expression and enzyme activity differed among plant organs. As the root is in permanent direct contact with the soil we suggest that root gene expression and enzyme activity can be used as reference to determine N application rate. 3) Yield, fruit quality, enzyme activity, and enzyme-related gene expression were considerably lower at low than at high-N supply. However, they were all inhibited by excess nitrogen (i.e., 2.72 kg/year). Therefore, we recommend 1.81 kg N/year as the optimal N application rate for young ‘Huangguogan’ trees.

Arabidopsis Natural Accessions Display Adaptations in Inflorescence Growth and Vascular Anatomy to Withstand High Salinity during Reproductive Growth

Plant responses to abiotic stresses entail adaptive processes that integrate both physiological and developmental cues. However, the adaptive traits that are involved in the responses to a high soil salinity during reproductive growth are still poorly studied. To identify new clues, we studied the halophyte, Thellungiella salsuginea, and three Arabidopsis accessions, known as tolerant or salt-sensitive. We focused on the quantitative traits associated with the stem growth, sugar content, and anatomy of the plants subjected to the salt treatment, with and without a three-day acclimation, applied during the reproductive stage. The stem growth of Thellungiella salsuginea was not affected by the salt stress. By contrast, salt affected all of the Arabidopsis accessions, with a natural variation in the effect of the salt on growth, sugar content, and stem anatomy. In response to the high salinity, irregular xylem vessels were observed, independently of the accession's tolerance to salt treatment, while the diameter of the largest xylem vessels was reduced in the tolerant accessions. The stem height, growth rate, hexoses-to-sucrose ratio, and phloem-to-xylem ratio also varied, in association with both the genotype and its tolerance to salt stress. Our findings indicate that several quantitative traits for salt tolerance are associated with the control of inflorescence growth and the adjustment of the phloem-to-xylem ratio.

Computational aspects underlying genome to phenome analysis in plants

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features.

Ultraviolet radiation modulates C:N stoichiometry and biomass allocation in Fagus sylvatica saplings cultivated under elevated CO2 concentration

Under the conditions of ongoing climate change, terrestrial ecosystems will be simultaneously exposed to a permanent rise in atmospheric CO₂ concentration and increasing variability of such environmental factors as temperature, precipitation, and UV radiation. This will result in numerous interactions. The interactive effects caused by exposure to such multiple environmental factors are not yet well understood. We tested the hypotheses that enhanced UV radiation reduces the stimulatory effect of elevated CO₂ concentration on plant biomass production and that it alters biomass allocation in broadleaved European beech (Fagus sylvatica L.) saplings. Our results after 2 years of exposure confirmed interactive effects of CO₂ concentration and UV radiation on biomass production, and particularly on biomass allocation to roots and aboveground biomass. The strongest stimulatory effect of elevated CO₂ on aboveground biomass and roots was found under ambient UV radiation, while both low and high UV doses reduced this stimulation. Nitrogen content in the roots and the distribution of nitrogen among leaves and roots were also significantly affected by interaction of CO₂ concentration and UV radiation. The observed changes in leaf and root C:N stoichiometry were associated with altered morphological traits, and particularly with a change in the proportion of fine roots. As the biomass allocation and especially the proportion of fine roots can play an important role in effective water and nutrient use and acclimation to future climates, it is essential to obtain a deeper understanding of the links between C:N stoichiometry and biomass accumulation.

A role for ecophysiology in the 'omics' era

Plant Ecophysiology is the study on how Plant Physiology is modulated by the environment. This discipline could have benefited greatly from the development of the different 'omic' technologies (from genomics to metabolomics). Instead, the overall impression is that ecophysiology and 'omics' have developed mostly independent each other. Here we provide a literature analysis over the past 20 years which fully confirms this view. Then, we review a few examples of studies in which ecophysiology and 'omics' studies have combined to different extents to illustrate the potential benefits from their mutualistic interaction. In addition, we debate on the possibilities of working with plants other than Arabidopsis, which is illustrated with some examples of fascinating plants from extreme environments of the world, what we call the 'sherplants'. Finally, we raise a call to both communities (ecophysiology and 'omics') to integrate these disciplines to enter an 'ecophysiolomics era' to maximize our understanding about plant mechanisms from a multidisciplinary approach.

Lateral root growth in Arabidopsis is controlled by short and long distance signaling through the LRR RLKs XIP1/CEPR1 and CEPR2

Plants rely on lateral roots to explore their soil environment and to maximize their uptake of essential minerals and water. Here we present evidence that the receptor kinases XIP1/CEPR1 and CEPR2 regulate both the initiation of lateral root primordia and emergence of lateral roots locally in the root, while also controlling lateral root extension in response to shoot-derived sucrose in Arabidopsis plants. In addition, mutation of both of these receptors prevents seedlings from responding to sucrose in the media, resulting in longer lateral roots. These results, combined with previous data, establish XIP1/CEPR1 and CEPR2-dependent roles in short- and long-distance pathways regulating different stages of lateral root growth.

