Elucidation of Gene-to-Gene and Metabolite-to-Gene Networks inArabidopsis by Integration of Metabolomics andTranscriptomics

l-2-Aminopimelic acid acts as an auxin mimic to induce lateral root formation across diverse plant species

The identification of chemicals that modulate plant development and adaptive responses to stresses has attracted increasing attention for agricultural applications. Recent basic studies have identified functional amino acids that are essential for plant organogenesis, indicating that amino acids can regulate plant growth. In this study, we newly identified 2-aminopimelic acid (2APA), a nonproteinogenic amino acid, as a novel bioactive compound involved in root morphogenesis. This biological effect was confirmed in several plant species. Our phenotypic analysis revealed that the bioactive 2APA is an l-form stereoisomer. Overall, our study identified a promising root growth regulator and provided insight into the intricate metabolism related to root morphology.

Gene regulatory networks underlying sulfate deficiency responses in plants

Sulfur (S) is an essential macronutrient for plants and its availability in soils is an important determinant for growth and development. Current regulatory policies aimed at reducing industrial S emissions together with changes in agronomical practices have led to a decline in S contents in soils worldwide. Deficiency of sulfate-the primary form of S accessible to plants in soil-has adverse effects on both crop yield and nutritional quality. Hence, recent research has increasingly focused on unraveling the molecular mechanisms through which plants detect and adapt to a limiting supply of sulfate. A significant part of these studies involves the use of omics technologies and has generated comprehensive catalogs of sulfate deficiency-responsive genes and processes, principally in Arabidopsis together with a few studies centering on crop species such as wheat, rice, or members of the Brassica genus. Although we know that sulfate deficiency elicits an important reprogramming of the transcriptome, the transcriptional regulators orchestrating this response are not yet well understood. In this review, we summarize our current knowledge of gene expression responses to sulfate deficiency and recent efforts towards the identification of the transcription factors that are involved in controlling these responses. We further compare the transcriptional response and putative regulators between Arabidopsis and two important crop species, rice and tomato, to gain insights into common mechanisms of the response to sulfate deficiency.

A Review of Transcriptomics and Metabolomics in Plant Quality and Environmental Response: From Bibliometric Analysis to Science Mapping and Future Trends

Transcriptomics and metabolomics offer distinct advantages in investigating the differentially expressed genes and cellular entities that have the greatest influence on end-phenotype, making them crucial techniques for studying plant quality and environmental responses. While numerous relevant articles have been published, a comprehensive summary is currently lacking. This review aimed to understand the global and longitudinal research trends of transcriptomics and metabolomics in plant quality and environmental response (TMPQE). Utilizing bibliometric methods, we presented a comprehensive science mapping of the social structure, conceptual framework, and intellectual foundation of TMPQE. We uncovered that TMPQE research has been categorized into three distinct stages since 2020. A citation analysis of the 29 most cited articles, coupled with a content analysis of recent works (2020-2023), highlight five potential research streams in plant quality and environmental responses: (1) biosynthetic pathways, (2) abiotic stress, (3) biotic stress, (4) development and ripening, and (5) methodologies and tools. Current trends and future directions are shaped by technological advancements, species diversity, evolving research themes, and an environmental ecology focus. Overall, this review provides a novel and comprehensive perspective to understand the longitudinal trend on TMPQE.

Transcriptional and metabolic profiling of sulfur starvation response in two monocots

BACKGROUND

Sulfur (S) is a mineral nutrient essential for plant growth and development, which is incorporated into diverse molecules fundamental for primary and secondary metabolism, plant defense, signaling, and maintaining cellular homeostasis. Although, S starvation response is well documented in the dicot model Arabidopsis thaliana, it is not clear if the same transcriptional networks control the response also in the monocots.

RESULTS

We performed series of physiological, expression, and metabolite analyses in two model monocot species, one representing the C3 plants, Oryza sativa cv. kitaake, and second representing the C4 plants, Setaria viridis. Our comprehensive transcriptomic analysis revealed twice as many differentially expressed genes (DEGs) in S. viridis than in O. sativa under S-deficiency, consistent with a greater loss of sulfur and S-containing metabolites under these conditions. Surprisingly, most of the DEGs and enriched gene ontology terms were species-specific, with an intersect of only 58 common DEGs. The transcriptional networks were different in roots and shoots of both species, in particular no genes were down-regulated by S-deficiency in the roots of both species.

CONCLUSIONS

Our analysis shows that S-deficiency seems to have different physiological consequences in the two monocot species and their nutrient homeostasis might be under distinct control mechanisms.

Traits linked to natural variation of sulfur content in Arabidopsis thaliana

Sulfur (S) is an essential mineral nutrient for plant growth and development; it is important for primary and specialized plant metabolites that are crucial for biotic and abiotic interactions. Foliar S content varies up to 6-fold under a controlled environment, suggesting an adaptive value under certain natural environmental conditions. However, a major quantitative regulator of S content in Arabidopsis thaliana has not been identified yet, pointing to the existence of either additional genetic factors controlling sulfate/S content or of many minor quantitative regulators. Here, we use overlapping information of two separate ionomics studies to select groups of accessions with low, mid, and high foliar S content. We quantify series of metabolites, including anions (sulfate, phosphate, and nitrate), thiols (cysteine and glutathione), and seven glucosinolates, gene expression of 20 genes, sulfate uptake, and three biotic traits. Our results suggest that S content is tightly connected with sulfate uptake, the concentration of sulfate and phosphate anions, and glucosinolate and glutathione synthesis. Additionally, our results indicate that the growth of pathogenic bacteria is enhanced in the A. thaliana accessions containing higher S in their leaves, suggesting a complex regulation between S homeostasis, primary and secondary metabolism, and biotic pressures.

