AtMetExpress development: a phytochemical atlas of Arabidopsis development

The rolB gene activates secondary metabolism in Arabidopsis calli via selective activation of genes encoding MYB and bHLH transcription factors

It is known that the rolB gene of Agrobacterium rhizogenes increases the production of secondary metabolites in transformed plant cells, but its mechanism of action remains unclear. In this report, we demonstrate that rolB expression in Arabidopsis thaliana calli led to the activation of most genes encoding secondary metabolism-specific MYB and bHLH transcription factors (TFs), such as MYB11, MYB12, MYB28, MYB76, MYB34, MYB51, MYB122, TT2 and TT8. Accordingly, a higher transcript abundance of main biosynthetic genes related to these factors was detected. The rolB-transformed calli produced 3-fold higher levels of indolic glucosinolates (GSs) compared with normal calli but did not produce secondary metabolites from other groups. Enhanced accumulation of indolic GSs was caused by activation of MYB34, MYB51 and MYB122, and the absence of aliphatic GSs in transformed calli was caused by the inability of rolB to induce MYB29. The inability of rolB-calli to produce flavonoids was caused by the lack of MYB111 expression, induced by the rolB-mediated conversion of MYB expression from cotyledon-specific to root-specific patterns. The high specificity of rolB on secondary metabolism-specific TFs was demonstrated for the first time.

Complementarity of medium-throughput in situ RNA hybridization and tissue-specific transcriptomics: case study of Arabidopsis seed development kinetics

The rationale of this study is to compare and integrate two heterologous datasets intended to unravel the spatiotemporal specificities of gene expression in a rapidly growing and complex organ. We implemented medium-throughput RNA in situ hybridization (ISH) for 39 genes mainly corresponding to cell wall proteins for which we have particular interest, selected (i) on their sequence identity (24 class III peroxidase multigenic family members and 15 additional genes used as positive controls) and (ii) on their expression levels in a publicly available Arabidopsis thaliana seed tissue-specific transcriptomics study. The specificity of the hybridization signals was carefully studied, and ISH results obtained for the 39 selected genes were systematically compared with tissue-specific transcriptomics for 5 seed developmental stages. Integration of results illustrates the complementarity of both datasets. The tissue-specific transcriptomics provides high-throughput possibilities whereas ISH provides high spatial resolution. Moreover, depending on the tissues and the developmental stages considered, one or the other technique appears more sensitive than the other. For each tissue/developmental stage, we finally determined tissue-specific transcriptomic threshold values compatible with the spatiotemporally-specific detection limits of ISH for lists of hundreds to tens-of-thousands of genes.

iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination

Efficient and accurate quantitation of metabolites from LC-MS data has become an important topic. Here we present an automated tool, called iMet-Q (intelligent Metabolomic Quantitation), for label-free metabolomics quantitation from high-throughput MS1 data. By performing peak detection and peak alignment, iMet-Q provides a summary of quantitation results and reports ion abundance at both replicate level and sample level. Furthermore, it gives the charge states and isotope ratios of detected metabolite peaks to facilitate metabolite identification. An in-house standard mixture and a public Arabidopsis metabolome data set were analyzed by iMet-Q. Three public quantitation tools, including XCMS, MetAlign, and MZmine 2, were used for performance comparison. From the mixture data set, seven standard metabolites were detected by the four quantitation tools, for which iMet-Q had a smaller quantitation error of 12% in both profile and centroid data sets. Our tool also correctly determined the charge states of seven standard metabolites. By searching the mass values for those standard metabolites against Human Metabolome Database, we obtained a total of 183 metabolite candidates. With the isotope ratios calculated by iMet-Q, 49% (89 out of 183) metabolite candidates were filtered out. From the public Arabidopsis data set reported with two internal standards and 167 elucidated metabolites, iMet-Q detected all of the peaks corresponding to the internal standards and 167 metabolites. Meanwhile, our tool had small abundance variation (≤ 0.19) when quantifying the two internal standards and had higher abundance correlation (≥ 0.92) when quantifying the 167 metabolites. iMet-Q provides user-friendly interfaces and is publicly available for download at http://ms.iis.sinica.edu.tw/comics/Software_iMet-Q.html.

Accumulation of Flavonols over Hydroxycinnamic Acids Favors Oxidative Damage Protection under Abiotic Stress

Efficient detoxification of reactive oxygen species (ROS) is thought to play a key role in enhancing the tolerance of plants to abiotic stresses. Although multiple pathways, enzymes, and antioxidants are present in plants, their exact roles during different stress responses remain unclear. Here, we report on the characterization of the different antioxidant mechanisms of tomato plants subjected to heat stress, salinity stress, or a combination of both stresses. All the treatments applied induced an increase of oxidative stress, with the salinity treatment being the most aggressive, resulting in plants with the lowest biomass, and the highest levels of H2O2 accumulation, lipid peroxidation, and protein oxidation. However, the results obtained from the transcript expression study and enzymatic activities related to the ascorbate-glutathione pathway did not fully explain the differences in the oxidative damage observed between salinity and the combination of salinity and heat. An exhaustive metabolomics study revealed the differential accumulation of phenolic compounds depending on the type of abiotic stress applied. An analysis at gene and enzyme levels of the phenylpropanoid metabolism concluded that under conditions where flavonols accumulated to a greater degree as compared to hydroxycinnamic acids, the oxidative damage was lower, highlighting the importance of flavonols as powerful antioxidants, and their role in abiotic stress tolerance.

Omics data input for metabolic modeling

Recent advancements in high-throughput large-scale analytical methods to sequence genomes of organisms, and to quantify gene expression, proteins, lipids and metabolites have changed the paradigm of metabolic modeling. The cost of data generation and analysis has decreased significantly, which has allowed exponential increase in the amount of omics data being generated for an organism in a very short time. Compared to progress made in microbial metabolic modeling, plant metabolic modeling still remains limited due to its complex genomes and compartmentalization of metabolic reactions. Herein, we review and discuss different omics-datasets with potential application in the functional genomics. In particular, this review focuses on the application of omics-datasets towards construction and reconstruction of plant metabolic models.

