Combined transcript and metabolite profiling of Arabidopsis grown under widely variant growth conditions facilitates the identification of novel metabolite-mediated regulation of gene expression

Transcriptomic and metabolomic profiling reveals the drought tolerance mechanism of Illicium difengpi (Schisandraceae)

Illicium difengpi (Schisandraceae), an endangered medicinal plant endemic to karst areas, is highly tolerant to drought and thus can be used as an ideal material for investigating adaptive mechanism to drought stress. The understanding of the drought tolerance of I. difengpi, especially at the molecular level, is lacking. In the present study, we aimed to clarify the molecular mechanism underlying drought tolerance in endemic I. difengpi plant in karst regions. The response characteristics of transcripts and changes in metabolite abundance of I. difengpi subjected to drought and rehydration were analyzed, the genes and key metabolites responsive to drought and rehydration were screened, and some important biosynthetic and secondary metabolic pathways were identified. A total of 231,784 genes and 632 metabolites were obtained from transcriptome and metabolome analyses, and most of the physiological metabolism in drought-treated I. difengpi plants recovered after rehydration. There were more upregulated genes than downregulated genes under drought and rehydration treatments, and rehydration treatment induced stable expression of 65.25% of genes, indicating that rehydration alleviated drought stress to some extent. Drought and rehydration treatment generated flavonoids, phenolic acids, flavonols, amino acids and their derivatives, as well as metabolites such as saccharides and alcohols in the leaves of I. difengpi plants, which alleviated the injury caused by excessive reactive oxygen species. The integration of transcriptome and metabolome analyses showed that, under drought stress, I. difengpi increased glutathione, flavonoids, polyamines, soluble sugars and amino acids, contributing to cell osmotic potential and antioxidant activity. The results show that the high drought tolerance and recovery after rehydration are the reasons for the normal growth of I. difengpi in karst mountain areas.

Mineralization of Few-Layer Graphene Made It Bioavailable in Chlamydomonas reinhardtii

Numerous studies have emphasized the toxicity of graphene-based nanomaterials to algae, however, the fundamental behavior and processes of graphene in biological hosts, including its transportation, metabolization, and bioavailability, are still not well understood. As photosynthetic organisms, algae are key contributors to carbon fixation and may play an important role in the fate of graphene. This study investigated the biological fate of 14C-labeled few-layer graphene (14C-FLG) in Chlamydomonas reinhardtii (C. reinhardtii). The results showed that 14C-FLG was taken up by C. reinhardtii and then translocated into its chloroplast. Metabolomic analysis revealed that 14C-FLG altered the metabolic profiles (including sugar metabolism, fatty acid, and tricarboxylic acid cycle) of C. reinhardtii, which promoted the photosynthesis of C. reinhardtii and then enhanced their growth. More importantly, the internalized 14C-FLG was metabolized into 14CO2, which was then used to participate in the metabolic processes required for life. Approximately 61.63%, 25.31%, and 13.06% of the total radioactivity (from 14CO2) was detected in carbohydrates, lipids, and proteins of algae, respectively. Overall, these results reveal the role of algae in the fate of graphene and highlight the potential of available graphene in bringing biological effects to algae, which helps to better assess the environmental risks of graphene.

Genome-wide association analysis provides insights into the genetic basis of photosynthetic responses to low-temperature stress in spring barley

Low-temperature stress (LTS) is among the major abiotic stresses affecting the geographical distribution and productivity of the most important crops. Understanding the genetic basis of photosynthetic variation under cold stress is necessary for developing more climate-resilient barley cultivars. To that end, we investigated the ability of chlorophyll fluorescence parameters (F_VF_M, and F_VF₀) to respond to changes in the maximum quantum yield of Photosystem II photochemistry as an indicator of photosynthetic energy. A panel of 96 barley spring cultivars from different breeding zones of Canada was evaluated for chlorophyll fluorescence-related traits under cold acclimation and freeze shock stresses at different times. Genome-wide association studies (GWAS) were performed using a mixed linear model (MLM). We identified three major and putative genomic regions harboring 52 significant quantitative trait nucleotides (QTNs) on chromosomes 1H, 3H, and 6H for low-temperature tolerance. Functional annotation indicated several QTNs were either within the known or close to genes that play important roles in the photosynthetic metabolites such as abscisic acid (ABA) signaling, hydrolase activity, protein kinase, and transduction of environmental signal transduction at the posttranslational modification levels. These outcomes revealed that barley plants modified their gene expression profile in response to decreasing temperatures resulting in physiological and biochemical modifications. Cold tolerance could influence a long-term adaption of barley in many parts of the world. Since the degree and frequency of LTS vary considerably among production sites. Hence, these results could shed light on potential approaches for improving barley productivity under low-temperature stress.

Bioengineering Techniques to Improve Nitrogen Transformation and Utilization: Implications for Nitrogen Use Efficiency and Future Sustainable Crop Production

Nitrogen (N) is crucial for plant growth and development, especially in physiological and biochemical processes such as component of different proteins, enzymes, nucleic acids, and plant growth regulators. Six categories, such as transporters, nitrate absorption, signal molecules, amino acid biosynthesis, transcription factors, and miscellaneous genes, broadly encompass the genes regulating NUE in various cereal crops. Herein, we outline detailed research on bioengineering modifications of N metabolism to improve the different crop yields and biomass. We emphasize effective and precise molecular approaches and technologies, including N transporters, transgenics, omics, etc., which are opening up fascinating opportunities for a complete analysis of the molecular elements that contribute to NUE. Moreover, the detection of various types of N compounds and associated signaling pathways within plant organs have been discussed. Finally, we highlight the broader impacts of increasing NUE in crops, crucial for better agricultural yield and in the greater context of global climate change.

Effects of Arbuscular Mycorrhizal Fungi on Alleviating Cadmium Stress in Medicago truncatula Gaertn

Heavy metal contamination is a global problem for ecosystems and human health. Remediation of contaminated soils has received much attention in the last decade. Aided mitigation of heavy metal phytotoxicity by arbuscular mycorrhizal fungi (AMF) is a cost-effective and environmentally friendly strategy. This study was carried out to investigate the mitigation effect of AMF inoculation on heavy metal toxicity in Medicago truncatula under soil cadmium stress. Therefore, a pot experiment was designed to evaluate the growth, chlorophyll fluorescence, Cd uptake and distribution, malondialdehyde (MDA) content, root soil physicochemical properties, and metabolite profile analysis of M. truncatula with/without AMF inoculation in Cd (20 mg/Kg)-contaminated soil. The results showed that inoculating AMF under Cd stress might enhance photosynthetic efficiency, increase plant biomass, decrease Cd and MDA content, and improve soil physicochemical properties in M. truncatula. Non-targeted metabolite analysis revealed that inoculation with AMF under Cd stress significantly upregulated the production of various amino acids in inter-root metabolism and increase organic acid and phytohormone synthesis. This study provides information on the physiological responses of mycorrhizal plants to heavy metal stress, which could help provide deeper insight into the mechanisms of heavy metal remediation by AMF.