Dynamics of metabolic responses to periods of combined heat and drought in Arabidopsis thaliana under ambient and elevated atmospheric CO2

As a consequence of global change processes, plants will increasingly be challenged by extreme climatic events, against a background of elevated atmospheric CO2. We analysed responses of Arabidopsis thaliana to periods of a combination of elevated heat and water deficit at ambient and elevated CO2 in order to gain mechanistic insights regarding changes in primary metabolism. Metabolic changes induced by extremes of climate are dynamic and specific to different classes of molecules. Concentrations of soluble sugars and amino acids increased transiently after short (4-d) exposure to heat and drought, and readjusted to control levels under prolonged (8-d) stress. In contrast, fatty acids showed persistent changes during the stress period. Elevated CO2 reduced the impact of stress on sugar and amino acid metabolism, but not on fatty acids. Integrating metabolite data with transcriptome results revealed that some of the metabolic changes were regulated at the transcriptional level. Multivariate analyses grouped metabolites on the basis of stress exposure time, indicating specificity in metabolic responses to short and prolonged stress. Taken together, the results indicate that dynamic metabolic reprograming plays an important role in plant acclimation to climatic extremes. The extent of such metabolic adjustments is less under high CO2, further pointing towards the role of high CO2 in stress mitigation.

Nitrogen supply influences photosynthesis establishment along the sugarcane leaf

Nitrogen (N) is a major component of the photosynthetic apparatus and is widely used as a fertilizer in crops. However, to the best of our knowledge, the dynamic of photosynthesis establishment due to differential N supply in the bioenergy crop sugarcane has not been reported to date. To address this question, we evaluated physiological and metabolic alterations along the sugarcane leaf in two contrasting genotypes, responsive (R) and nonresponsive (NR), grown under high- and low-N conditions. We found that the N supply and the responsiveness of the genotype determined the degree of senescence, the carboxylation process mediated by phosphoenolpyruvate carboxylase (PEPcase) and differential accumulation of soluble sugars. The metabolite profiles indicated that the NR genotype had a higher respiration rate in the youngest tissues after exposure to high N. We observed elevated levels of metabolites related to photosynthesis in almost all leaf segments from the R genotype under high-N conditions, suggesting that N supply and the ability to respond to N influenced photosynthesis. Therefore, we observed that N influence on photosynthesis and other pathways is dependent on the genotype and the leaf region.

Interactive Effects of CO2 Concentration and Water Regime on Stable Isotope Signatures, Nitrogen Assimilation and Growth in Sweet Pepper

Sweet pepper is among the most widely cultivated horticultural crops in the Mediterranean basin, being frequently grown hydroponically under cover in combination with CO2 fertilization and water conditions ranging from optimal to suboptimal. The aim of this study is to develop a simple model, based on the analysis of plant stable isotopes in their natural abundance, gas exchange traits and N concentration, to assess sweet pepper growth. Plants were grown in a growth chamber for near 6 weeks. Two [CO2] (400 and 800 μmol mol-1), three water regimes (control and mild and moderate water stress) and four genotypes were assayed. For each combination of genotype, [CO2] and water regime five plants were evaluated. Water stress applied caused significant decreases in water potential, net assimilation, stomatal conductance, intercellular to atmospheric [CO2], and significant increases in water use efficiency, leaf chlorophyll content and carbon isotope composition, while the relative water content, the osmotic potential and the content of anthocyanins did change not under stress compared to control conditions support this statement. Nevertheless, water regime affects plant growth via nitrogen assimilation, which is associated with the transpiration stream, particularly at high [CO2], while the lower N concentration caused by rising [CO2] is not associated with stomatal closure. The stable isotope composition of carbon, oxygen, and nitrogen (δ13C, δ18O, and δ15N) in plant matter are affected not only by water regime but also by rising [CO2]. Thus, δ18O increased probably as response to decreases in transpiration, while the increase in δ15N may reflect not only a lower stomatal conductance but a higher nitrogen demand in leaves or shifts in nitrogen metabolism associated with decreases in photorespiration. The way that δ13C explains differences in plant growth across water regimes within a given [CO2], seems to be mediated through its direct relationship with N accumulation in leaves. The changes in the profile and amount of amino acids caused by water stress and high [CO2] support this conclusion. However, the results do not support the use of δ18O as an indicator of the effect of water regime on plant growth.