Exogenous Melatonin Promotes Glucoraphanin Biosynthesis by Mediating Glutathione in Hairy Roots of Broccoli (Brassica oleracea L. var. italica Planch)

To investigate the mechanism of melatonin (MT)-mediated glutathione (GSH) in promoting glucoraphanin (GRA) and sulforaphane (SF) synthesis, the gene expression pattern and protein content of hairy broccoli roots under MT treatment were analyzed by a combination of RNA-seq and tandem mass spectrometry tagging (TMT) techniques in this study. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that both proteins and mRNAs with the same expression trend were enriched in the "Glutathione metabolism (ko00480)" and "Proteasome (ko03050)" pathways, and most of the differentially expressed genes (DEGs) and differentially abundant proteins (DAPs) regulating the two pathways were downregulated. The results showed that endogenous GSH concentration and GR activity were increased in hairy roots after MT treatment. Exogenous GSH could promote the biosynthesis of GRA and SF, and both exogenous MT and GSH could upregulate the expression of the GSTF11 gene related to the sulfur transport gene, thus promoting the biosynthesis of GRA. Taken together, this study provides a new perspective to explore the complex molecular mechanisms of improving GRA and SF synthesis levels by MT and GSH regulation.

Transcriptome and Metabolome Analyses of Thitarodes xiaojinensis in Response to Ophiocordyceps sinensis Infection

Ophiocordyceps sinensis exhibits more than 5 months of vegetative growth in Thitarodes xiaojinensis hemocoel. The peculiar development process of O. sinensis has been elucidated through morphological observation and omics technology; however, little information has been reported regarding the changes that occur in the host T. xiaojinensis. The RNA sequencing data showed that when O. sinensis blastospores were in the proliferative stage, the greatest change in the infected larval fat body was the selectively upregulated immune recognition and antimicrobial peptide genes. When O. sinensis blastospores were in the stationary stage, the immune pathways of T. xiaojinensis reverted to normal levels, which coincides with the successful settlement of O. sinensis. Pathway enrichment analysis showed a higher expression of genes involved in energy metabolism pathway in this stage. Metabolomic analyses revealed a reduction of amino acids and lipids in hemolymph, but an upregulation of lipids in the fat body of the host larvae after O. sinensis infection. We present the first transcriptome integrated with the metabolome study of T. xiaojinensis infected by O. sinensis. It will improve our understanding of the interaction mechanisms between the host and entomopathogenic fungi, and facilitate future functional studies of genes and pathways involved in these interactions.

Is specialized metabolite regulation specialized?

Recent technical and theoretical advances have generated an explosion in the identification of specialized metabolite pathways. In comparison, our understanding of how these pathways are regulated is relatively lagging. This and the relatively young age of specialized metabolite pathways has partly contributed to a default and common paradigm whereby specialized metabolite regulation is theorized as relatively simple with a few key transcription factors and the compounds are non-regulatory end-products. In contrast, studies into model specialized metabolites, such as glucosinolates, are beginning to identify a new understanding whereby specialized metabolites are highly integrated into the plants' core metabolic, physiological, and developmental pathways. This model includes a greatly extended compendium of transcription factors controlling the pathway, key transcription factors that co-evolve with the pathway and simultaneously control core metabolic and developmental components, and finally the compounds themselves evolve regulatory connections to integrate into the plants signaling machinery. In this review, these concepts are illustrated using studies in the glucosinolate pathway within the Brassicales. This suggests that the broader community needs to reconsider how they do or do not integrate specialized metabolism into the regulatory network of their study species.

Insights into the loss of glucoraphanin in post-harvested broccoli--Possible involvement of the declined supply capacity of sulfur donor

The loss of characteristic nutrient glucoraphanin during the shelf life seriously affects the nutritional quality of broccoli. Here, we monitored the changes in the levels of sulfur donors (cysteine and glutathione) required for glucoraphanin biosynthesis. Similar to glucoraphanin, cysteine content decreased sharply. Continuous down-regulation of BoCysK1 and BoCysK2 genes encoding cysteine synthase might account for cysteine loss. Contrarily, glutathione content accumulated steadily, which might owe to the up-regulation of biosynthetic gene (BoEC1). Additionally, the change of malondialdehyde content was positively correlated with glutathione, implying that oxidative stress might stimulate glutathione accumulation. Nevertheless, the expression of BoGSTF11 gene encoding glutathione S-transferases was down-regulated, which blocked the supply of glutathione. The increase in the content of raphanusamic acid (degradation product) indicated that insufficient supply of sulfur donors not only could constrain the biosynthesis of glucoraphanin but also triggered its degradation.

Two O-Methyltransferases from Phylogenetically Unrelated Cow Parsley (Anthriscus sylvestris) and Hinoki-Asunaro (Thujopsis dolabrata var. hondae) as a Signature of Lineage-Specific Evolution in Lignan Biosynthesis

O-Methyltransferases (OMTs) play important roles in antitumor lignan biosynthesis. To date, six OMTs catalyzing the methylation of dibenzylbutyrolactone lignans as biosynthetic precursors of antitumor lignans have been identified. However, there is still no systematic understanding of the diversity and regularity of the biosynthetic mechanisms among various plant lineages. Herein, we report the characterization of two OMTs from Anthriscus sylvestris and Thujopsis dolabrata var. hondae [designated as AsSecoNorYatein (SNY) OMT and TdSNYOMT] together with the six known OMTs to evaluate their diversity and regularity. Although A. sylvestris 5-O-methylthujaplicatin (SecoNorYatein) and 4-O-demethylyatein (NorYatein) OMT (AsSNYOMT) and TdSNYOMT accept 5-O-methylthujaplicatin and 4-O-demethylyatein as substrates, phylogenetic analysis indicated that these two OMTs shared low amino acid sequence identity, 33.8%, indicating a signature of parallel evolution. The OMTs and the six previously identified OMTs were found to be diverse in terms of their substrate specificity, regioselectivity and amino acid sequence identity, indicating independent evolution in each plant species. Meanwhile, two-entropy analysis detected four amino acid residues as being specifically acquired by dibenzylbutyrolactone lignan OMTs. Site-directed mutation of AsSNYOMT indicated that two of them contributed specifically to 5-O-methylthujaplicatin methylation. The results provide a new example of parallel evolution and the diversity and regularity of OMTs in plant secondary (specialized) metabolism.