Comparative proteomics analysis of Arabidopsis thaliana response to light-emitting diode of narrow wavelength 450 nm, 595 nm, and 650 nm

Incident light is a central modulator of plant growth and development. However, there are still open questions surrounding wavelength-specific plant proteomic responses. Here we applied tandem mass tag based quantitative proteomics technology to acquire an in-depth view of proteome changes in Arabidopsis thaliana response to narrow wavelength blue (B; 450 nm), amber (A; 595 nm), or red (R; 650 nm) light treatments. A total of 16,707 proteins were identified with 9120 proteins quantified across all three light treatments in three biological replicates. This enabled examination of changes in the abundance for proteins with low abundance and important regulatory roles including transcription factors and hormone signaling. Importantly, 18% (1631 proteins) of the A. thaliana proteome is differentially abundant in response to narrow wavelength lights, and changes in proteome correlate well with different morphologies exhibited by plants. To showcase the usefulness of this resource, data were placed in the context of more than thirty published datasets, providing orthogonal validation and further insights into light-specific biological pathways, including Systemic Acquired Resistance and Shade Avoidance Syndrome. This high-resolution resource for A. thaliana provides baseline data and a tool for defining molecular mechanisms that control fundamental aspects of plant response to changing light conditions, with implications in plant development and adaptation. SIGNIFICANCE: Understanding of molecular mechanisms involved in wavelength-specific response of plant is question of widespread interest both to basic researchers and to those interested in applying such knowledge to the engineering of novel proteins, as well as targeted lighting systems. Here we sought to generate a high-resolution labeling proteomic profile of plant leaves, based on exposure to specific narrow-wavelength lights. Although changes in plant physiology in response to light spectral composition is well documented, there is limited knowledge on the roles of specific light wavelengths and their impact. Most previous studies have utilized relatively broad wavebands in their experiments. These multi-wavelengths lights function in a complex signaling network, which provide major challenges in inference of wavelength-specific molecular processes that underly the plant response. Besides, most studies have compared the effect of blue and red wavelengths comparing with FL, as control. As FL light consists the mixed spectra composition of both red and blue as well as numerous other wavelengths, comparing undeniably results in inconsistent and overlapping responses that will hamper effects to elucidate the plant response to specific wavelengths [1, 2]. Monitoring plant proteome response to specific wavelengths and further compare the changes to one another, rather than comparing plants proteome to FL, is thus necessary to gain the clear insights to specific underlying biological pathways and their effect consequences in plant response. Here, we employed narrow wavelength LED lights in our design to eliminate the potential overlap in molecular responses by ensuring non-overlapping wavelengths in the light treatments. We further applied TMT-labeling technology to gain a high-resolution view on the associates of proteome changes. Our proteomics data provides an in-depth coverage suitable for system-wide analyses, providing deep insights on plant physiological processes particularly because of the tremendous increase in the amount of identified proteins which outreach the other biological data.

Prediction of Metabolic Profiles from Transcriptomics Data in Human Cancer Cell Lines

The Metabolome and Transcriptome are mutually communicating within cancer cells, and this interplay is translated into the existence of quantifiable correlation structures between gene expression and metabolite abundance levels. Studying these correlations could provide a novel venue of understanding cancer and the discovery of novel biomarkers and pharmacological strategies, as well as laying the foundation for the prediction of metabolite quantities by leveraging information from the more widespread transcriptomics data. In the current paper, we investigate the correlation between gene expression and metabolite levels in the Cancer Cell Line Encyclopedia dataset, building a direct correlation network between the two molecular ensembles. We show that a metabolite/transcript correlation network can be used to predict metabolite levels in different samples and datasets, such as the NCI-60 cancer cell line dataset, both on a sample-by-sample basis and in differential contrasts. We also show that metabolite levels can be predicted in principle on any sample and dataset for which transcriptomics data are available, such as the Cancer Genome Atlas (TCGA).

Comparative assessment of amino acids composition in two types of marine fish silage

Fish silage is a brown liquefied product achieved by the action of enzymes when finely grounded whole/parts of either single or mixed fish types are subjected to acidification. This study made a comparative assessment of biochemical and nutritive properties, especially the amino acid composition in supernatant phase of formic acid silages prepared from two fish types, Indian mackerel (Rastrelliger kanagurta) and false travely (Lactarius lactarius) representing fat fish (FF, fat content > 5%) and lean fish (LF, fat content < 5%), respectively during 35 days of fermentation (DoF). Significantly higher content of total amino acid (TAA) and free amino acids (FAA) were recorded in FFS (TAA, 41.2 ± 0.03 mg/g; FAA, 31.3 ± 0.003 mg/g) compared to LFS (TAA, 35.8 ± 0.07 mg/g; FAA, 18.26 ± 0.003 mg/g; FAA, 31.3 ± 0.003 mg/g) (p < 0.05). At the end of 35 DoF, the concentrations of amino acids such as asparagine, histidine, isoleucine, valine, cysteine, serine, lysine and arginine were significantly higher in FFS as compared to LFS. The relative amino acid composition of FFS and LFS varied in accordance with DoF and the relationship was found to be highly significant (ANOVA, p < 0.00001). High concentrations of l-amino acids such as leucine, glutamic acid and arginine were recorded in both FFS and LFS. In conclusion, the analysis suggested that a fermentation period of 25–30 days showed a significant effect on the composition of amino acids in both types of ensilage compared to other fermentation periods (p < 0.05). Considering the role of amino acids in enhancing the plant growth and proliferation, the findings of the present study are quite useful.

Identification and Quantification of Coumarins by UHPLC-MS in Arabidopsis thaliana Natural Populations

Coumarins are phytochemicals occurring in the plant kingdom, which biosynthesis is induced under various stress factors. They belong to the wide class of specialized metabolites well known for their beneficial properties. Due to their high and wide biological activities, coumarins are important not only for the survival of plants in changing environmental conditions, but are of great importance in the pharmaceutical industry and are an active source for drug development. The identification of coumarins from natural sources has been reported for different plant species including a model plant Arabidopsis thaliana. In our previous work, we demonstrated a presence of naturally occurring intraspecies variation in the concentrations of scopoletin and its glycoside, scopolin, the major coumarins accumulating in Arabidopsis roots. Here, we expanded this work by examining a larger group of 28 Arabidopsis natural populations (called accessions) and by extracting and analysing coumarins from two different types of tissues-roots and leaves. In the current work, by quantifying the coumarin content in plant extracts with ultra-high-performance liquid chromatography coupled with a mass spectrometry analysis (UHPLC-MS), we detected a significant natural variation in the content of simple coumarins like scopoletin, umbelliferone and esculetin together with their glycosides: scopolin, skimmin and esculin, respectively. Increasing our knowledge of coumarin accumulation in Arabidopsis natural populations, might be beneficial for the future discovery of physiological mechanisms of action of various alleles involved in their biosynthesis. A better understanding of biosynthetic pathways of biologically active compounds is the prerequisite step in undertaking a metabolic engineering research.

Metabolite Regulatory Interactions Control Plant Respiratory Metabolism via Target of Rapamycin (TOR) Kinase Activation

Respiration rate measurements provide an important readout of energy expenditure and mitochondrial activity in plant cells during the night. As plants inhabit a changing environment, regulatory mechanisms must ensure that respiratory metabolism rapidly and effectively adjusts to the metabolic and environmental conditions of the cell. Using a high-throughput approach, we have directly identified specific metabolites that exert transcriptional, translational, and posttranslational control over the nighttime O2 consumption rate (RN) in mature leaves of Arabidopsis (Arabidopsis thaliana). Multi-hour RN measurements following leaf disc exposure to a wide array of primary carbon metabolites (carbohydrates, amino acids, and organic acids) identified phosphoenolpyruvate (PEP), Pro, and Ala as the most potent stimulators of plant leaf RN Using metabolite combinations, we discovered metabolite-metabolite regulatory interactions controlling RN Many amino acids, as well as Glc analogs, were found to potently inhibit the RN stimulation by Pro and Ala but not PEP. The inhibitory effects of amino acids on Pro- and Ala-stimulated RN were mitigated by inhibition of the Target of Rapamycin (TOR) kinase signaling pathway. Supporting the involvement of TOR, these inhibitory amino acids were also shown to be activators of TOR kinase. This work provides direct evidence that the TOR signaling pathway in plants responds to amino acid levels by eliciting regulatory effects on respiratory energy metabolism at night, uniting a hallmark mechanism of TOR regulation across eukaryotes.