Integrative field scale phenotyping for investigating metabolic components of water stress within a vineyard

BACKGROUND

There is currently a high requirement for field phenotyping methodologies/technologies to determine quantitative traits related to crop yield and plant stress responses under field conditions.

METHODS

We employed an unmanned aerial vehicle equipped with a thermal camera as a high-throughput phenotyping platform to obtain canopy level data of the vines under three irrigation treatments. High-resolution imagery (< 2.5 cm/pixel) was employed to estimate the canopy conductance (gc ) via the leaf energy balance model. In parallel, physiological stress measurements at leaf and stem level as well as leaf sampling for primary and secondary metabolome analysis were performed.

RESULTS

Aerial gc correlated significantly with leaf stomatal conductance (gs ) and stem sap flow, benchmarking the quality of our remote sensing technique. Metabolome profiles were subsequently linked with gc and gs via partial least square modelling. By this approach malate and flavonols, which have previously been implicated to play a role in stomatal function under controlled greenhouse conditions within model species, were demonstrated to also be relevant in field conditions.

CONCLUSIONS

We propose an integrative methodology combining metabolomics, organ-level physiology and UAV-based remote sensing of the whole canopy responses to water stress within a vineyard. Finally, we discuss the general utility of this integrative methodology for broad field phenotyping.

Genome-Wide Association Mapping Reveals That Specific and Pleiotropic Regulatory Mechanisms Fine-Tune Central Metabolism and Growth in Arabidopsis

Central metabolism is a coordinated network that is regulated at multiple levels by resource availability and by environmental and developmental cues. Its genetic architecture has been investigated by mapping metabolite quantitative trait loci (QTL). A more direct approach is to identify enzyme activity QTL, which distinguishes between cis-QTL in structural genes encoding enzymes and regulatory trans-QTL. Using genome-wide association studies, we mapped QTL for 24 enzyme activities, nine metabolites, three structural components, and biomass in Arabidopsis thaliana We detected strong cis-QTL for five enzyme activities. A cis-QTL for UDP-glucose pyrophosphorylase activity in the UGP1 promoter is maintained through balancing selection. Variation in acid invertase activity reflects multiple evolutionary events in the promoter and coding region of VAC-INVcis-QTL were also detected for ADP-glucose pyrophosphorylase, fumarase, and phosphoglucose isomerase activity. We detected many trans-QTL, including transcription factors, E3 ligases, protein targeting components, and protein kinases, and validated some by knockout analysis. trans-QTL are more frequent but tend to have smaller individual effects than cis-QTL. We detected many colocalized QTL, including a multitrait QTL on chromosome 4 that affects six enzyme activities, three metabolites, protein, and biomass. These traits are coordinately modified by different ACCELERATED CELL DEATH6 alleles, revealing a trade-off between metabolism and defense against biotic stress.

Growth rate correlates negatively with protein turnover in Arabidopsis accessions

Previous studies with Arabidopsis accessions revealed that biomass correlates negatively to dusk starch content and total protein, and positively to the maximum activities of enzymes in photosynthesis. We hypothesized that large accessions have lower ribosome abundance and lower rates of protein synthesis, and that this is compensated by lower rates of protein degradation. This would increase growth efficiency and allow more investment in photosynthetic machinery. We analysed ribosome abundance and polysome loading in 19 accessions, modelled the rates of protein synthesis and compared them with the observed rate of growth. Large accessions contained less ribosomes than small accessions, due mainly to cytosolic ribosome abundance falling at night in large accessions. The modelled rates of protein synthesis resembled those required for growth in large accessions, but were up to 30% in excess in small accessions. We then employed ¹³ CO₂ pulse-chase labelling to measure the rates of protein synthesis and degradation in 13 accessions. Small accessions had a slightly higher rate of protein synthesis and much higher rates of protein degradation than large accessions. Protein turnover was negligible in large accessions but equivalent to up to 30% of synthesised protein day^-1 in small accessions. We discuss to what extent the decrease in growth in small accessions can be quantitatively explained by known costs of protein turnover and what factors may lead to the altered diurnal dynamics and increase of ribosome abundance in small accessions, and propose that there is a trade-off between protein turnover and maximisation of growth rate.