From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology

The selection of plant genotypes with improved productivity and tolerance to environmental constraints has always been a major concern in plant breeding. Classical approaches based on the generation of variability and selection of better phenotypes from large variant collections have improved their efficacy and processivity due to the implementation of molecular biology techniques, particularly genomics, Next Generation Sequencing and other omics such as proteomics and metabolomics. In this regard, the identification of interesting variants before they develop the phenotype trait of interest with molecular markers has advanced the breeding process of new varieties. Moreover, the correlation of phenotype or biochemical traits with gene expression or protein abundance has boosted the identification of potential new regulators of the traits of interest, using a relatively low number of variants. These important breakthrough technologies, built on top of classical approaches, will be improved in the future by including the spatial variable, allowing the identification of gene(s) involved in key processes at the tissue and cell levels.

Cytokinin modulates the metabolic network of sulfur and glutathione

The phytohormone cytokinin is implicated in a range of growth, developmental, and defense processes. A growing body of evidence supports a crosstalk between cytokinin and nutrient signaling pathways, such as nitrate availability. Cytokinin signaling regulates sulfur-responsive gene expression, but the underlying molecular mechanisms and their impact on sulfur-containing metabolites have not been systematically explored. Using a combination of genetic and pharmacological tools, we investigated the interplay between cytokinin signaling and sulfur homeostasis. Exogenous cytokinin triggered sulfur starvation-like gene expression accompanied by a decrease in sulfate and glutathione content. This process was uncoupled from the activity of the major transcriptional regulator of sulfate starvation signaling SULFUR LIMITATION 1 and an important glutathione-degrading enzyme, γ-glutamyl cyclotransferase 2;1, expression of which was robustly up-regulated by cytokinin. Conversely, glutathione accumulation was observed in mutants lacking the cytokinin receptor ARABIDOPSIS HISTIDINE KINASE 3 and in cytokinin-deficient plants. Cytokinin-deficient plants displayed improved root growth upon exposure to glutathione-depleting chemicals which was attributed to a higher capacity to maintain glutathione levels. These results shed new light on the interplay between cytokinin signaling and sulfur homeostasis. They position cytokinin as an important modulator of sulfur uptake, assimilation, and remobilization in plant defense against xenobiotics and root growth.

Early-stage responses to Plasmodiophora brassicae at the transcriptome and metabolome levels in clubroot resistant and susceptible oilseed Brassica napus

Clubroot, a devastating soil-borne root disease, in Brassicaceae is caused by Plasmodiophora brassicae Woronin (P. brassicae W.), an obligate biotrophic protist. Plant growth and development, as well as seed yield of Brassica crops, are severely affected due to this disease. Several reports described the molecular responses of B. napus to P. brassicae; however, information on the early stages of pathogenesis is limited. In this study, we have used transcriptomics and metabolomics to characterize P. brassicae pathogenesis at 1-, 4-, and 7-days post-inoculation (DPI) in clubroot resistant (CR) and susceptible (CS) doubled-haploid (DH) canola lines. When we compared between inoculated and uninoculated groups, a total of 214 and 324 putative genes exhibited differential expression (q-value < 0.05) at one or more time-points in the CR and CS genotypes, respectively. When the inoculated CR and inoculated CS genotypes were compared, 4765 DEGs were differentially expressed (q-value < 0.05) at one or more time-points. Several metabolites related to organic acids (e.g., citrate, pyruvate), amino acids (e.g., proline, aspartate), sugars, and mannitol, were differentially accumulated in roots in response to pathogen infection when the CR and CS genotypes were compared. Several DEGs also corresponded to differentially accumulated metabolites, including pyrroline-5-carboxylate reductase (BnaC04g11450D), citrate synthase (BnaC02g39080D), and pyruvate kinase (BnaC04g23180D) as detected by transcriptome analysis. Our results suggest important roles for these genes in mediating resistance to clubroot disease. To our knowledge, this is the first report of an integrated transcriptome and metabolome analysis aimed at characterizing the molecular basis of resistance to clubroot in canola.