Atmospheric H2S and SO2 as sulfur source for Brassica juncea and Brassica rapa: impact on the glucosinolate composition

The impact of sulfate deprivation and atmospheric H2S and SO2 nutrition on the content and composition of glucosinolates was studied in Brassica juncea and B. rapa. Both species contained a number of aliphatic, aromatic and indolic glucosinolates. The total glucosinolate content was more than 5.5-fold higher in B. juncea than in B. rapa, which could solely be attributed to the presence of high levels of sinigrin, which was absent in the latter species. Sulfate deprivation resulted in a strong decrease in the content and an altered composition of the glucosinolates of both species. Despite the differences in patterns in foliarly uptake and metabolism, their exposure hardly affected the glucosinolate composition of the shoot, both at sulfate-sufficient and sulfate-deprived conditions. This indicated that the glucosinolate composition in the shoot was hardly affected by differences in sulfur source (viz., sulfate, sulfite and sulfide). Upon sulfate deprivation, where foliarly absorbed H2S and SO2 were the sole sulfur source for growth, the glucosinolate composition of roots differed from sulfate-sufficient B. juncea and B. rapa, notably the fraction of the indolic glucosinolates was lower than that observed in sulfur-sufficient roots.

Metabolic acclimation of source and sink tissues to salinity stress in bermudagrass (Cynodon dactylon)

Salinity is one of the major environmental factors affecting plant growth and survival by modifying source and sink relationships at physiological and metabolic levels. Individual metabolite levels and/or ratios in sink and source tissues may reflect the complex interplay of metabolic activities in sink and source tissues at the whole-plant level. We used a non-targeted gas chromatography-mass spectrometry (GC-MS) approach to study sink and source tissue-specific metabolite levels and ratios from bermudagrass under salinity stress. Shoot growth rate decreased while root growth rate increased which lead to an increased root/shoot growth rate ratio under salt stress. A clear shift in soluble sugars (sucrose, glucose and fructose) and metabolites linked to nitrogen metabolism (glutamate, aspartate and asparagine) in favor of sink roots was observed, when compared with sink and source leaves. The higher shifts in soluble sugars and metabolites linked to nitrogen metabolism in favor of sink roots may contribute to the root sink strength maintenance that facilitated the recovery of the functional equilibrium between shoot and root, allowing the roots to increase competitive ability for below-ground resource capture. This trait could be considered in breeding programs for increasing salt tolerance, which would help maintain root functioning (i.e. water and nutrient absorption, Na⁺ exclusion) and adaptation to stress.

Modern plant metabolomics: advanced natural product gene discoveries, improved technologies, and future prospects

Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This review covers the approximate period of 2000 to 2014, and highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR for metabolite identifications, and X-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine.

Introduction of chemically labile substructures into Arabidopsis lignin through the use of LigD, the Cα-dehydrogenase from Sphingobium sp. strain SYK-6

Bacteria-derived enzymes that can modify specific lignin substructures are potential targets to engineer plants for better biomass processability. The Gram-negative bacterium Sphingobium sp. SYK-6 possesses a Cα-dehydrogenase (LigD) enzyme that has been shown to oxidize the α-hydroxy functionalities in β-O-4-linked dimers into α-keto analogues that are more chemically labile. Here, we show that recombinant LigD can oxidize an even wider range of β-O-4-linked dimers and oligomers, including the genuine dilignols, guaiacylglycerol-β-coniferyl alcohol ether and syringylglycerol-β-sinapyl alcohol ether. We explored the possibility of using LigD for biosynthetically engineering lignin by expressing the codon-optimized ligD gene in Arabidopsis thaliana. The ligD cDNA, with or without a signal peptide for apoplast targeting, has been successfully expressed, and LigD activity could be detected in the extracts of the transgenic plants. UPLC-MS/MS-based metabolite profiling indicated that levels of oxidized guaiacyl (G) β-O-4-coupled dilignols and analogues were significantly elevated in the LigD transgenic plants regardless of the signal peptide attachment to LigD. In parallel, 2D NMR analysis revealed a 2.1- to 2.8-fold increased level of G-type α-keto-β-O-4 linkages in cellulolytic enzyme lignins isolated from the stem cell walls of the LigD transgenic plants, indicating that the transformation was capable of altering lignin structure in the desired manner.

Nicotinate O-Glucosylation Is an Evolutionarily Metabolic Trait Important for Seed Germination under Stress Conditions in Arabidopsis thaliana

The glycosylation of nicotinate (NA), a key intermediate of the NAD salvage pathway, occurs widely in land plants. However, the physiological function of NA glycosylation is not well understood in planta, and no gene encoding NA glycosyltransferase has been reported to date. NA glycosylation in Arabidopsis thaliana occurs at either the N- or the O-position of the NA molecule, and O-glucosylation appears to be unique to the Brassicaceae. Using gene-enzyme correlations focused on Family 1 glycosyltransferases (GTs; EC 2.4), we identified and characterized three Arabidopsis GTs, which are likely involved in NA glycosylation. These include one NAOGT (UGT74F2; previously identified as a salicylic acid glycosyltransferases) and two NANGTs (UGT76C4 and UGT76C5). Arabidopsis mutants of UGT74F2 accumulate higher levels of free NA, but not salicylic acid, than that of the wild type, and this inversely correlated with seed germination rates under various abiotic stresses. The germination defect of the ugt74f2-1 mutant could be fully complemented by overexpression of UGT74F2. These observations, together with comprehensive chemical analysis, suggest that NA glycosylation may function to protect plant cells from the toxicity of NA overaccumulation during seed germination. Combined with phylogenetic analysis, our results suggest that NAOGTs arose recently in the Brassicaceae family and may provide a fitness benefit. The multifunctionality of UGT74F2 in Arabidopsis is also investigated and discussed.

Metabolome-genome-wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism

Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications.