Deficient glutamate biosynthesis triggers a concerted upregulation of ribosomal protein genes in Arabidopsis

Biomass production requires the coordination between growth and metabolism. In a large-scale screen for mutants affected in leaf morphology, we isolated the orbiculata1 (orb1) mutants, which exhibit a pale green phenotype and reduced growth. The combination of map-based cloning and next-generation sequencing allowed us to establish that ORB1 encodes the GLUTAMATE SYNTHASE 1 (GLU1) enzyme, also known as FERREDOXIN-DEPENDENT GLUTAMINE OXOGLUTARATE AMINOTRANSFERASE 1 (Fd-GOGAT1). We performed an RNA-seq analysis to identify global gene expression changes in the orb1–3 mutant. We found altered expression levels of genes encoding enzymes involved in nitrogen assimilation and amino acid biosynthesis, such as glutamine synthetases, asparagine synthetases and glutamate dehydrogenases, showing that the expression of these genes depends on the levels of glutamine and/or glutamate. In addition, we observed a concerted upregulation of genes encoding subunits of the cytosolic ribosome. A gene ontology (GO) analysis of the differentially expressed genes between Ler and orb1–3 showed that the most enriched GO terms were ‘translation’, ‘cytosolic ribosome’ and ‘structural constituent of ribosome’. The upregulation of ribosome-related functions might reflect an attempt to keep protein synthesis at optimal levels even when the pool of glutamate is reduced.

Predicting future biomass yield in Miscanthus using the carbohydrate metabolic profile as a biomarker

In perennial energy crop breeding programmes, it can take several years before a mature yield is reached when potential new varieties can be scored. Modern plant breeding technologies have focussed on molecular markers, but for many crop species, this technology is unavailable. Therefore, prematurity predictors of harvestable yield would accelerate the release of new varieties. Metabolic biomarkers are routinely used in medicine, but they have been largely overlooked as predictive tools in plant science. We aimed to identify biomarkers of productivity in the bioenergy crop, Miscanthus, that could be used prognostically to predict future yields. This study identified a metabolic profile reflecting productivity in Miscanthus by correlating the summer carbohydrate composition of multiple genotypes with final yield 6 months later. Consistent and strong, significant correlations were observed between carbohydrate metrics and biomass traits at two separate field sites over 2 years. Machine-learning feature selection was used to optimize carbohydrate metrics for support vector regression models, which were able to predict interyear biomass traits with a correlation (R) of >0.67 between predicted and actual values. To identify a causal basis for the relationships between the glycome profile and biomass, a 13C-labelling experiment compared carbohydrate partitioning between high- and low-yielding genotypes. A lower yielding and slower growing genotype partitioned a greater percentage of the 13C pulse into starch compared to a faster growing genotype where a greater percentage was located in the structural biomass. These results supported a link between plant performance and carbon flow through two rival pathways (starch vs. sucrose), with higher yielding plants exhibiting greater partitioning into structural biomass, via sucrose metabolism, rather than starch. Our results demonstrate that the plant metabolome can be used prognostically to anticipate future yields and this is a method that could be used to accelerate selection in perennial energy crop breeding programmes.

Mass spectrometry as a quantitative tool in plant metabolomics

Metabolomics is a research field used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include the analysis of a wide range of chemical species with very diverse physico-chemical properties, and therefore powerful analytical tools are required for the separation, characterization and quantification of this vast compound diversity present in plant matrices. In this review, challenges in the use of mass spectrometry (MS) as a quantitative tool in plant metabolomics experiments are discussed, and important criteria for the development and validation of MS-based analytical methods provided.This article is part of the themed issue 'Quantitative mass spectrometry'.

Nitrogen remobilisation facilitates adventitious root formation on reversible dark-induced carbohydrate depletion in Petunia hybrida

BACKGROUND

Adventitious root (AR) formation in axillary shoot tip cuttings is a crucial physiological process for ornamental propagation that is utilised in global production chains for young plants. In this process, the nitrogen and carbohydrate metabolisms of a cutting are regulated by its total nitrogen content (N_t), dark exposure during transport and irradiance levels at distinct production sites and phases through a specific plasticity to readjust metabolite pools. Here, we examined how elevated N_t contents with a combined dark exposure of cuttings influence their internal N-pools including free amino acids and considered early anatomic events of AR formation as well as further root development in Petunia hybrida cuttings.

RESULTS

Enhanced N_t contents of unrooted cuttings resulted in elevated total free amino acid levels and in particular glutamate (glu) and glutamine (gln) in leaf and basal stem. N-allocation to mobile N-pools increased whereas the allocation to insoluble protein-N declined. A dark exposure of cuttings conserved initial N_t and nitrate-N, while it reduced insoluble protein-N and increased soluble protein, amino- and amide-N. The increase of amino acids mainly comprised asparagine (asn), aspartate (asp) and arginine (arg) in the leaves, with distinct tissue specific responses to an elevated N supply. Dark exposure induced an early transient rise of asp followed by a temporary increase of glu. A strong positive N effect of high N_t contents of cuttings on AR formation after 384 h was observed. Root meristematic cells developed at 72 h with a negligible difference for two N_t levels. After 168 h, an enhanced N_t accelerated AR formation and gave rise to first obvious fully developed roots while only meristems were formed with a low N_t. However, dark exposure for 168 h promoted AR formation particularly in cuttings with a low N_t to such an extent so that the benefit of the enhanced N_t was almost compensated. Combined dark exposure and low N_t of cuttings strongly reduced shoot growth during AR formation.