Transcriptomic and metabolomic integration as a resource in grapevine to study fruit metabolite quality traits

Transcriptomics and metabolomics are methodologies being increasingly chosen to perform molecular studies in grapevine (Vitis vinifera L.), focusing either on plant and fruit development or on interaction with abiotic or biotic factors. Currently, the integration of these approaches has become of utmost relevance when studying key plant physiological and metabolic processes. The results from these analyses can undoubtedly be incorporated in breeding programs whereby genes associated with better fruit quality (e.g., those enhancing the accumulation of health-promoting compounds) or with stress resistance (e.g., those regulating beneficial responses to environmental transition) can be used as selection markers in crop improvement programs. Despite the vast amount of data being generated, integrative transcriptome/metabolome meta-analyses (i.e., the joint analysis of several studies) have not yet been fully accomplished in this species, mainly due to particular specificities of metabolomic studies, such as differences in data acquisition (i.e., different compounds being investigated), unappropriated and unstandardized metadata, or simply no deposition of data in public repositories. These meta-analyses require a high computational capacity for data mining a priori, but they also need appropriate tools to explore and visualize the integrated results. This perspective article explores the universe of omics studies conducted in V. vinifera, focusing on fruit-transcriptome and metabolome analyses as leading approaches to understand berry physiology, secondary metabolism, and quality. Moreover, we show how omics data can be integrated in a simple format and offered to the research community as a web resource, giving the chance to inspect potential gene-to-gene and gene-to-metabolite relationships that can later be tested in hypothesis-driven research. In the frame of the activities promoted by the COST Action CA17111 INTEGRAPE, we present the first grapevine transcriptomic and metabolomic integrated database (TransMetaDb) developed within the Vitis Visualization (VitViz) platform (https://tomsbiolab.com/vitviz). This tool also enables the user to conduct and explore meta-analyses utilizing different experiments, therefore hopefully motivating the community to generate Findable, Accessible, Interoperable and Reusable (F.A.I.R.) data to be included in the future.

Genome-Wide Association Reveals Trait Loci for Seed Glucosinolate Accumulation in Indian Mustard (Brassica juncea L.)

Glucosinolates (GSLs) are sulphur- and nitrogen-containing secondary metabolites implicated in the fitness of Brassicaceae and appreciated for their pungency and health-conferring properties. In Indian mustard (Brassica juncea L.), GSL content and composition are seed-quality-determining traits affecting its economic value. Depending on the end use, i.e., condiment or oil, different GSL levels constitute breeding targets. The genetic control of GSL accumulation in Indian mustard, however, is poorly understood, and current knowledge of GSL biosynthesis and regulation is largely based on Arabidopsis thaliana. A genome-wide association study was carried out to dissect the genetic architecture of total GSL content and the content of two major GSLs, sinigrin and gluconapin, in a diverse panel of 158 Indian mustard lines, which broadly grouped into a South Asia cluster and outside-South-Asia cluster. Using 14,125 single-nucleotide polymorphisms (SNPs) as genotyping input, seven distinct significant associations were discovered for total GSL content, eight associations for sinigrin content and 19 for gluconapin. Close homologues of known GSL structural and regulatory genes were identified as candidate genes in proximity to peak SNPs. Our results provide a comprehensive map of the genetic control of GLS biosynthesis in Indian mustard, including priority targets for further investigation and molecular marker development.

Arabidopsis Glutathione-S-Transferases GSTF11 and GSTU20 Function in Aliphatic Glucosinolate Biosynthesis

Glutathione (GSH) conjugation with intermediates is required for the biosynthesis of glucosinolate (GSL) by serving as a sulfur supply. Glutathione-S-transferases (GSTs) primarily work on GSH conjugation, suggesting their involvement in GSL metabolism. Although several GSTs, including GSTF11 and GSTU20, have been recently postulated to act in GSL biosynthesis, molecular evidence is lacking. Here, we demonstrated that GSTF11 and GSTU20 play non-redundant, although partially overlapping, roles in aliphatic GSL biosynthesis. In addition, GSTU20 plays a more important role than GSTF11, which is manifested by the greater loss of aliphatic GSLs associated with GSTU20 mutant and a greater number of differentially expressed genes in GSTU20 mutant compared to GSTF11 mutant. Moreover, a double mutation leads to a greater aggregate loss of aliphatic GSLs, suggesting that GSTU20 and GSTF11 may function in GSL biosynthesis in a dosage-dependent manner. Together, our results provide direct evidence that GSTU20 and GSTF11 are critically involved in aliphatic GSL biosynthesis, filling the knowledge gap that has been speculated in recent decades.

An integrated metabolomics and proteogenomics approach reveals molecular alterations following carbamazepine exposure in the male mussel Mytilus galloprovincialis

Carbamazepine is one of the most abundant pharmaceutical active compounds detected in aquatic systems. Based on laboratory exposures, carbamazepine has been proven to adversely affect aquatic organisms. However, the underlying molecular events remain poorly understood. This study aims to investigate the molecular mechanisms potentially associated with toxicological effects of carbamazepine on the mussel Mytilus galloprovincialis exposed for 3 days at realistic concentrations encountered in coastal environments (80 ng/L and 8 μg/L). An integrated metabolomics and proteogenomics approach, including data fusion strategy, was applied to gain more insight in molecular events and cellular processes triggered by carbamazepine exposure. Consistent metabolic and protein signatures revealed a metabolic rewiring and cellular stress at both concentrations (e.g. intensification of protein synthesis, transport and catabolism processes, disruption of lipid and amino acid metabolisms). These highlighted molecular signatures point to the induction of autophagy, closely related with carbamazepine mechanism of action, as well as a destabilization of the lysosomal membranes and an enzymatic overactivity of the peroxisomes. Induction of programmed cell death was highlighted by the modulation of apoptotic cognate proteins. The proposed integrative omics data analysis was shown to be highly relevant to identify the modulations of the two molecular levels, i.e. metabolites and proteins. Multi-omics approach is able to explain the resulting complex biological system, and document stronger toxicological pieces of evidence on pharmaceutical active compounds at environmental concentrations in sentinel organisms.