Metabolic fingerprinting of Arabidopsis thaliana accessions

In the post-genomic era much effort has been put on the discovery of gene function using functional genomics. Despite the advances achieved by these technologies in the understanding of gene function at the genomic and proteomic level, there is still a big genotype-phenotype gap. Metabolic profiling has been used to analyze organisms that have already been characterized genetically. However, there is a small number of studies comparing the metabolic profile of different tissues of distinct accessions. Here, we report the detection of over 14,000 and 17,000 features in inflorescences and leaves, respectively, in two widely used Arabidopsis thaliana accessions. A predictive Random Forest Model was developed, which was able to reliably classify tissue type and accession of samples based on LC-MS profile. Thereby we demonstrate that the morphological differences among A. thaliana accessions are reflected also as distinct metabolic phenotypes within leaves and inflorescences.

Profiling of secondary metabolites in root exudates of Arabidopsis thaliana

To explore the chemical composition of root exudates of the model plant Arabidopsis thaliana a workflow for nontargeted metabolite profiling of the semipolar fraction of root exudates was developed. It comprises hydroponic plant cultivation and sampling of root exudates under sterile conditions, sample preparation by solid-phase extraction and analysis by reversed-phase UPLC/ESI-QTOFMS. Following the established workflow, root exudates of six-week-old plants were profiled and a set of reproducibly occurring molecular features was compiled. To structurally elucidate the corresponding metabolites, accurate mass tandem mass spectrometry and on-line hydrogen/deuterium exchange were applied. Currently, a total of 103 compounds were detected and annotated by elemental composition of which more than 90 were structurally characterized or classified. Among them, 42 compounds were rigorously identified using an authenticated standard. The compounds identified so far include nucleosides, deoxynucleosides, aromatic amino acids, anabolites and catabolites of glucosinolates, dipeptides, indolics, salicylic and jasmonic acid catabolites, coumarins, mono-, di- and trilignols, hydroxycinnamic acid derivatives and oxylipins and exemplify the high chemical diversity of plant root exudates.

Revealing insect herbivory-induced phenolamide metabolism: from single genes to metabolic network plasticity analysis

The phenylpropanoid metabolic space comprises a network of interconnected metabolic branches that contribute to the biosynthesis of a large array of compounds with functions in plant development and stress adaptation. During biotic challenges, such as insect attack, a major rewiring of gene networks associated with phenylpropanoid metabolism is observed. This rapid reconfiguration of gene expression allows prioritized production of metabolites that help the plant solve ecological problems. Phenolamides are a group of phenolic derivatives that originate from diversion of hydroxycinnamoyl acids from the main phenylpropanoid pathway after N-acyltransferase-dependent conjugation to polyamines or aryl monoamines. These structurally diverse metabolites are abundant in the reproductive organs of many plants, and have recently been shown to play roles as induced defenses in vegetative tissues. In the wild tobacco, Nicotiana attenuata, in which herbivory-induced regulation of these metabolites has been studied, rapid elevations of the levels of phenolamides that function as induced defenses result from a multi-hormonal signaling network that re-shapes connected metabolic pathways. In this review, we summarize recent findings in the regulation of phenolamides obtained by mass spectrometry-based metabolomics profiling, and outline a conceptual framework for gene discovery in this pathway. We also introduce a multifactorial approach that is useful in deciphering metabolic pathway reorganizations among tissues in response to stress.

Metabolome analysis of Arabidopsis thaliana roots identifies a key metabolic pathway for iron acquisition

Fe deficiency compromises both human health and plant productivity. Thus, it is important to understand plant Fe acquisition strategies for the development of crop plants which are more Fe-efficient under Fe-limited conditions, such as alkaline soils, and have higher Fe density in their edible tissues. Root secretion of phenolic compounds has long been hypothesized to be a component of the reduction strategy of Fe acquisition in non-graminaceous plants. We therefore subjected roots of Arabidopsis thaliana plants grown under Fe-replete and Fe-deplete conditions to comprehensive metabolome analysis by gas chromatography-mass spectrometry and ultra-pressure liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry. Scopoletin and other coumarins were found among the metabolites showing the strongest response to two different Fe-limited conditions, the cultivation in Fe-free medium and in medium with an alkaline pH. A coumarin biosynthesis mutant defective in ortho-hydroxylation of cinnamic acids was unable to grow on alkaline soil in the absence of Fe fertilization. Co-cultivation with wild-type plants partially rescued the Fe deficiency phenotype indicating a contribution of extracellular coumarins to Fe solubilization. Indeed, coumarins were detected in root exudates of wild-type plants. Direct infusion mass spectrometry as well as UV/vis spectroscopy indicated that coumarins are acting both as reductants of Fe(III) and as ligands of Fe(II).

Phenolic characterization and variability in leaves, stems and roots of Micro-Tom and patio tomatoes, in response to nitrogen limitation

Phenolics are implicated in the defence strategies of many plant species rendering their concentration increase of putative practical interest in the field of crop protection. Little attention has been given to the nature, concentration and distribution of phenolics within vegetative organs of tomato (Solanum lycopersicum. L) as compared to fruits. In this study, we extensively characterized the phenolics in leaves, stems and roots of nine tomato cultivars using high-performance liquid chromatography coupled to electrospray ionization tandem mass spectrometry (LC-MS(n)) and assessed the impact of low nitrogen (LN) availability on their accumulation. Thirty-one phenolics from the four sub-classes, hydroxycinnamoyl esters, flavonoids, anthocyanins and phenolamides were identified, five of which had not previously been reported in these tomato organs. A higher diversity and concentration of phenolics was found in leaves than in stems and roots. The qualitative distribution of these compounds between plant organs was similar for the nine cultivars with the exception of Micro-Tom because of its significantly higher phenolic concentrations in leaves and stems as compared to roots. With few exceptions, the influence of the LN treatment on the three organs of all cultivars was to increase the concentrations of hydroxycinnamoyl esters, flavonoids and anthocyanins and to decrease those of phenolamides. This impact of LN was greater in roots than in leaves and stems. Nitrogen nutrition thus appears as a means of modulating the concentration and composition of organ phenolics and their distribution within the whole plant.

Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism

Plant metabolites are important to world food security in terms of maintaining sustainable yield and providing food with enriched phytonutrients. Here we report comprehensive profiling of 840 metabolites and a further metabolic genome-wide association study based on ∼6.4 million SNPs obtained from 529 diverse accessions of Oryza sativa. We identified hundreds of common variants influencing numerous secondary metabolites with large effects at high resolution. We observed substantial heterogeneity in the natural variation of metabolites and their underlying genetic architectures among different subspecies of rice. Data mining identified 36 candidate genes modulating levels of metabolites that are of potential physiological and nutritional importance. As a proof of concept, we functionally identified or annotated five candidate genes influencing metabolic traits. Our study provides insights into the genetic and biochemical bases of rice metabolome variation and can be used as a powerful complementary tool to classical phenotypic trait mapping for rice improvement.

Systematic structural characterization of metabolites in Arabidopsis via candidate substrate-product pair networks

Plant metabolomics is increasingly used for pathway discovery and to elucidate gene function. However, the main bottleneck is the identification of the detected compounds. This is more pronounced for secondary metabolites as many of their pathways are still underexplored. Here, an algorithm is presented in which liquid chromatography-mass spectrometry profiles are searched for pairs of peaks that have mass and retention time differences corresponding with those of substrates and products from well-known enzymatic reactions. Concatenating the latter peak pairs, called candidate substrate-product pairs (CSPP), into a network displays tentative (bio)synthetic routes. Starting from known peaks, propagating the network along these routes allows the characterization of adjacent peaks leading to their structure prediction. As a proof-of-principle, this high-throughput cheminformatics procedure was applied to the Arabidopsis thaliana leaf metabolome where it allowed the characterization of the structures of 60% of the profiled compounds. Moreover, based on searches in the Chemical Abstract Service database, the algorithm led to the characterization of 61 compounds that had never been described in plants before. The CSPP-based annotation was confirmed by independent MS(n) experiments. In addition to being high throughput, this method allows the annotation of low-abundance compounds that are otherwise not amenable to isolation and purification. This method will greatly advance the value of metabolomics in systems biology.

Enhancement of oxidative and drought tolerance in Arabidopsis by overaccumulation of antioxidant flavonoids

The notion that plants use specialized metabolism to protect against environmental stresses needs to be experimentally proven by addressing the question of whether stress tolerance by specialized metabolism is directly due to metabolites such as flavonoids. We report that flavonoids with radical scavenging activity mitigate against oxidative and drought stress in Arabidopsis thaliana. Metabolome and transcriptome profiling and experiments with oxidative and drought stress in wild-type, single overexpressors of MYB12/PFG1 (PRODUCTION OF FLAVONOL GLYCOSIDES1) or MYB75/PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT1), double overexpressors of MYB12 and PAP1, transparent testa4 (tt4) as a flavonoid-deficient mutant, and flavonoid-deficient MYB12 or PAP1 overexpressing lines (obtained by crossing tt4 and the individual MYB overexpressor) demonstrated that flavonoid overaccumulation was key to enhanced tolerance to such stresses. Antioxidative activity assays using 2,2-diphenyl-1-picrylhydrazyl, methyl viologen, and 3,3'-diaminobenzidine clearly showed that anthocyanin overaccumulation with strong in vitro antioxidative activity mitigated the accumulation of reactive oxygen species in vivo under oxidative and drought stress. These data confirm the usefulness of flavonoids for enhancing both biotic and abiotic stress tolerance in crops.

Expression of PRX36, PMEI6 and SBT1.7 is controlled by complex transcription factor regulatory networks for proper seed coat mucilage extrusion

Mucilage secretory cells (MSC) form an intriguing cell layer important for seed germination. In Arabidopsis thaliana, several master transcription factors (TFs) and "actor" proteins have already been identified as key players for seed coat differentiation including epidermal cell formation, mucilage production and extrusion. The regulation of the genes coding for MSC cell wall "actor" proteins by TFs needs to be better established. Here, the expression and the regulation of 3 known actors (PRX36, PMEI6, SBT1.7) and 2 additional putative actors (PRX56, DIR12) have been analyzed in T-DNA mutants affected in master TFs (ap2, egl3/gl3, gl2, myb5, tt8, ttg1, ttg2 and luh1/mum1). Genes with somehow similar function are differentially regulated and conversely, genes with different functions are regulated in similar manner.

Genomics and bioinformatics resources for translational science in Rosaceae

Recent technological advances in biology promise unprecedented opportunities for rapid and sustainable advancement of crop quality. Following this trend, the Rosaceae research community continues to generate large amounts of genomic, genetic and breeding data. These include annotated whole genome sequences, transcriptome and expression data, proteomic and metabolomic data, genotypic and phenotypic data, and genetic and physical maps. Analysis, storage, integration and dissemination of these data using bioinformatics tools and databases are essential to provide utility of the data for basic, translational and applied research. This review discusses the currently available genomics and bioinformatics resources for the Rosaceae family.

Alternation of flavonoid accumulation under drought stress in Arabidopsis thaliana

Plants have developed mechanisms to protect themselves against both biotic and abiotic environmental stress. Specialized/secondary metabolism is one of the stress response mechanisms. Recently, we reported that flavonoids, a class of specialized metabolites, including flavonols and anthocyanins with strong radical scavenging activity contributed to the mitigation of oxidative and drought stress in Arabidopsis thaliana (Arabidopsis). However, the behavior of flavonoids during drought stress is still not well-documented. Herein we investigated the time-series alternation of flavonoids in the aerial part of Arabidopsis (wild type, Col-0) during drought stress by LC-QTOF-MS. The drastic alternation of 5 flavonols and 5 anthocyanins was revealed together with changes in marker metabolites of drought stress, e.g., proline, raffinose, and galactinol. These findings indicate that flavonols and anthocyanins can mitigate drought stress.