CONCLUSIONS

The results indicate that both enhanced N_t content and dark exposure of cuttings reinforced N signals and mobile N resources in the stem base facilitated by senescence-related proteolysis in leaves. Based on our results, a model of N mobilisation concomitant with carbohydrate depletion and its significance for AR formation is postulated.

Observability of Plant Metabolic Networks Is Reflected in the Correlation of Metabolic Profiles

Understanding whether the functionality of a biological system can be characterized by measuring few selected components is key to targeted phenotyping techniques in systems biology. Methods from observability theory have proven useful in identifying sensor components that have to be measured to obtain information about the entire system. Yet, the extent to which the data profiles reflect the role of components in the observability of the system remains unexplored. Here we first identify the sensor metabolites in the model plant Arabidopsis (Arabidopsis thaliana) by employing state-of-the-art genome-scale metabolic networks. By using metabolic data profiles from a set of seven environmental perturbations as well as from natural variability, we demonstrate that the data profiles of sensor metabolites are more correlated than those of nonsensor metabolites. This pattern was confirmed with in silico generated metabolic profiles from a medium-size kinetic model of plant central carbon metabolism. Altogether, due to the small number of identified sensors, our study implies that targeted metabolite analyses may provide the vast majority of relevant information about plant metabolic systems.

The Metabolic Signature of Biomass Formation in Barley

The network analysis of genome-wide transcriptome responses, metabolic signatures and enzymes' relationship to biomass formation has been studied in a diverse panel of 12 barley accessions during vegetative and reproductive stages. The primary metabolites and enzymes involved in central metabolism that determine the accumulation of shoot biomass at the vegetative stage of barley development are primarily being linked to sucrose accumulation and sucrose synthase activity. Interestingly, the metabolic and enzyme links which are strongly associated with biomass accumulation during reproductive stages are related to starch accumulation and tricarboxylic acid (TCA) cycle intermediates citrate, malate, trans-aconitate and isocitrate. Additional significant associations were also found for UDP glucose, ATP and the amino acids isoleucine, valine, glutamate and histidine during the reproductive stage. A network analysis resulted in a combined identification of metabolite and enzyme signatures indicative for grain weight accumulation that was correlated with the activity of ADP-glucose pyrophosphorylase (AGPase), a rate-limiting enzyme involved in starch biosynthesis, and with that of alanine amino transferase involved in the synthesis of storage proteins. We propose that the mechanism related to vegetative and reproductive biomass formation vs. seed biomass formation is being linked to distinct fluxes regulating sucrose, starch, sugars and amino acids as central resources. These distinct biomarkers can be used to engineer biomass production and grain weight in barley.

Effect of carbon/nitrogen ratio on carbohydrate metabolism and light energy dissipation mechanisms in Arabidopsis thaliana

Carbon (C) and nitrogen (N) nutrient sources are essential elements for metabolism, and their availability must be tightly coordinated for the optimal growth and development in plants. Plants are able to sense and respond to different C/N conditions via specific partitioning of C and N sources and the regulation of a complex cellular metabolic activity. We studied how the interaction between C and N signaling could affect carbohydrate metabolism, soluble sugar levels, photochemical efficiency of photosystem II (PSII) and the ability to drive the excess energy in Arabidopsis seedlings under moderated and disrupted C/N-nutrient conditions. Invertase and sucrose synthase activities were markedly affected by C/N-nutrient status depending on the phosphorylation status, suggesting that these enzymes may necessarily be modulated by their direct phosphorylation or phosphorylation of proteins that form complex with them in response to C/N stress. In addition, the enzymatic activity of these enzymes was also correlated with the amount of sugars, which not only act as substrate but also as signaling compounds. Analysis of chlorophyll fluorescence in plants under disrupted C/N condition suggested a reduction of electron transport rate at PSII level associated with a higher capacity for non-radiative energy dissipation in comparison with plants under moderated C/N condition. In conclusion, the tight coordination between C and N not only affects the carbohydrates metabolism and their concentration within plant tissues, but also the partitioning of the excitation energy at PSII level between radiative (electron transport) and non-radiative (heat) dissipation pathways.