Skotomorphogenesis exploits threonine to promote hypocotyl elongation

Mobilisation of seed storage reserves is important for seedling establishment in Arabidopsis. In this process, sucrose is synthesised from triacylglycerol via core metabolic processes. Mutants with defects in triacylglycerol-to-sucrose conversion display short etiolated seedlings. We found that whereas sucrose content in the indole-3-butyric acid response 10 (ibr10) mutant was significantly reduced, hypocotyl elongation in the dark was unaffected, questioning the role of IBR10 in this process. To dissect the metabolic complexity behind cell elongation, a quantitative-based phenotypic analysis combined with a multi-platform metabolomics approach was applied. We revealed that triacylglycerol and diacylglycerol breakdown were disrupted in ibr10, resulting in low sugar content and poor photosynthetic ability. Importantly, batch-learning self-organised map clustering revealed that threonine level was correlated with hypocotyl length. Consistently, exogenous threonine supply stimulated hypocotyl elongation, indicating that sucrose levels are not always correlated with etiolated seedling length, suggesting the contribution of amino acids in this process.

Potential Arabidopsis thaliana glucosinolate genes identified from the co-expression modules using graph clustering approach

Background

Glucosinolates (GSLs) are plant secondary metabolites that contain nitrogen-containing compounds. They are important in the plant defense system and known to provide protection against cancer in humans. Currently, increasing the amount of data generated from various omics technologies serves as a hotspot for new gene discovery. However, sometimes sequence similarity searching approach is not sufficiently effective to find these genes; hence, we adapted a network clustering approach to search for potential GSLs genes from the Arabidopsis thaliana co-expression dataset.

Methods

We used known GSL genes to construct a comprehensive GSL co-expression network. This network was analyzed with the DPClusOST algorithm using a density of 0.5. 0.6. 0.7, 0.8, and 0.9. Generating clusters were evaluated using Fisher’s exact test to identify GSL gene co-expression clusters. A significance score (SScore) was calculated for each gene based on the generated p-value of Fisher’s exact test. SScore was used to perform a receiver operating characteristic (ROC) study to classify possible GSL genes using the ROCR package. ROCR was used in determining the AUC that measured the suitable density value of the cluster for further analysis. Finally, pathway enrichment analysis was conducted using ClueGO to identify significant pathways associated with the GSL clusters.

Results

The density value of 0.8 showed the highest area under the curve (AUC) leading to the selection of thirteen potential GSL genes from the top six significant clusters that include IMDH3, MVP1, T19K24.17, MRSA2, SIR, ASP4, MTO1, At1g21440, HMT3, At3g47420, PS1, SAL1, and At3g14220. A total of Four potential genes (MTO1, SIR, SAL1, and IMDH3) were identified from the pathway enrichment analysis on the significant clusters. These genes are directly related to GSL-associated pathways such as sulfur metabolism and valine, leucine, and isoleucine biosynthesis. This approach demonstrates the ability of the network clustering approach in identifying potential GSL genes which cannot be found from the standard similarity search.

Unraveling the roles of plant specialized metabolites: using synthetic biology to design molecular biosensors

Plants are a rich source of specialized metabolites with a broad range of bioactivities and many applications in human daily life. Over the past decades significant progress has been made in identifying many such metabolites in different plant species and in elucidating their biosynthetic pathways. However, the biological roles of plant specialized metabolites remain elusive and proposed functions lack an identified underlying molecular mechanism. Understanding the roles of specialized metabolites frequently is hampered by their dynamic production and their specific spatiotemporal accumulation within plant tissues and organs throughout a plant's life cycle. In this review, we propose the employment of strategies from the field of Synthetic Biology to construct and optimize genetically encoded biosensors that can detect individual specialized metabolites in a standardized and high-throughput manner. This will help determine the precise localization of specialized metabolites at the tissue and single-cell levels. Such information will be useful in developing complete system-level models of specialized plant metabolism, which ultimately will demonstrate how the biosynthesis of specialized metabolites is integrated with the core processes of plant growth and development.

Statistical Integration of 'Omics Data Increases Biological Knowledge Extracted from Metabolomics Data: Application to Intestinal Exposure to the Mycotoxin Deoxynivalenol

The effects of low doses of toxicants are often subtle and information extracted from metabolomic data alone may not always be sufficient. As end products of enzymatic reactions, metabolites represent the final phenotypic expression of an organism and can also reflect gene expression changes caused by this exposure. Therefore, the integration of metabolomic and transcriptomic data could improve the extracted biological knowledge on these toxicants induced disruptions. In the present study, we applied statistical integration tools to metabolomic and transcriptomic data obtained from jejunal explants of pigs exposed to the food contaminant, deoxynivalenol (DON). Canonical correlation analysis (CCA) and self-organizing map (SOM) were compared for the identification of correlated transcriptomic and metabolomic features, and O2-PLS was used to model the relationship between exposure and selected features. The integration of both 'omics data increased the number of discriminant metabolites discovered (39) by about 10 times compared to the analysis of the metabolomic dataset alone (3). Besides the disturbance of energy metabolism previously reported, assessing correlations between both functional levels revealed several other types of damage linked to the intestinal exposure to DON, including the alteration of protein synthesis, oxidative stress, and inflammasome activation. This confirms the added value of integration to enrich the biological knowledge extracted from metabolomics.

Next-Generation Mass Spectrometry Metabolomics Revives the Functional Analysis of Plant Metabolic Diversity

The remarkable diversity of specialized metabolites produced by plants has inspired several decades of research and nucleated a long list of theories to guide empirical ecological studies. However, analytical constraints and the lack of untargeted processing workflows have long precluded comprehensive metabolite profiling and, consequently, the collection of the critical currencies to test theory predictions for the ecological functions of plant metabolic diversity. Developments in mass spectrometry (MS) metabolomics have revolutionized the large-scale inventory and annotation of chemicals from biospecimens. Hence, the next generation of MS metabolomics propelled by new bioinformatics developments provides a long-awaited framework to revisit metabolism-centered ecological questions, much like the advances in next-generation sequencing of the last two decades impacted all research horizons in genomics. Here, we review advances in plant (computational) metabolomics to foster hypothesis formulation from complex metabolome data. Additionally, we reflect on how next-generation metabolomics could reinvigorate the testing of long-standing theories on plant metabolic diversity.