A novel integrated method for large-scale detection, identification, and quantification of widely targeted metabolites: application in the study of rice metabolomics

Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics has been facilitated by the construction of MS(2) spectral tag (MS2T) library from the total scan ESI MS/MS data, and the development of widely targeted metabolomics method using MS/MS data gathered from authentic standards. In this report, a novel strategy called stepwise multiple ion monitoring-enhanced product ions (stepwise MIM-EPI) was developed to construct the MS2T library, in which stepwise MIM was used as survey scans to trigger the acquisition of EPI. A total number of 698 (almost) non-redundant metabolites with MS(2) spectra were obtained, of which 135 metabolites were identified/annotated. Integrating the data gathered from our MS2T library and other available multiple reaction monitoring (MRM) information, a widely targeted metabolomics method was developed to quantify 277 metabolites, including some phytohormones. Evaluation of the dehydration responses and natural variations of these metabolites in rice leaf not only suggested the coordinated regulation of abscisic acid (ABA) with metabolites such as serotonin derivative(s), polyamine conjugates under drought stress, but also revealed some C-glycosylated flavones as the potential markers for the discrimination of indica and japonica rice subspecies. The new MS2T library construction and widely targeted metabolomics strategy could be used as a tool for rice functional genomics.

The flavonoid biosynthetic pathway in Arabidopsis: structural and genetic diversity

Flavonoids are representative plant secondary products. In the model plant Arabidopsis thaliana, at least 54 flavonoid molecules (35 flavonols, 11 anthocyanins and 8 proanthocyanidins) are found. Scaffold structures of flavonoids in Arabidopsis are relatively simple. These include kaempferol, quercetin and isorhamnetin for flavonols, cyanidin for anthocyanins and epicatechin for proanthocyanidins. The chemical diversity of flavonoids increases enormously by tailoring reactions which modify these scaffolds, including glycosylation, methylation and acylation. Genes responsible for the formation of flavonoid aglycone structures and their subsequent modification reactions have been extensively characterized by functional genomic efforts - mostly the integration of transcriptomics and metabolic profiling followed by reverse genetic experimentation. This review describes the state-of-art of flavonoid biosynthetic pathway in Arabidopsis regarding both structural and genetic diversity, focusing on the genes encoding enzymes for the biosynthetic reactions and vacuole translocation.

Network analysis for gene discovery in plant-specialized metabolism

Recent omics technologies provide information on multiple components of biological networks. Web-based data mining tools are continuously being developed. Because genes involved in specialized (secondary) metabolism are often co-ordinately regulated at the transcriptional level, a number of gene discovery studies have been successfully conducted using network analysis, especially by integrating gene co-expression network analysis and metabolomic investigation. In addition, next-generation sequencing technologies are currently utilized in functional genomics investigations of Arabidopsis and non-model plant species including medicinal plants. Systems-based approaches are expected to gain importance in medicinal plant research. This review discussed network analysis in Arabidopsis and gene discovery in plant-specialized metabolism in non-model plants.

Integration of biosynthesis and long-distance transport establish organ-specific glucosinolate profiles in vegetative Arabidopsis

Although it is essential for plant survival to synthesize and transport defense compounds, little is known about the coordination of these processes. Here, we investigate the above- and belowground source-sink relationship of the defense compounds glucosinolates in vegetative Arabidopsis thaliana. In vivo feeding experiments demonstrate that the glucosinolate transporters1 and 2 (GTR1 and GTR2), which are essential for accumulation of glucosinolates in seeds, are likely to also be involved in bidirectional distribution of glucosinolates between the roots and rosettes, indicating phloem and xylem as their transport pathways. Grafting of wild-type, biosynthetic, and transport mutants show that both the rosette and roots are able to synthesize aliphatic and indole glucosinolates. While rosettes constitute the major source and storage site for short-chained aliphatic glucosinolates, long-chained aliphatic glucosinolates are synthesized both in roots and rosettes with roots as the major storage site. Our grafting experiments thus indicate that in vegetative Arabidopsis, GTR1 and GTR2 are involved in bidirectional long-distance transport of aliphatic but not indole glucosinolates. Our data further suggest that the distinct rosette and root glucosinolate profiles in Arabidopsis are shaped by long-distance transport and spatially separated biosynthesis, suggesting that integration of these processes is critical for plant fitness in complex natural environments.

Comprehensive dissection of spatiotemporal metabolic shifts in primary, secondary, and lipid metabolism during developmental senescence in Arabidopsis

Developmental senescence is a coordinated physiological process in plants and is critical for nutrient redistribution from senescing leaves to newly formed sink organs, including young leaves and developing seeds. Progress has been made concerning the genes involved and the regulatory networks controlling senescence. The resulting complex metabolome changes during senescence have not been investigated in detail yet. Therefore, we conducted a comprehensive profiling of metabolites, including pigments, lipids, sugars, amino acids, organic acids, nutrient ions, and secondary metabolites, and determined approximately 260 metabolites at distinct stages in leaves and siliques during senescence in Arabidopsis (Arabidopsis thaliana). This provided an extensive catalog of metabolites and their spatiotemporal cobehavior with progressing senescence. Comparison with silique data provides clues to source-sink relations. Furthermore, we analyzed the metabolite distribution within single leaves along the basipetal sink-source transition trajectory during senescence. Ceramides, lysolipids, aromatic amino acids, branched chain amino acids, and stress-induced amino acids accumulated, and an imbalance of asparagine/aspartate, glutamate/glutamine, and nutrient ions in the tip region of leaves was detected. Furthermore, the spatiotemporal distribution of tricarboxylic acid cycle intermediates was already changed in the presenescent leaves, and glucosinolates, raffinose, and galactinol accumulated in the base region of leaves with preceding senescence. These results are discussed in the context of current models of the metabolic shifts occurring during developmental and environmentally induced senescence. As senescence processes are correlated to crop yield, the metabolome data and the approach provided here can serve as a blueprint for the analysis of traits and conditions linking crop yield and senescence.