The role of amino acid metabolism during abiotic stress release

Plant responses to abiotic stress include various modifications in amino acid metabolism. By using a hydroponic culture system, we systematically investigate modification in amino acid profiles and the proteome of Arabidopsis thaliana leaves during initial recovery from low water potential or high salinity. Both treatments elicited oxidative stress leading to a biphasic stress response during recovery. Degradation of highly abundant proteins such as subunits of photosystems and ribosomes contributed to an accumulation of free amino acids. Catabolic pathways for several low abundant amino acids were induced indicating their usage as an alternative respiratory substrate to compensate for the decreased photosynthesis. Our results demonstrate that rapid detoxification of potentially detrimental amino acids such as Lys is a priority during the initial stress recovery period. The content of Pro, which acts as a compatible osmolyte during stress, was adjusted by balancing its synthesis and catabolism both of which were induced both during and after stress treatments. The production of amino acid derived secondary metabolites was up-regulated specifically during the recovery period, and our dataset also indicates increased synthesis rates of the precursor amino acids. Overall, our results support a tight relationship between amino acid metabolism and stress responses.

Mutations in the Arabidopsis ROL17/isopropylmalate synthase 1 locus alter amino acid content, modify the TOR network, and suppress the root hair cell development mutant lrx1

The growth and development of organisms must be tightly controlled and adjusted to nutrient availability and metabolic activities. The Target of Rapamycin (TOR) network is a major control mechanism in eukaryotes and influences processes such as translation, mitochondrial activity, production of reactive oxygen species, and the cytoskeleton. In Arabidopsis thaliana, inhibition of the TOR kinase causes changes in cell wall architecture and suppression of phenotypic defects of the cell wall formation mutant lrx1 (leucine-rich repeat extensin 1). The rol17 (repressor of lrx1 17) mutant was identified as a new suppressor of lrx1 that induces also a short root phenotype. The ROL17 locus encodes isopropylmalate synthase 1, a protein involved in leucine biosynthesis. Dependent on growth conditions, mutations in ROL17 do not necessarily alter the level of leucine, but always cause development of the rol17 mutant phenotypes, suggesting that the mutation does not only influence leucine biosynthesis. Changes in the metabolome of rol17 mutants are also found in plants with inhibited TOR kinase activity. Furthermore, rol17 mutants show reduced sensitivity to the TOR kinase inhibitor AZD-8055, indicating a modified TOR network. Together, these data suggest that suppression of lrx1 by rol17 is the result of an alteration of the TOR network.

Diversified secondary metabolite biosynthesis gene repertoire revealed in symbiotic dinoflagellates

Symbiodiniaceae dinoflagellates possess smaller nuclear genomes than other dinoflagellates and produce structurally specialized, biologically active, secondary metabolites. Till date, little is known about the evolution of secondary metabolism in dinoflagellates as comparative genomic approaches have been hampered by their large genome sizes. Here, we overcome this challenge by combining genomic and metabolomics approaches to investigate how chemical diversity arises in three decoded Symbiodiniaceae genomes (clades A3, B1 and C). Our analyses identify extensive diversification of polyketide synthase and non-ribosomal peptide synthetase genes from two newly decoded genomes of Symbiodinium tridacnidorum (A3) and Cladocopium sp. (C). Phylogenetic analyses indicate that almost all the gene families are derived from lineage-specific gene duplications in all three clades, suggesting divergence for environmental adaptation. Few metabolic pathways are conserved among the three clades and we detect metabolic similarity only in the recently diverged clades, B1 and C. We establish that secondary metabolism protein architecture guides substrate specificity and that gene duplication and domain shuffling have resulted in diversification of secondary metabolism genes.

Synthesis versus degradation: directions of amino acid metabolism during Arabidopsis abiotic stress response

During abiotic stress low abundant amino acids are not synthesized but they accumulate due to increased protein turnover under conditions inducing carbohydrate starvation (dehydration, salt stress, darkness) and are degraded. Metabolic adaptation is crucial for abiotic stress resistance in plants, and accumulation of specific amino acids as well as secondary metabolites derived from amino acid metabolism has been implicated in increased tolerance to adverse environmental conditions. The role of proline, which is synthesized during Arabidopsis stress response to act as a compatible osmolyte, has been well established. However, conclusions drawn about potential functions of other amino acids such as leucine, valine, and isoleucine are not entirely consistent. This study reevaluates published datasets with a special emphasis on changes in the free amino acid pool and transcriptional regulation of the associated anabolic and catabolic pathways. In order to gain a comprehensive overview about the general direction of amino acid metabolism under abiotic stress conditions a complete map of all currently known enzymatic steps involved in amino acid synthesis and degradation was assembled including also the initial steps leading to the synthesis of secondary metabolites. Microarray datasets and amino acid profiles of Arabidopsis plants exposed to dehydration, high salinity, extended darkness, cold, and heat were systematically analyzed to identify trends in fluxes of amino acid metabolism. Some high abundant amino acids such as proline, arginine, asparagine, glutamine, and GABA are synthesized during abiotic stress to act as compatible osmolytes, precursors for secondary metabolites, or storage forms of organic nitrogen. In contrast, most of the low abundant amino acids are not synthesized but they accumulate due to increased protein turnover under conditions inducing carbohydrate starvation (dehydration, salt stress, extended darkness) and are degraded.

Data Reduction Approaches for Dissecting Transcriptional Effects on Metabolism

The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coli, Saccharomycies cerevisiae, and Arabidopsis thaliana.

Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis

BACKGROUND

Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response.

RESULTS

In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways.

CONCLUSIONS

Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome may respond with different extent to individual stress components. Their contrasting behavior in response to temperature stress highlights that the protein folding machinery effectively shields the metabolism from stress. Disentangling the complex relationships between transcriptome and metabolome in response to stress is an enormous challenge. As demonstrated by case studies with supporting evidence from additional data, the large dataset provided in this study may assist in determining linked genetic and metabolic features as candidates for future mechanistic analyses.

How do plants sense their nitrogen status?

The primary processes that contribute to the efficient capture of soil nitrate are the development of a root system that effectively explores the soil and the expression of high-affinity nitrate uptake systems in those roots. Both these processes are highly regulated to take into account the availability and distribution of external nitrate pools and the endogenous N status of the plant. While significant progress has been made in elucidating the early steps in sensing and responding to external nitrate, there is much less clarity about how the plant monitors its N status. This review specifically addresses the questions of what N compounds are sensed and in which part of the plant, as well as the identity of the signalling pathways responsible for their detection. Candidates that are considered for the role of N sensory systems include the target of rapamycin (TOR) signalling pathway, the general control non-derepressible 2 (GCN2) pathway, the plastidic PII-dependent pathway, and the family of glutamate-like receptors (GLRs). However, despite significant recent progress in elucidating the function and mode of action of these signalling systems, there is still much uncertainty about the extent to which they contribute to the process by which plants monitor their N status. The possibility is discussed that the large GLR family of Ca2+ channels, which are gated by a wide range of different amino acids and expressed throughout the plant, could act as amino acid sensors upstream of a Ca2+-regulated signalling pathway, such as the TOR pathway, to regulate the plant's response to changes in N status.