Advances in the Study of Metabolomics and Metabolites in Some Species Interactions

In the natural environment, interactions between species are a common natural phenomena. The mechanisms of interaction between different species are mainly studied using genomic, transcriptomic, proteomic, and metabolomic techniques. Metabolomics is a crucial part of system biology and is based on precision instrument analysis. In the last decade, the emerging field of metabolomics has received extensive attention. Metabolomics not only provides a qualitative and quantitative method for studying the mechanisms of interactions between different species, but also helps clarify the mechanisms of defense between the host and pathogen, and to explore new metabolites with various biological activities. This review focuses on the methods and progress of interspecies metabolomics. Additionally, the prospects and challenges of interspecies metabolomics are discussed.

Retrograde sulfur flow from glucosinolates to cysteine in Arabidopsis thaliana

Specialized (secondary) metabolites have been largely considered bioactive “end” products synthesized from primary metabolites. We report biochemical evidence of a retrograde flow of sulfur atoms from specialized metabolites (glucosinolates) to primary metabolites (cysteine) in Arabidopsis thaliana. The reaction begins with glucosinolate breakdown by specific beta-glucosidases, which facilitates sulfur deficiency tolerance, demonstrating a physiological advantage of utilizing specialized metabolites as nutrient reservoirs. Our findings address the breadth of turnover systems in nature and enhance our understanding of how plants coordinate primary and specialized metabolism under different environmental conditions.

Specialized (secondary) metabolic pathways in plants have long been considered one-way routes of leading primary metabolite precursors to bioactive end products. Conversely, endogenous degradation of such “end” products in plant tissues has been observed following environmental stimuli, including nutrition stress. Therefore, it is of general interest whether specialized metabolites can be reintegrated into primary metabolism to recover the invested resources, especially in the case of nitrogen- or sulfur-rich compounds. Here, we demonstrate that endogenous glucosinolates (GLs), a class of sulfur-rich plant metabolites, are exploited as a sulfur source by the reallocation of sulfur atoms to primary metabolites such as cysteine in Arabidopsis thaliana. Tracer experiments using ³⁴S- or deuterium-labeled GLs depicted the catabolic processing of GL breakdown products in which sulfur is mobilized from the thioglucoside group in GL molecules, potentially accompanied by the release of the sulfate group. Moreover, we reveal that beta-glucosidases BGLU28 and BGLU30 are the major myrosinases that initiate sulfur reallocation by hydrolyzing particular GL species, conferring sulfur deficiency tolerance in A. thaliana, especially during early development. The results delineate the physiological function of GL as a sulfur reservoir, in addition to their well-known functions as defense chemicals. Overall, our findings demonstrate the bidirectional interaction between primary and specialized metabolism, which enhances our understanding of the underlying metabolic mechanisms via which plants adapt to their environments.

Comparative Analysis Based on Transcriptomics and Metabolomics Data Reveal Differences between Emmer and Durum Wheat in Response to Nitrogen Starvation

Mounting evidence indicates the key role of nitrogen (N) on diverse processes in plant, including development and defense. Using a combined transcriptomics and metabolomics approach, we studied the response of seedlings to N starvation of two different tetraploid wheat genotypes from the two main domesticated subspecies: emmer and durum wheat. We found that durum wheat exhibits broader and stronger response in comparison to emmer as seen from the expression pattern of both genes and metabolites and gene enrichment analysis. They showed major differences in the responses to N starvation for transcription factor families, emmer showed differential reduction in the levels of primary metabolites while durum wheat exhibited increased levels of most of them to N starvation. The correlation-based networks, including the differentially expressed genes and metabolites, revealed tighter regulation of metabolism in durum wheat in comparison to emmer. We also found that glutamate and γ-aminobutyric acid (GABA) had highest values of centrality in the metabolic correlation network, suggesting their critical role in the genotype-specific response to N starvation of emmer and durum wheat, respectively. Moreover, this finding indicates that there might be contrasting strategies associated to GABA and glutamate signaling modulating shoot vs. root growth in the two different wheat subspecies.

Approaches to Integrating Metabolomics and Multi-Omics Data: A Primer

Metabolomics deals with multiple and complex chemical reactions within living organisms and how these are influenced by external or internal perturbations. It lies at the heart of omics profiling technologies not only as the underlying biochemical layer that reflects information expressed by the genome, the transcriptome and the proteome, but also as the closest layer to the phenome. The combination of metabolomics data with the information available from genomics, transcriptomics, and proteomics offers unprecedented possibilities to enhance current understanding of biological functions, elucidate their underlying mechanisms and uncover hidden associations between omics variables. As a result, a vast array of computational tools have been developed to assist with integrative analysis of metabolomics data with different omics. Here, we review and propose five criteria-hypothesis, data types, strategies, study design and study focus- to classify statistical multi-omics data integration approaches into state-of-the-art classes under which all existing statistical methods fall. The purpose of this review is to look at various aspects that lead the choice of the statistical integrative analysis pipeline in terms of the different classes. We will draw particular attention to metabolomics and genomics data to assist those new to this field in the choice of the integrative analysis pipeline.

Integrating multi-omics data for crop improvement

Our agricultural systems are now in urgent need to secure food for a growing world population. To meet this challenge, we need a better characterization of plant genetic and phenotypic diversity. The combination of genomics, transcriptomics and metabolomics enables a deeper understanding of the mechanisms underlying the complex architecture of many phenotypic traits of agricultural relevance. We review the recent advances in plant genomics to see how these can be integrated with broad molecular profiling approaches to improve our understanding of plant phenotypic variation and inform crop breeding strategies.