Comprehensive dissection of spatiotemporal metabolic shifts in primary, secondary, and lipid metabolism during developmental senescence in Arabidopsis

Developmental senescence is a coordinated physiological process in plants and is critical for nutrient redistribution from senescing leaves to newly formed sink organs, including young leaves and developing seeds. Progress has been made concerning the genes involved and the regulatory networks controlling senescence. The resulting complex metabolome changes during senescence have not been investigated in detail yet. Therefore, we conducted a comprehensive profiling of metabolites, including pigments, lipids, sugars, amino acids, organic acids, nutrient ions, and secondary metabolites, and determined approximately 260 metabolites at distinct stages in leaves and siliques during senescence in Arabidopsis (Arabidopsis thaliana). This provided an extensive catalog of metabolites and their spatiotemporal cobehavior with progressing senescence. Comparison with silique data provides clues to source-sink relations. Furthermore, we analyzed the metabolite distribution within single leaves along the basipetal sink-source transition trajectory during senescence. Ceramides, lysolipids, aromatic amino acids, branched chain amino acids, and stress-induced amino acids accumulated, and an imbalance of asparagine/aspartate, glutamate/glutamine, and nutrient ions in the tip region of leaves was detected. Furthermore, the spatiotemporal distribution of tricarboxylic acid cycle intermediates was already changed in the presenescent leaves, and glucosinolates, raffinose, and galactinol accumulated in the base region of leaves with preceding senescence. These results are discussed in the context of current models of the metabolic shifts occurring during developmental and environmentally induced senescence. As senescence processes are correlated to crop yield, the metabolome data and the approach provided here can serve as a blueprint for the analysis of traits and conditions linking crop yield and senescence.

Phytochemical genomics--a new trend

Phytochemical genomics is a recently emerging field, which investigates the genomic basis of the synthesis and function of phytochemicals (plant metabolites), particularly based on advanced metabolomics. The chemical diversity of the model plant Arabidopsis thaliana is larger than previously expected, and the gene-to-metabolite correlations have been elucidated mostly by an integrated analysis of transcriptomes and metabolomes. For example, most genes involved in the biosynthesis of flavonoids in Arabidopsis have been characterized by this method. A similar approach has been applied to the functional genomics for production of phytochemicals in crops and medicinal plants. Great promise is seen in metabolic quantitative loci analysis in major crops such as rice and tomato, and identification of novel genes involved in the biosynthesis of bioactive specialized metabolites in medicinal plants.

Integrated LC-MS/MS system for plant metabolomics

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is highly sensitive, selective, and enables extensive detection of metabolites within a sample. The result allows us to characterize comprehensive metabolite accumulation patterns without dependence on authentic standard compounds and isolation of the individual metabolites. A reference database search is essential for the structural assignment process of un-targeted MS and MS/MS data. Moreover, the characterization of unknown metabolites is challenging, since these cannot be assigned a candidate structure by using a reference database. In this case study, integrated LC-MS/MS based plant metabolomics allows us to detect several hundred metabolites in a sample; and integrated omics analyses, e.g., large-scale reverse genetics, linkage mapping, and association mapping, provides a powerful tool for candidate structure selection or rejection. We also examine emerging technology and applications for LC-MS/MS-based un-targeted plant metabolomics. These activities promote the characterization of massive extended detectable metabolites.

Coupling deep transcriptome analysis with untargeted metabolic profiling in Ophiorrhiza pumila to further the understanding of the biosynthesis of the anti-cancer alkaloid camptothecin and anthraquinones

The Rubiaceae species, Ophiorrhiza pumila, accumulates camptothecin, an anti-cancer alkaloid with a potent DNA topoisomerase I inhibitory activity, as well as anthraquinones that are derived from the combination of the isochorismate and hemiterpenoid pathways. The biosynthesis of these secondary products is active in O. pumila hairy roots yet very low in cell suspension culture. Deep transcriptome analysis was conducted in O. pumila hairy roots and cell suspension cultures using the Illumina platform, yielding a total of 2 Gb of sequence for each sample. We generated a hybrid transcriptome assembly of O. pumila using the Illumina-derived short read sequences and conventional Sanger-derived expressed sequence tag clones derived from a full-length cDNA library constructed using RNA from hairy roots. Among 35,608 non-redundant unigenes, 3,649 were preferentially expressed in hairy roots compared with cell suspension culture. Candidate genes involved in the biosynthetic pathway for the monoterpenoid indole alkaloid camptothecin were identified; specifically, genes involved in post-strictosamide biosynthetic events and genes involved in the biosynthesis of anthraquinones and chlorogenic acid. Untargeted metabolomic analysis by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) indicated that most of the proposed intermediates in the camptothecin biosynthetic pathway accumulated in hairy roots in a preferential manner compared with cell suspension culture. In addition, a number of anthraquinones and chlorogenic acid preferentially accumulated in hairy roots compared with cell suspension culture. These results suggest that deep transcriptome and metabolome data sets can facilitate the identification of genes and intermediates involved in the biosynthesis of secondary products including camptothecin in O. pumila.

Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK motorcycle database

Biology is increasingly becoming a data-intensive science with the recent progress of the omics fields, e.g. genomics, transcriptomics, proteomics and metabolomics. The species-metabolite relationship database, KNApSAcK Core, has been widely utilized and cited in metabolomics research, and chronological analysis of that research work has helped to reveal recent trends in metabolomics research. To meet the needs of these trends, the KNApSAcK database has been extended by incorporating a secondary metabolic pathway database called Motorcycle DB. We examined the enzyme sequence diversity related to secondary metabolism by means of batch-learning self-organizing maps (BL-SOMs). Initially, we constructed a map by using a big data matrix consisting of the frequencies of all possible dipeptides in the protein sequence segments of plants and bacteria. The enzyme sequence diversity of the secondary metabolic pathways was examined by identifying clusters of segments associated with certain enzyme groups in the resulting map. The extent of diversity of 15 secondary metabolic enzyme groups is discussed. Data-intensive approaches such as BL-SOM applied to big data matrices are needed for systematizing protein sequences. Handling big data has become an inevitable part of biology.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