Effect of growth temperature on glucosinolate profiles in Arabidopsis thaliana accessions

Glucosinolates are plant secondary metabolites with important roles in plant defence against pathogens and pests and are also known for their health benefits. Understanding how environmental factors affect the level and composition of glucosinolates is therefore of importance in the perspective of climate change. In this study we analysed glucosinolates in Arabidopsis thaliana accessions when grown at constant standard (21 °C), moderate (15 °C) and low (9 °C) temperatures during three generations. In most of the tested accessions moderate and pronounced chilling temperatures led to higher levels of glucosinolates, especially aliphatic glucosinolates. Which temperature yielded the highest glucosinolate levels was accession-dependent. Transcriptional profiling revealed also accession-specific gene responses, but only a limited correlation between changes in glucosinolate-related gene expression and glucosinolate levels. Different growth temperatures in one generation did not consistently affect glucosinolate composition in subsequent generations, hence a clear transgenerational effect of temperature on glucosinolates was not observed.

TOR Signaling and Nutrient Sensing

All living organisms rely on nutrients to sustain cell metabolism and energy production, which in turn need to be adjusted based on available resources. The evolutionarily conserved target of rapamycin (TOR) protein kinase is a central regulatory hub that connects environmental information about the quantity and quality of nutrients to developmental and metabolic processes in order to maintain cellular homeostasis. TOR is activated by both nitrogen and carbon metabolites and promotes energy-consuming processes such as cell division, mRNA translation, and anabolism in times of abundance while repressing nutrient remobilization through autophagy. In animals and yeasts, TOR acts antagonistically to the starvation-induced AMP-activated kinase (AMPK)/sucrose nonfermenting 1 (Snf1) kinase, called Snf1-related kinase 1 (SnRK1) in plants. This review summarizes the immense knowledge on the relationship between TOR signaling and nutrients in nonphotosynthetic organisms and presents recent findings in plants that illuminate the crucial role of this pathway in conveying nutrient-derived signals and regulating many aspects of metabolism and growth.

Effects of Parental Temperature and Nitrate on Seed Performance are Reflected by Partly Overlapping Genetic and Metabolic Pathways

Seed performance is affected by the seed maturation environment, and previously we have shown that temperature, nitrate and light intensity were the most influential environmental factors affecting seed performance. Seeds developed in these environments were selected to assess the underlying metabolic pathways, using a combination of transcriptomics and metabolomics. These analyses revealed that the effects of the parental temperature and nitrate environments were reflected by partly overlapping genetic and metabolic networks, as indicated by similar changes in the expression levels of metabolites and transcripts. Nitrogen metabolism-related metabolites (asparagine, γ-aminobutyric acid and allantoin) were significantly decreased in both low temperature (15 °C) and low nitrate (N0) maturation environments. Correspondingly, nitrogen metabolism genes (ALLANTOINASE, NITRATE REDUCTASE 1, NITRITE REDUCTASE 1 and NITRILASE 4) were differentially regulated in the low temperature and nitrate maturation environments, as compared with control conditions. High light intensity during seed maturation increased galactinol content, and displayed a high correlation with seed longevity. Low light had a genotype-specific effect on cell surface-encoding genes in the DELAY OF GERMINATION 6-near isogenic line (NILDOG6). Overall, the integration of phenotypes, metabolites and transcripts led to new insights into the regulation of seed performance.

Stress memory induced transcriptional and metabolic changes of perennial ryegrass (Lolium perenne) in response to salt stress

Preexposure to a stress could induce stable signals and reactions on plant physiology and gene expression during future encounters as a 'stress memory'. In this study, we found that two trainable genes, BPSP encoding putative brown plant hopper susceptibility protein and sucs encoding sucrose synthase displayed transcriptional memory for their considerably higher transcript levels during two or more subsequent stresses (S3, S4) relative to the initial stress (S0), and their expression returning to basal transcript levels (non-stressed) during the recovery states (R1, R2 and R3). Removing the repetitive stress/recovery exercise, activated transcriptional memory from two trainable genes persisted for at least 4 days in perennial ryegrass. The pretrainable genes with stress memory effort had higher response to the subsequent elevated NaCl concentration treatment than the non-trainable plants, which was confirmed by lower electrolyte leakage and minimum H2 O2 and O2 (-) accumulation. Salt stress elevated the content of 41 metabolites in perennial ryegrass leaves, and sugars and sugar alcohol accounted for more than 74.1% of the total metabolite content. The salt stress memory was associated with higher contents of 11 sugars and 1 sugar alcohol in the pretrainable grass leaves. Similarly, six sugars showed greater content in the pretrainable grass roots. These novel phenomena associated with transcriptional memory and metabolite profiles could lead to new insights into improving plant salinity acclimation process.

Amino Acid Catabolism in Plants

Amino acids have various prominent functions in plants. Besides their usage during protein biosynthesis, they also represent building blocks for several other biosynthesis pathways and play pivotal roles during signaling processes as well as in plant stress response. In general, pool sizes of the 20 amino acids differ strongly and change dynamically depending on the developmental and physiological state of the plant cell. Besides amino acid biosynthesis, which has already been investigated in great detail, the catabolism of amino acids is of central importance for adjusting their pool sizes but so far has drawn much less attention. The degradation of amino acids can also contribute substantially to the energy state of plant cells under certain physiological conditions, e.g. carbon starvation. In this review, we discuss the biological role of amino acid catabolism and summarize current knowledge on amino acid degradation pathways and their regulation in the context of plant cell physiology.

Effects of Elevated Atmospheric CO2 on Primary Metabolite Levels in Arabidopsis thaliana Col-0 Leaves: An Examination of Metabolome Data

Elevated atmospheric CO(2) concentrations ([CO(2)]) affect primary metabolite levels because CO(2) is a direct substrate for photosynthesis. In several studies, the responses of primary metabolite levels have been examined using Arabidopsis thaliana leaves, but these results have not been comprehensively discussed. Here, we examined metabolome data for A. thaliana accession Col-0 leaves that were grown at elevated [CO(2)] with sufficient nitrogen (N) nutrition. At elevated [CO(2)], starch, monosaccharides and several major amino acids accumulated in leaves. The degree of accumulation depended on whether the rooting medium contained NH(4) (+) or only NO(3) (-). Because low N conditions induce an increase in carbohydrates similar to that of elevated [CO(2)], we compared the responses of primary metabolite levels between elevated [CO(2)] and low N conditions. Levels of the tricarboxylic acid (TCA) cycle-associated organic acids and major amino acids decreased with low N, but not with elevated [CO(2)]. Even at elevated [CO(2)], the low N induced the decreases in the levels of organic acids and major amino acids. A small sink size also affects the primary metabolite response patterns in leaves under elevated [CO(2)] conditions. Thus, care is necessary when interpreting primary metabolite changes in leaves of field-grown plants.