Coordinating Sulfur Pools under Sulfate Deprivation

Plants display manifold metabolic changes on sulfate deficiency (S deficiency) with all sulfur-containing pools of primary and secondary metabolism affected. O-Acetylserine (OAS), whose levels are rapidly altered on S deficiency, is correlated tightly with novel regulators of plant sulfur metabolism that have key roles in balancing plant sulfur pools, including the Sulfur Deficiency Induced genes (SDI1 and SDI2), More Sulfur Accumulation1 (MSA1), and GGCT2;1. Despite the importance of OAS in the coordination of S pools under stress, mechanisms of OAS perception and signaling have remained elusive. Here, we put particular focus on the general OAS-responsive genes but also elaborate on the specific roles of SDI1 and SDI2 genes, which downregulate the glucosinolate (GSL) pool size. We also highlight the key open questions in sulfur partitioning.

Transcriptomic analysis at organ and time scale reveals gene regulatory networks controlling the sulfate starvation response of Solanum lycopersicum

BACKGROUND

Sulfur is a major component of biological molecules and thus an essential element for plants. Deficiency of sulfate, the main source of sulfur in soils, negatively influences plant growth and crop yield. The effect of sulfate deficiency on plants has been well characterized at the physiological, transcriptomic and metabolomic levels in Arabidopsis thaliana and a limited number of crop plants. However, we still lack a thorough understanding of the molecular mechanisms and regulatory networks underlying sulfate deficiency in most plants. In this work we analyzed the impact of sulfate starvation on the transcriptome of tomato plants to identify regulatory networks and key transcriptional regulators at a temporal and organ scale.

RESULTS

Sulfate starvation reduces the growth of roots and leaves which is accompanied by major changes in the organ transcriptome, with the response being temporally earlier in roots than leaves. Comparative analysis showed that a major part of the Arabidopsis and tomato transcriptomic response to sulfate starvation is conserved between these plants and allowed for the identification of processes specifically regulated in tomato at the transcript level, including the control of internal phosphate levels. Integrative gene network analysis uncovered key transcription factors controlling the temporal expression of genes involved in sulfate assimilation, as well as cell cycle, cell division and photosynthesis during sulfate starvation in tomato roots and leaves. Interestingly, one of these transcription factors presents a high identity with SULFUR LIMITATION1, a central component of the sulfate starvation response in Arabidopsis.

CONCLUSIONS

Together, our results provide the first comprehensive catalog of sulfate-responsive genes in tomato, as well as novel regulatory targets for future functional analyses in tomato and other crops.

A Comprehensive Gene Inventory for Glucosinolate Biosynthetic Pathway in Arabidopsis thaliana

Glucosinolates (GSLs) are plant secondary metabolites comprising sulfur and nitrogen mainly found in plants from the order of Brassicales, such as broccoli, cabbage, and Arabidopsis thaliana. The activated forms of GSL play important roles in fighting against pathogens and have health benefits to humans. The increasing amount of data on A. thaliana generated from various omics technologies can be investigated more deeply in search of new genes or compounds involved in GSL biosynthesis and metabolism. This review describes a comprehensive inventory of A. thaliana GSLs identified from published literature and databases such as KNApSAcK, KEGG, and AraCyc. A total of 113 GSL genes encoding for 23 transcription components, 85 enzymes, and five protein transporters were experimentally characterized in the past two decades. Continuous efforts are still on going to identify all molecules related to the production of GSLs. A manually curated database known as SuCCombase (http://plant-scc.org) was developed to serve as a comprehensive GSL inventory. Realizing lack of information on the regulation of GSL biosynthesis and degradation mechanisms, this review also includes relevant information and their connections with crosstalk among various factors, such as light, sulfur metabolism, and nitrogen metabolism, not only in A. thaliana but also in other crucifers.

Sulfur Deficiency Increases Phosphate Accumulation, Uptake, and Transport in Arabidopsis thaliana

Recent studies have shown various metabolic and transcriptomic interactions between sulfur (S) and phosphorus (P) in plants. However, most studies have focused on the effects of phosphate (Pi) availability and P signaling pathways on S homeostasis, whereas the effects of S availability on P homeostasis remain largely unknown. In this study, we investigated the interactions between S and P from the perspective of S availability. We investigated the effects of S availability on Pi uptake, transport, and accumulation in Arabidopsis thaliana grown under sulfur sufficiency (+S) and deficiency (-S). Total P in shoots was significantly increased under -S owing to higher Pi accumulation. This accumulation was facilitated by increased Pi uptake under -S. In addition, -S increased root-to-shoot Pi transport, which was indicated by the increased Pi levels in xylem sap under -S. The -S-increased Pi level in the xylem sap was diminished in the disruption lines of PHT1;9 and PHO1, which are involved in root-to-shoot Pi transport. Our findings indicate a new aspect of the interaction between S and P by listing the increased Pi accumulation as part of -S responses and by highlighting the effects of -S on Pi uptake, transport, and homeostasis.