Molecular biological data has rapidly increased with the recent progress of the Omics fields, e.g., genomics, transcriptomics, proteomics and metabolomics that necessitates the development of databases and methods for efficient storage, retrieval, integration and analysis of massive data. The present study reviews the usage of KNApSAcK Family DB in metabolomics and related area, discusses several statistical methods for handling multivariate data and shows their application on Indonesian blended herbal medicines (Jamu) as a case study. Exploration using Biplot reveals many plants are rarely utilized while some plants are highly utilized toward specific efficacy. Furthermore, the ingredients of Jamu formulas are modeled using Partial Least Squares Discriminant Analysis (PLS-DA) in order to predict their efficacy. The plants used in each Jamu medicine served as the predictors, whereas the efficacy of each Jamu provided the responses. This model produces 71.6% correct classification in predicting efficacy. Permutation test then is used to determine plants that serve as main ingredients in Jamu formula by evaluating the significance of the PLS-DA coefficients. Next, in order to explain the role of plants that serve as main ingredients in Jamu medicines, information of pharmacological activity of the plants is added to the predictor block. Then N-PLS-DA model, multiway version of PLS-DA, is utilized to handle the three-dimensional array of the predictor block. The resulting N-PLS-DA model reveals that the effects of some pharmacological activities are specific for certain efficacy and the other activities are diverse toward many efficacies. Mathematical modeling introduced in the present study can be utilized in global analysis of big data targeting to reveal the underlying biology.

PRIMe Update: innovative content for plant metabolomics and integration of gene expression and metabolite accumulation

PRIMe (http://prime.psc.riken.jp/), the Platform for RIKEN Metabolomics, is a website that was designed and implemented to support research and analyses ranging from metabolomics to transcriptomics. To achieve functional genomics and annotation of unknown metabolites, we established the following PRIMe contents: MS2T, a library comprising >1 million entries of untargeted tandem mass spectrometry (MS/MS) data of plant metabolites; AtMetExpress LC-MS, a database of transcriptomics and metabolomics approaches in Arabidopsis developmental stages (AtMetExpress Development LC-MS) and a data set of the composition of secondary metabolites among 20 Arabidopsis ecotypes (AtMetExpress 20 ecotypes LC-MS); and ReSpect, hybrid reference MS/MS data resources (acquisitions and literature). PRIMeLink is a new web application that allows access to the innovative data resources of PRIMe. The MS2T library was generated from a set of MS/MS spectra acquired using the automatic data acquisition function of mass spectrometry. To increase the understanding of mechanisms driving variations in metabolic profiles among plant tissues, we further provided the AtMetExpress Development LC-MS database in PRIMe, facilitating the investigation of relationships between gene expression and metabolite accumulation. This information platform therefore provides an integrative analysis resource by linking Arabidopsis transcriptome and metabolome data. Moreover, we developed the ReSpect database, a plant-specific MS/MS data resource, which allows users to identify candidate structures from the suite of complex phytochemical structures. Finally, we integrated the three databases into PRIMeLink and established a walk-through link between transcriptome and metabolome information. PRIMeLink offers a bi-directional searchable function, from the gene and the metabolite perspective, to search for targets seamlessly and effectively.

UniVIO: a multiple omics database with hormonome and transcriptome data from rice

Plant hormones play important roles as signaling molecules in the regulation of growth and development by controlling the expression of downstream genes. Since the hormone signaling system represents a complex network involving functional cross-talk through the mutual regulation of signaling and metabolism, a comprehensive and integrative analysis of plant hormone concentrations and gene expression is important for a deeper understanding of hormone actions. We have developed a database named Uniformed Viewer for Integrated Omics (UniVIO: http://univio.psc.riken.jp/), which displays hormone-metabolome (hormonome) and transcriptome data in a single formatted (uniformed) heat map. At the present time, hormonome and transcriptome data obtained from 14 organ parts of rice plants at the reproductive stage and seedling shoots of three gibberellin signaling mutants are included in the database. The hormone concentration and gene expression data can be searched by substance name, probe ID, gene locus ID or gene description. A correlation search function has been implemented to enable users to obtain information of correlated substance accumulation and gene expression. In the correlation search, calculation method, range of correlation coefficient and plant samples can be selected freely.

Current metabolomics: practical applications

The field of metabolomics continues to grow rapidly over the last decade and has been proven to be a powerful technology in predicting and explaining complex phenotypes in diverse biological systems. Metabolomics complements other omics, such as transcriptomics and proteomics and since it is a 'downstream' result of gene expression, changes in the metabolome is considered to best reflect the activities of the cell at a functional level. Thus far, metabolomics might be the sole technology capable of detecting complex, biologically essential changes. As one of the omics technology, metabolomics has exciting applications in varied fields, including medical science, synthetic biology, medicine, and predictive modeling of plant, animal and microbial systems. In addition, integrated applications with genomics, transcriptomics, and proteomics provide greater understanding of global system biology. In this review, we discuss recent applications of metabolomics in microbiology, plant, animal, food, and medical science.

Recent progress in the development of metabolome databases for plant systems biology

Metabolomics has grown greatly as a functional genomics tool, and has become an invaluable diagnostic tool for biochemical phenotyping of biological systems. Over the past decades, a number of databases involving information related to mass spectra, compound names and structures, statistical/mathematical models and metabolic pathways, and metabolite profile data have been developed. Such databases complement each other and support efficient growth in this area, although the data resources remain scattered across the World Wide Web. Here, we review available metabolome databases and summarize the present status of development of related tools, particularly focusing on the plant metabolome. Data sharing discussed here will pave way for the robust interpretation of metabolomic data and advances in plant systems biology.

Identification and analysis of an outer-seed-coat-specific promoter from Arabidopsis thaliana

Differentiation of the Arabidopsis thaliana (Arabidopsis) seed coat epidermal cells involves pronounced changes highlighted by the synthesis and secretion of copious amounts of dispensable, pectinaceous mucilage followed by a thick cellulosic secondary cell wall. This cell type, therefore, represents an excellent molecular-genetic model to study the biosynthesis and modification of cell wall components, particularly pectin. To support such research, we sought to identify a promoter that drives expression specifically in the Arabidopsis seed coat epidermis. Arabidopsis seed coat microarray data was analysed for genes expressed in the wild type seed coat but not the seed coat of the apetala2 mutant where the epidermal cells fail to differentiate. Of 14 candidate genes, 9 showed a seed-specific expression pattern by reverse transcriptase-PCR. Transcriptional regulatory region-β-glucuronidase (GUS) reporter gene fusions introduced into Arabidopsis identified one promoter, that of the DIRIGENT PROTEIN1 (DP1) gene, as seed coat specific. The specificity of the expression was confirmed using a second reporter gene, Citrine YFP. Expression of both reporter genes was limited to the epidermal and palisade cell layers of the seed coat. Quantitative PCR data using wild type seed coat RNA suggested that the promoter is particularly active at 7 days post anthesis. The DP1 promoter was able to direct transcription of GUS in a similar pattern in the Brassica napus seed coat. Thus, in addition to its application in studying the plant cell wall, this promoter will provide an experimental tool for expressing high-valued recombinant proteins as well as modifying seed coat traits in economically important crops.