Integrative Approaches to Enhance Understanding of Plant Metabolic Pathway Structure and Regulation

Huge insight into molecular mechanisms and biological network coordination have been achieved following the application of various profiling technologies. Our knowledge of how the different molecular entities of the cell interact with one another suggests that, nevertheless, integration of data from different techniques could drive a more comprehensive understanding of the data emanating from different techniques. Here, we provide an overview of how such data integration is being used to aid the understanding of metabolic pathway structure and regulation. We choose to focus on the pairwise integration of large-scale metabolite data with that of the transcriptomic, proteomics, whole-genome sequence, growth- and yield-associated phenotypes, and archival functional genomic data sets. In doing so, we attempt to provide an update on approaches that integrate data obtained at different levels to reach a better understanding of either single gene function or metabolic pathway structure and regulation within the context of a broader biological process.

Metabolomic changes during cellular transformation monitored by metabolite-metabolite correlation analysis and correlated with gene expression

To investigate metabolic changes during cellular transformation, we used a 1H NMR based metabolite-metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used to further explain the results. Transformed cells showed many more metabolite-metabolite correlations than control cells. Some had intuitively plausible explanations: a shift from glycolysis to amino acid oxidation after transformation was accompanied by a strongly positive correlation between glucose and glutamine and a strongly negative one between lactate and glutamate; there were also many correlations between the branched chain amino acids and the aromatic amino acids. Others remain puzzling: after transformation strong positive correlations developed between choline and a group of five amino acids, whereas the same amino acids showed negative correlations with phosphocholine, a membrane phospholipid precursor. MMCA in conjunction with transcriptome analysis has opened a new window into the metabolome.

Taxonomic and environmental variation of metabolite profiles in marine dinoflagellates of the genus symbiodinium

Microorganisms in terrestrial and marine ecosystems are essential to environmental sustainability. In the marine environment, invertebrates often depend on metabolic cooperation with their endosymbionts. Coral reefs, one of the most important marine ecosystems, are based on the symbiosis between a broad diversity of dinoflagellates of the genus Symbiodinium and a wide phyletic diversity of hosts (i.e., cnidarian, molluscan, poriferan). This diversity is reflected in the ecology and physiology of the symbionts, yet the underlying biochemical mechanisms are still poorly understood. We examined metabolite profiles of four cultured species of Symbiodinium known to form viable symbioses with reef-building corals, S. microadriaticum (cp-type A194), S. minutum (cp-type B184), S. psygmophilum (cp-type B224) and S. trenchii (cp-type D206). Metabolite profiles were shown to differ among Symbiodinium species and were found to be affected by their physiological response to growth in different temperatures and light regimes. A combined Random Forests and Bayesian analysis revealed that the four Symbiodinium species examined primarily differed in their production of sterols and sugars, including a C₂₉ stanol and the two sterols C₂₈Δ⁵ and C₂₈Δ^5,22, as well as differences in metabolite abundances of a hexose and inositol. Inositol levels were also strongly affected by changes in temperature across all Symbiodinium species. Our results offer a detailed view of the metabolite profile characteristic of marine symbiotic dinoflagellates of the genus Symbiodinium, and identify patterns of metabolites related to several growth conditions.

Co-ordination and divergence of cell-specific transcription and translation of genes in arabidopsis root cells

BACKGROUND AND AIMS

A key challenge in biology is to systematically investigate and integrate the different levels of information available at the global and single-cell level. Recent studies have elucidated spatiotemporal expression patterns of root cell types in Arabidopsis thaliana, and genome-wide quantification of polysome-associated mRNA levels, i.e. the translatome, has also been obtained for corresponding cell types. Translational control has been increasingly recognized as an important regulatory step in protein synthesis. The aim of this study was to investigate coupled transcription and translation by use of publicly available root datasets.

METHODS

Using cell-type-specific datasets of the root transcriptome and translatome of arabidopsis, a systematic assessment was made of the degree of co-ordination and divergence between these two levels of cellular organization. The computational analysis considered correlation and variation of expression across cell types at both system levels, and also provided insights into the degree of co-regulatory relationships that are preserved between the two processes.

KEY RESULTS

The overall correlation of expression and translation levels of genes resemble an almost bimodal distribution (mean/median value of 0·08/0·12), with a second, less strongly pronounced 'mode' for negative Pearson's correlation coefficient values. The analysis conducted also confirms that previously identified key transcriptional activators of secondary cell wall development display highly conserved patterns of transcription and translation across the investigated cell types. Moreover, the biological processes that display conserved and divergent patterns based on the cell-type-specific expression and translation levels were identified.

CONCLUSIONS

In agreement with previous studies in animal cells, a large degree of uncoupling was found between the transcriptome and translatome. However, components and processes were also identified that are under co-ordinated transcriptional and translational control in plant root cells.

Regulation of amino acid metabolic enzymes and transporters in plants

Amino acids play several critical roles in plants, from providing the building blocks of proteins to being essential metabolites interacting with many branches of metabolism. They are also important molecules that shuttle organic nitrogen through the plant. Because of this central role in nitrogen metabolism, amino acid biosynthesis, degradation, and transport are tightly regulated to meet demand in response to nitrogen and carbon availability. While much is known about the feedback regulation of the branched biosynthesis pathways by the amino acids themselves, the regulation mechanisms at the transcriptional, post-transcriptional, and protein levels remain to be identified. This review focuses mainly on the current state of our understanding of the regulation of the enzymes and transporters at the transcript level. Current results describing the effect of transcription factors and protein modifications lead to a fragmental picture that hints at multiple, complex levels of regulation that control and coordinate transport and enzyme activities. It also appears that amino acid metabolism, amino acid transport, and stress signal integration can influence each other in a so-far unpredictable fashion.

Bottom-up Metabolic Reconstruction of Arabidopsis and Its Application to Determining the Metabolic Costs of Enzyme Production

Large-scale modeling of plant metabolism provides the possibility to compare and contrast different cellular and environmental scenarios with the ultimate aim of identifying the components underlying the respective plant behavior. The existing models of Arabidopsis (Arabidopsis thaliana) are top-down assembled, whereby the starting point is the annotated genome, in particular, the metabolic genes. Hence, dead-end metabolites and blocked reactions can arise that are subsequently addressed by using gap-filling algorithms in combination with species-unspecific genes. Here, we present a bottom-up-assembled, large-scale model that relies solely on Arabidopsis-specific annotations and results in the inclusion of only manually curated reactions. While the existing models are largely condition unspecific by employing a single biomass reaction, we provide three biomass compositions that pertain to realistic and frequently examined scenarios: carbon-limiting, nitrogen-limiting, and optimal growth conditions. The comparative analysis indicates that the proposed Arabidopsis core model exhibits comparable efficiency in carbon utilization and flexibility to the existing network alternatives. Moreover, the model is utilized to quantify the energy demand of amino acid and enzyme de novo synthesis in photoautotrophic growth conditions. Illustrated by the case of the most abundant protein in the world, Rubisco, we determine its synthesis cost in terms of ATP requirements. This, in turn, allows us to explore the tradeoff between protein synthesis and growth in Arabidopsis. Altogether, the model provides a solid basis for completely species-specific integration of high-throughput data, such as gene expression levels, and for condition-specific investigations of in silico metabolic engineering strategies.

Metabolic changes in Avena sativa crowns recovering from freezing

Extensive research has been conducted on cold acclimation and freezing tolerance of fall-sown cereal plants due to their economic importance; however, little has been reported on the biochemical changes occurring over time after the freezing conditions are replaced by conditions favorable for recovery and growth such as would occur during spring. In this study, GC-MS was used to detect metabolic changes in the overwintering crown tissue of oat (Avena sativa L.) during a fourteen day time-course after freezing. Metabolomic analysis revealed increases in most amino acids, particularly proline, 5-oxoproline and arginine, which increased greatly in crowns that were frozen compared to controls and correlated very significantly with days after freezing. In contrast, sugar and sugar related metabolites were little changed by freezing, except sucrose and fructose which decreased dramatically. In frozen tissue all TCA cycle metabolites, especially citrate and malate, decreased in relation to unfrozen tissue. Alterations in some amino acid pools after freezing were similar to those observed in cold acclimation whereas most changes in sugar pools after freezing were not. These similarities and differences suggest that there are common as well as unique genetic mechanisms between these two environmental conditions that are crucial to the winter survival of plants.

The small subunit 1 of the Arabidopsis isopropylmalate isomerase is required for normal growth and development and the early stages of glucosinolate formation

In Arabidopsis thaliana the evolutionary and functional relationship between Leu biosynthesis and the Met chain elongation pathway, the first part of glucosinolate formation, is well documented. Nevertheless the exact functions of some pathway components are still unclear. Isopropylmalate isomerase (IPMI), an enzyme usually involved in Leu biosynthesis, is a heterodimer consisting of a large and a small subunit. While the large protein is encoded by a single gene (ISOPROPYLMALATE ISOMERASE LARGE SUBUNIT1), three genes encode small subunits (ISOPROPYLMALATE ISOMERASE SMALL SUBUNIT1 to 3). We have now analyzed small subunit 1 (ISOPROPYLMALATE ISOMERASE SMALL SUBUNIT1) employing artificial microRNA for a targeted knockdown of the encoding gene. Strong reduction of corresponding mRNA levels to less than 5% of wild-type levels resulted in a severe phenotype with stunted growth, narrow pale leaf blades with green vasculature and abnormal adaxial-abaxial patterning as well as anomalous flower morphology. Supplementation of the knockdown plants with leucine could only partially compensate for the morphological and developmental abnormalities. Detailed metabolite profiling of the knockdown plants revealed changes in the steady state levels of isopropylmalate and glucosinolates as well as their intermediates demonstrating a function of IPMI SSU1 in both leucine biosynthesis and the first cycle of Met chain elongation. Surprisingly the levels of free leucine slightly increased suggesting an imbalanced distribution of leucine within cells and/or within plant tissues.

Poly(ADP-ribose)polymerase activity controls plant growth by promoting leaf cell number

A changing global environment, rising population and increasing demand for biofuels are challenging agriculture and creating a need for technologies to increase biomass production. Here we demonstrate that the inhibition of poly (ADP-ribose) polymerase activity is a promising technology to achieve this under non-stress conditions. Furthermore, we investigate the basis of this growth enhancement via leaf series and kinematic cell analysis as well as single leaf transcriptomics and plant metabolomics under non-stress conditions. These data indicate a regulatory function of PARP within cell growth and potentially development. PARP inhibition enhances growth of Arabidopsis thaliana by enhancing the cell number. Time course single leaf transcriptomics shows that PARP inhibition regulates a small subset of genes which are related to growth promotion, cell cycle and the control of metabolism. This is supported by metabolite analysis showing overall changes in primary and particularly secondary metabolism. Taken together the results indicate a versatile function of PARP beyond its previously reported roles in controlling plant stress tolerance and thus can be a useful target for enhancing biomass production.

Dosage Effects of Salt and pH Stresses on Saccharomyces cerevisiae as Monitored via Metabolites by Using Two Dimensional NMR Spectroscopy

Saccharomyces cerevisiae, which is a common species of yeast, is by far the most extensively studied model of a eukaryote because although it is one of the simplest eukaryotes, its basic cellular processes resemble those of higher organisms. In addition, yeast is a commercially valuable organism for ethanol production. Since the yeast data can be extrapolated to the important aspects of higher organisms, many researchers have studied yeast metabolism under various conditions. In this report, we analyzed and compared metabolites of Saccharomyces cerevisiae under salt and pH stresses of various strengths by using two-dimensional NMR spectroscopy. A total of 31 metabolites were identified for most of the samples. The levels of many identified metabolites showed gradual or drastic increases or decreases depending on the severity of the stresses involved. The statistical analysis produced a holistic outline: pH stresses were clustered together, but salt stresses were spread out depending on the severity. This work could provide a link between the metabolite profiles and mRNA or protein profiles under representative and well studied stress conditions.

Genome-wide analysis of branched-chain amino acid levels in Arabidopsis seeds

Branched-chain amino acids (BCAAs) are three of the nine essential amino acids in human and animal diets and are important for numerous processes in development and growth. However, seed BCAA levels in major crops are insufficient to meet dietary requirements, making genetic improvement for increased and balanced seed BCAAs an important nutritional target. Addressing this issue requires a better understanding of the genetics underlying seed BCAA content and composition. Here, a genome-wide association study and haplotype analysis for seed BCAA traits in Arabidopsis thaliana revealed a strong association with a chromosomal interval containing two branched-chain amino acid transferases, BCAT1 and BCAT2. Linkage analysis, reverse genetic approaches, and molecular complementation analysis demonstrated that allelic variation at BCAT2 is responsible for the natural variation of seed BCAAs in this interval. Complementation analysis of a bcat2 null mutant with two significantly different alleles from accessions Bayreuth-0 and Shahdara is consistent with BCAT2 contributing to natural variation in BCAA levels, glutamate recycling, and free amino acid homeostasis in seeds in an allele-dependent manner. The seed-specific phenotype of bcat2 null alleles, its strong transcription induction during late seed development, and its subcellular localization to the mitochondria are consistent with a unique, catabolic role for BCAT2 in BCAA metabolism in seeds.

Coordinating metabolite changes with our perception of plant abiotic stress responses: emerging views revealed by integrative-omic analyses

Metabolic configuration and adaptation under a range of abiotic stresses, including drought, heat, salinity, cold, and nutrient deprivation, are subjected to an intricate span of molecular pathways that work in parallel in order to enhance plant fitness and increase stress tolerance. In recent years, unprecedented advances have been made in identifying and linking different abiotic stresses, and the current challenge in plant molecular biology is deciphering how the signaling responses are integrated and transduced throughout metabolism. Metabolomics have often played a fundamental role in elucidating the distinct and overlapping biochemical changes that occur in plants. However, a far greater understanding and appreciation of the complexity in plant metabolism under specific stress conditions have become apparent when combining metabolomics with other—omic platforms. This review focuses on recent advances made in understanding the global changes occurring in plant metabolism under abiotic stress conditions using metabolite profiling as an integrated discovery platform.

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

Natural genetic diversity provides a powerful tool to study the complex interrelationship between metabolism and growth. Profiling of metabolic traits combined with network-based and statistical analyses allow the comparison of conditions and identification of sets of traits that predict biomass. However, it often remains unclear why a particular set of metabolites is linked with biomass and to what extent the predictive model is applicable beyond a particular growth condition. A panel of 97 genetically diverse Arabidopsis (Arabidopsis thaliana) accessions was grown in near-optimal carbon and nitrogen supply, restricted carbon supply, and restricted nitrogen supply and analyzed for biomass and 54 metabolic traits. Correlation-based metabolic networks were generated from the genotype-dependent variation in each condition to reveal sets of metabolites that show coordinated changes across accessions. The networks were largely specific for a single growth condition. Partial least squares regression from metabolic traits allowed prediction of biomass within and, slightly more weakly, across conditions (cross-validated Pearson correlations in the range of 0.27-0.58 and 0.21-0.51 and P values in the range of <0.001-<0.13 and <0.001-<0.023, respectively). Metabolic traits that correlate with growth or have a high weighting in the partial least squares regression were mainly condition specific and often related to the resource that restricts growth under that condition. Linear mixed-model analysis using the combined metabolic traits from all growth conditions as an input indicated that inclusion of random effects for the conditions improves predictions of biomass. Thus, robust prediction of biomass across a range of conditions requires condition-specific measurement of metabolic traits to take account of environment-dependent changes of the underlying networks.