A core set of metabolite sink/source ratios indicative for plant organ productivity in Lotus japonicus

Plant growth is an important process in physiological as well as ecological respect and a number of metabolic parameters (elemental ratios as well as steady-state levels of individual metabolites) have been demonstrated to reflect this process on the whole plant level. Since plant growth is highly localized and is the result of a complex interplay of metabolic activities in sink and source organs, we propose that ratios in metabolite levels of sink and source organs are particularly well suited to characterize this process. To demonstrate such a connection, we studied organ-specific metabolite ratios from Lotus japonicus treated with mineral nutrients, salt stress or arbuscular mycorrhizal fungi. The plants were displaying a wide range of biomass and of flower/biomass ratios. In the analysis of our data we looked for correlations between shifts in sink/source metabolite ratios and plant productivity (biomass accumulated at the time of harvest). In addition we correlated shifts in metabolite ratios comparing competing generative and vegetative sink organs with shifts in productivity of the two organs (changes in flower/biomass ratios). In our analyses we observed clear shifts of carbohydrates and of compounds connected to nitrogen metabolism in favour of sink organs of particularly high productivity. These shifts were in agreement with general differences in metabolite steady-state levels when comparing sink and source organs. Our findings suggest that differentiation of sink and source organs during sampling for metabolomic experiments substantially increases the amount of information obtained from such experiments.

Metabolic engineering of novel lignin in biomass crops

Lignin, a phenolic polymer in the secondary wall, is the major cause of lignocellulosic biomass recalcitrance to efficient industrial processing. From an applications perspective, it is desirable that second-generation bioenergy crops have lignin that is readily degraded by chemical pretreatments but still fulfill its biological role in plants. Because plants can tolerate large variations in lignin composition, often without apparent adverse effects, substitution of some fraction of the traditional monolignols by alternative monomers through genetic engineering is a promising strategy to tailor lignin in bioenergy crops. However, successful engineering of lignin incorporating alternative monomers requires knowledge about phenolic metabolism in plants and about the coupling properties of these alternative monomers. Here, we review the current knowledge about lignin biosynthesis and the pathways towards the main phenolic classes. In addition, the minimal requirements are defined for molecules that, upon incorporation into the lignin polymer, make the latter more susceptible to biomass pretreatment. Numerous metabolites made by plants meet these requirements, and several have already been tested as monolignol substitutes in biomimetic systems. Finally, the status of detection and identification of compounds by phenolic profiling is discussed, as phenolic profiling serves in pathway elucidation and for the detection of incorporation of alternative lignin monomers.

RIKEN tandem mass spectral database (ReSpect) for phytochemicals: a plant-specific MS/MS-based data resource and database

The fragment pattern analysis of tandem mass spectrometry (MS/MS) has long been used for the structural characterization of metabolites. The construction of a plant-specific MS/MS data resource and database will enable complex phytochemical structures to be narrowed down to candidate structures. Therefore, a web-based database of MS/MS data pertaining to phytochemicals was developed and named ReSpect (RIKEN tandem mass spectral database). Of the 3595 metabolites in ReSpect, 76% were derived from 163 literature reports, whereas the rest was obtained from authentic standards. As a main web application of ReSpect, a fragment search was established based on only the m/z values of query data and records. The confidence levels of the annotations were managed using the MS/MS fragmentation association rule, which is an algorithm for discovering common fragmentations in MS/MS data. Using this data resource and database, a case study was conducted for the annotation of untargeted MS/MS data that were selected after quantitative trait locus analysis of the accessions (Gifu and Miyakojima) of a model legume Lotus japonicus. In the case study, unknown metabolites were successfully narrowed down to putative structures in the website.

CML42-mediated calcium signaling coordinates responses to Spodoptera herbivory and abiotic stresses in Arabidopsis

In the interaction between Arabidopsis (Arabidopsis thaliana) and the generalist herbivorous insect Spodoptera littoralis, little is known about early events in defense signaling and their link to downstream phytohormone pathways. S. littoralis oral secretions induced both Ca²⁺ and phytohormone elevation in Arabidopsis. Plant gene expression induced by oral secretions revealed up-regulation of a gene encoding a calmodulin-like protein, CML42. Functional analysis of cml42 plants revealed more resistance to herbivory than in the wild type, because caterpillars gain less weight on the mutant, indicating that CML42 negatively regulates plant defense; cml42 also showed increased aliphatic glucosinolate content and hyperactivated transcript accumulation of the jasmonic acid (JA)-responsive genes VSP2 and Thi2.1 upon herbivory, which might contribute to increased resistance. CML42 up-regulation is negatively regulated by the jasmonate receptor Coronatine Insensitive1 (COI1), as loss of functional COI1 resulted in prolonged CML42 activation. CML42 thus acts as a negative regulator of plant defense by decreasing COI1-mediated JA sensitivity and the expression of JA-responsive genes and is independent of herbivory-induced JA biosynthesis. JA-induced Ca²⁺ elevation and root growth inhibition were more sensitive in cml42, also indicating higher JA perception. Our results indicate that CML42 acts as a crucial signaling component connecting Ca²⁺ and JA signaling. CML42 is localized to cytosol and nucleus. CML42 is also involved in abiotic stress responses, as kaempferol glycosides were down-regulated in cml42, and impaired in ultraviolet B resistance. Under drought stress, the level of abscisic acid accumulation was higher in cml42 plants. Thus, CML42 might serve as a Ca²⁺ sensor having multiple functions in insect herbivory defense and abiotic stress responses.