Transcriptome responses to combinations of stresses in Arabidopsis

Biotic and abiotic stresses limit agricultural yields, and plants are often simultaneously exposed to multiple stresses. Combinations of stresses such as heat and drought or cold and high light intensity have profound effects on crop performance and yields. Thus, delineation of the regulatory networks and metabolic pathways responding to single and multiple concurrent stresses is required for breeding and engineering crop stress tolerance. Many studies have described transcriptome changes in response to single stresses. However, exposure of plants to a combination of stress factors may require agonistic or antagonistic responses or responses potentially unrelated to responses to the corresponding single stresses. To analyze such responses, we initially compared transcriptome changes in 10 Arabidopsis (Arabidopsis thaliana) ecotypes using cold, heat, high-light, salt, and flagellin treatments as single stress factors as well as their double combinations. This revealed that some 61% of the transcriptome changes in response to double stresses were not predic from the responses to single stress treatments. It also showed that plants prioritized between potentially antagonistic responses for only 5% to 10% of the responding transcripts. This indicates that plants have evolved to cope with combinations of stresses and, therefore, may be bred to endure them. In addition, using a subset of this data from the Columbia and Landsberg erecta ecotypes, we have delineated coexpression network modules responding to single and combined stresses.

Genetic analysis of metabolome-phenotype interactions: from model to crop species

The past decade has seen increased interest from the scientific community, and particularly plant biologists, in integrating metabolic approaches into research aimed at unraveling phenotypic diversity and its underlying genetic variation. Advances in plant metabolomics have enabled large-scale analyses that have identified qualitative and quantitative variation in the metabolic content of various species, and this variation has been linked to genetic factors through genetic-mapping approaches, providing a glimpse of the genetic architecture of the plant metabolome. Parallel analyses of morphological phenotypes and physiological performance characteristics have further enhanced our understanding of the complex molecular mechanisms regulating these quantitative traits. This review aims to illustrate the advantages of including assessments of phenotypic and metabolic diversity in investigations of the genetic basis of complex traits, and the value of this approach in studying agriculturally important crops. We highlight the ground-breaking work on model species and discuss recent achievements in important crop species.

Stress adaptation of Saccharomyces cerevisiae as monitored via metabolites using two-dimensional NMR spectroscopy

Many studies on yeast metabolism are focused on its response to specific stress conditions because the results can be extended to the human medical issues. Most of those works have been accomplished through functional genomics studies. However, these changes may not show a linear correlation with protein or metabolite levels. For many organisms including yeast, the number of metabolites is far fewer than that of genes or gene products. Thus, metabolic profiling can provide a simpler yet efficient snapshot of the system's physiology. Metabolites of Saccharomyces cerevisiae under various stresses were analyzed and compared with those under the normal, unstressed growth conditions by two-dimensional NMR spectroscopy. At least 31 metabolites were identified for most of the samples. The levels of many identified metabolites showed significant increase or decrease depending on the nature of the stress. The statistical analysis produced a holistic view: different stresses were clustered and isolated from one another with the exception of high pH, heat, and oxidative stresses. This work could provide a link between the metabolite profiles and mRNA or protein profiles under representative and well-studied stress conditions.

Metabolite profiling reveals novel multi-level cold responses in the diploid model Fragaria vesca (woodland strawberry)

Winter freezing damage is a crucial factor in overwintering crops such as the octoploid strawberry (Fragaria × ananassa Duch.) when grown in a perennial cultivation system. Our study aimed at assessing metabolic processes and regulatory mechanisms in the close-related diploid model woodland strawberry (Fragaria vescaL.) during a 10-days cold acclimation experiment. Based on gas chromatography/time-of-flight-mass spectrometry (GC/TOF-MS) metabolite profiling of three F. vesca genotypes, clear distinctions could be made between leaves and non-photosynthesizing roots, underscoring the evolvement of organ-dependent cold acclimation strategies. Carbohydrate and amino acid metabolism, photosynthetic acclimation, and antioxidant and detoxification systems (ascorbate pathway) were strongly affected. Metabolic changes in F. vesca included the strong modulation of central metabolism, and induction of osmotically-active sugars (fructose, glucose), amino acids (aspartic acid), and amines (putrescine). In contrast, a distinct impact on the amino acid proline, known to be cold-induced in other plant systems, was conspicuously absent. Levels of galactinol and raffinose, key metabolites of the cold-inducible raffinose pathway, were drastically enhanced in both leaves and roots throughout the cold acclimation period of 10 days. Furthermore, initial freezing tests and multifaceted GC/TOF-MS data processing (Venn diagrams, independent component analysis, hierarchical clustering) showed that changes in metabolite pools of cold-acclimated F. vesca were clearly influenced by genotype.

Functional genomics tools applied to plant metabolism: a survey on plant respiration, its connections and the annotation of complex gene functions

The application of post-genomic techniques in plant respiration studies has greatly improved our ability to assign functions to gene products. In addition it has also revealed previously unappreciated interactions between distal elements of metabolism. Such results have reinforced the need to consider plant respiratory metabolism as part of a complex network and making sense of such interactions will ultimately require the construction of predictive and mechanistic models. Transcriptomics, proteomics, metabolomics, and the quantification of metabolic flux will be of great value in creating such models both by facilitating the annotation of complex gene function, determining their structure and by furnishing the quantitative data required to test them. In this review, we highlight how these experimental approaches have contributed to our current understanding of plant respiratory metabolism and its interplay with associated process (e.g., photosynthesis, photorespiration, and nitrogen metabolism). We also discuss how data from these techniques may be integrated, with the ultimate aim of identifying mechanisms that control and regulate plant respiration and discovering novel gene functions with potential biotechnological implications.

GabiPD - The GABI Primary Database integrates plant proteomic data with gene-centric information

GabiPD is an integrative plant "omics" database that has been established as part of the German initiative for Genome Analysis of the Plant Biological System (GABI). Data from different "omics" disciplines are integrated and interactively visualized. Proteomics is represented by data and tools aiding studies on the identification of post-translational modification and function of proteins. Annotated 2D electrophoresis-gel images are offered to inspect protein sets expressed in different tissues of Arabidopsis thaliana and Brassica napus. From a given protein spot, a link will direct the user to the related GreenCard Gene entry where detailed gene-centric information will support the functional annotation. Beside MapMan- and GO-classification, information on conserved protein domains and on orthologs is integrated in this GreenCard service. Moreover, all other GabiPD data related to the gene, including transcriptomic data, as well as gene-specific links to external resources are provided. Researches interested in plant protein phosphorylation will find information on potential MAP kinase substrates identified in different protein microarray studies integrated in GabiPD's Phosphoproteomics page. These data can be easily compared to experimentally identified or predicted phosphorylation sites in PhosPhAt via the related Gene GreenCard. This will allow the selection of interesting candidates for further experimental validation of their phosphorylation.

Unraveling retrograde signaling pathways: finding candidate signaling molecules via metabolomics and systems biology driven approaches

A tight coordination of biological processes between cellular compartments and organelles is crucial for the survival of any eukaryotic organism. According to cellular requirements, signals can be generated within organelles, such as chloroplasts and mitochondria, modulating the nuclear gene expression in a process called retrograde signaling. Whilst many research efforts have been focused on dissecting retrograde signaling pathways using biochemical and genetics approaches, metabolomics and systems biology driven studies have illustrated their great potential for hypotheses generation and for dissecting signaling networks in a rather unbiased or untargeted fashion. Recently, integrative genomics approaches, in which correlation analysis has been applied on transcript and metabolite profiling data of Arabidopsis thaliana, revealed the identification of metabolites which are putatively acting as mediators of nuclear gene expression. Complimentary, the continuous technological developments in the field of metabolomics per se has further demonstrated its potential as a very suitable readout to unravel metabolite-mediated signaling processes. As foundation for these studies here we outline and discuss recent advances in elucidating retrograde signaling molecules and pathways with an emphasis on metabolomics and systems biology driven approaches.

Perspectives on Systematic Analyses of Gene Function in Arabidopsis thaliana: New Tools, Topics and Trends

Since the sequencing of the nuclear genome of Arabidopsis thaliana ten years ago, various large-scale analyses of gene function have been performed in this model species. In particular, the availability of collections of lines harbouring random T-DNA or transposon insertions, which include mutants for almost all of the ~27,000 A. thaliana genes, has been crucial for the success of forward and reverse genetic approaches. In the foreseeable future, genome-wide phenotypic data from mutant analyses will become available for Arabidopsis, and will stimulate a flood of novel in-depth gene-function analyses. In this review, we consider the present status of resources and concepts for systematic studies of gene function in A. thaliana. Current perspectives on the utility of loss-of-function and gain-of-function mutants will be discussed in light of the genetic and functional redundancy of many A. thaliana genes.

Arabidopsis roots and shoots show distinct temporal adaptation patterns toward nitrogen starvation

Nitrogen (N) is an essential macronutrient for plants. N levels in soil vary widely, and plants have developed strategies to cope with N deficiency. However, the regulation of these adaptive responses and the coordinating signals that underlie them are still poorly understood. The aim of this study was to characterize N starvation in adult Arabidopsis (Arabidopsis thaliana) plants in a spatiotemporal manner by an integrative, multilevel global approach analyzing growth, metabolites, enzyme activities, and transcript levels. We determined that the remobilization of N and carbon compounds to the growing roots occurred long before the internal N stores became depleted. A global metabolite analysis by gas chromatography-mass spectrometry revealed organ-specific differences in the metabolic adaptation to complete N starvation, for example, for several tricarboxylic acid cycle intermediates, but also for carbohydrates, secondary products, and phosphate. The activities of central N metabolism enzymes and the capacity for nitrate uptake adapted to N starvation by favoring N remobilization and by increasing the high-affinity nitrate uptake capacity after long-term starvation. Changes in the transcriptome confirmed earlier studies and added a new dimension by revealing specific spatiotemporal patterns and several unknown N starvation-regulated genes, including new predicted small RNA genes. No global correlation between metabolites, enzyme activities, and transcripts was evident. However, this multilevel spatiotemporal global study revealed numerous new patterns of adaptation mechanisms to N starvation. In the context of a sustainable agriculture, this work will give new insight for the production of crops with increased N use efficiency.

Protein degradation - an alternative respiratory substrate for stressed plants

In cellular circumstances under which carbohydrates are scarce, plants can metabolize proteins and lipids as alternative respiratory substrates. Respiration of protein is less efficient than that of carbohydrate as assessed by the respiratory quotient; however, under certain adverse conditions, it represents an important alternative energy source for the cell. Significant effort has been invested in understanding the regulation of protein degradation in plants. This has included an investigation of how proteins are targeted to the proteosome, and the processes of senescence and autophagy. Here we review these events with particular reference to amino acid catabolism and its role in supporting the tricarboxylic acid cycle and direct electron supply to the ubiquinone pool of the mitochondrial electron transport chain in plants.

BYPASS1: synthesis of the mobile root-derived signal requires active root growth and arrests early leaf development

BACKGROUND

The Arabidopsis bypass1 (bps1) mutant root produces a biologically active mobile compound that induces shoot growth arrest. However it is unknown whether the root retains the capacity to synthesize the mobile compound, or if only shoots of young seedlings are sensitive. It is also unknown how this compound induces arrest of shoot growth. This study investigated both of these questions using genetic, inhibitor, reporter gene, and morphological approaches.

RESULTS

Production of the bps1 root-synthesized mobile compound was found to require active root growth. Inhibition of postembryonic root growth, by depleting glutathione either genetically or chemically, allowed seedlings to escape shoot arrest. However, the treatments were not completely effective, as the first leaf pair remained radialized, but elongated. This result indicated that the embryonic root transiently synthesized a small amount of the mobile substance. In addition, providing glutathione later in vegetative development caused shoot growth arrest to be reinstated, revealing that these late-arising roots were still capable of producing the mobile substance, and that the older vegetative leaves were still responsive. To gain insight into how leaf development responds to the mobile signal, leaf development was followed morphologically and using the CYCB1,1::GUS marker for G2/M phase cells. We found that arrest of leaf growth is a fully penetrant phenotype, and a dramatic decrease in G2/M phase cells was coincident with arrest. Analyses of stress phenotypes found that late in development, bps1 cotyledons produced necrotic lesions, however neither hydrogen peroxide nor superoxide were abundant as leaves underwent arrest.

CONCLUSIONS

bps1 roots appear to require active growth in order to produce the mobile bps1 signal, but the potential for this compound's synthesis is present both early and late during vegetative development. This prolonged capacity to synthesize and respond to the mobile compound is consistent with a possible role for the mobile compound in linking shoot growth to subterranean conditions. The specific growth-related responses in the shoot indicated that the mobile substance prevents full activation of cell division in leaves, although whether cell division is a direct response remains to be determined.

Analysis of the compartmentalized metabolome - a validation of the non-aqueous fractionation technique

With the development of high-throughput metabolic technologies, a plethora of primary and secondary compounds have been detected in the plant cell. However, there are still major gaps in our understanding of the plant metabolome. This is especially true with regards to the compartmental localization of these identified metabolites. Non-aqueous fractionation (NAF) is a powerful technique for the determination of subcellular metabolite distributions in eukaryotic cells, and it has become the method of choice to analyze the distribution of a large number of metabolites concurrently. However, the NAF technique produces a continuous gradient of metabolite distributions, not discrete assignments. Resolution of these distributions requires computational analyses based on marker molecules to resolve compartmental localizations. In this article we focus on expanding the computational analysis of data derived from NAF. Along with an experimental workflow, we describe the critical steps in NAF experiments and how computational approaches can aid in assessing the quality and robustness of the derived data. For this, we have developed and provide a new version (v1.2) of the BestFit command line tool for calculation and evaluation of subcellular metabolite distributions. Furthermore, using both simulated and experimental data we show the influence on estimated subcellular distributions by modulating important parameters, such as the number of fractions taken or which marker molecule is selected. Finally, we discuss caveats and benefits of NAF analysis in the context of the compartmentalized metabolome.