Integrated Metabolomics and Transcriptomics Unravel the Metabolic Pathway Variations for Different Sized Beech Mushrooms

Beech mushrooms (Hypsizygus marmoreus) are largely relished for their characteristic earthy flavor, chewy-texture, and gustatory and nutritional properties in East Asian societies. Intriguingly, the aforementioned properties of beech mushroom can be subsumed under its elusive metabolome and subtle transcriptome regulating its various stages of growth and development. Herein, we carried out an integrated metabolomic and transcriptomic profiling for different sized beech mushrooms across spatial components (cap and stipe) to delineate their signature pathways. We observed that metabolite profiles and differentially expressed gene (DEGs) displayed marked synergy for specific signature pathways according to mushroom sizes. Notably, the amino acid, nucleotide, and terpenoid metabolism-related metabolites and genes were more abundant in small-sized mushrooms. On the other hand, the relative levels of carbohydrates and TCA intermediate metabolites as well as corresponding genes were linearly increased with mushroom size. However, the composition of flavor-related metabolites was varying in different sized beech mushrooms. Our study explores the signature pathways associated with growth, development, nutritional, functional and organoleptic properties of different sized beech mushrooms.

An Integrated Analysis of the Rice Transcriptome and Metabolome Reveals Root Growth Regulation Mechanisms in Response to Nitrogen Availability

Nitrogen is an essential nutrient for plant growth and basic metabolic processes. Root systems play an important role in the ability of plants to obtain nutrients from the soil, and are closely related to the growth and development of above-ground plants. Root morphology analysis showed that root growth was induced under low-nitrogen conditions and inhibited under high-nitrogen conditions. To better understand the molecular mechanisms and metabolic basis underlying the rice root response to nitrogen availability, an integrated analysis of the rice root transcriptome and metabolome under three environmental conditions (low-, control, and high-nitrogen conditions) was conducted. A total of 262 and 262 differentially level metabolites were identified under low- and high-nitrogen conditions, respectively. A total of 696 and 808 differentially expressed genes were identified under low- and high-nitrogen conditions, respectively. For both the differentially expressed genes and metabolites, KEGG pathway analysis indicated that amino acid metabolism, carbon and nitrogen metabolism, phenylpropanoid metabolism, and phytohormones’ signal transduction were significantly affected by nitrogen availability. Additionally, variable levels of 65 transcription factors (TFs) were identified in rice leaves exposed to high and low nitrogen, covering 22 TF families. These results also indicate that there is a significant difference in the transcriptional regulation mechanisms of rice roots between low and high nitrogen. In summary, our study provides new information for a further understanding of the response of rice roots to low-nitrogen and high-nitrogen conditions.

Exploring the basis of 2-propenyl and 3-butenyl glucosinolate synthesis by QTL mapping and RNA-sequencing in Brassica juncea

Brassica juncea is used as a condiment, as vegetables and as an oilseed crop, especially in semiarid areas. In the present study, we constructed a genetic map using one recombinant inbred line (RIL) of B. juncea. A total of 304 ILP (intron length polymorphism) markers were mapped to 18 linkage groups designated LG01-LG18 in B. juncea. The constructed map covered a total genetic length of 1671.13 cM with an average marker interval of 5.50 cM. The QTLs for 2-propenyl glucosinolates (GSLs) colocalized with the QTLs for 3-butenyl GSLs between At1g26180 and BnapPIP1580 on LG08 in the field experiments of 2016 and 2017. These QTLs accounted for an average of 42.3% and 42.6% phenotypic variation for 2-propenyl and 3-butenyl GSLs, respectively. Furthermore, the Illumina RNA-sequencing technique was used to excavate the genes responsible for the synthesis of GSLs in the siliques of the parental lines of the RIL mapping population, because the bulk of the seed GSLs might originate from the siliques. Comparative analysis and annotation by gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) revealed that 324 genes were involved in GSL metabolism, among which only 24 transcripts were differentially expressed genes (DEGs). Among those DEGs, 15 genes were involved in the biosynthesis and transport of aliphatic GSLs, and their expression patterns were further validated by qRT-PCR analysis. Joint QTL mapping and RNA-sequencing analyses reveal one candidate gene of IIL1 (LOC106416451) for GSL metabolism in B. juncea. These results will be helpful for further fine mapping, gene cloning and genetic mechanisms of 2-propenyl and 3-butenyl GSLs in B. juncea.

Integration of Transcriptomics and Metabolomics for Pepper (Capsicum annuum L.) in Response to Heat Stress

Heat stress (HS), caused by extremely high temperatures, is one of the most severe forms of abiotic stress in pepper. In the present study, we studied the transcriptome and metabolome of a heat-tolerant cultivar (17CL30) and a heat-sensitive cultivar (05S180) under HS. Briefly, we identified 5754 and 5756 differentially expressed genes (DEGs) in 17CL30 and 05S180, respectively. Moreover, we also identified 94 and 108 differentially accumulated metabolites (DAMs) in 17CL30 and 05S180, respectively. Interestingly, there were many common HS-responsive genes (approximately 30%) in both pepper cultivars, despite the expression patterns of these HS-responsive genes being different in both cultivars. Notably, the expression changes of the most common HS-responsive genes were typically much more significant in 17CL30, which might explain why 17CL30 was more heat tolerant. Similar results were also obtained from metabolome data, especially amino acids, organic acids, flavonoids, and sugars. The changes in numerous genes and metabolites emphasized the complex response mechanisms involved in HS in pepper. Collectively, our study suggested that the glutathione metabolic pathway played a critical role in pepper response to HS and the higher accumulation ability of related genes and metabolites might be one of the primary reasons contributing to the heat resistance.

Sulphur systems biology-making sense of omics data

Systems biology approaches have been applied over the last two decades to study plant sulphur metabolism. These 'sulphur-omics' approaches have been developed in parallel with the advancing field of systems biology, which is characterized by permanent improvements of high-throughput methods to obtain system-wide data. The aim is to obtain a holistic view of sulphur metabolism and to generate models that allow predictions of metabolic and physiological responses. Besides known sulphur-responsive genes derived from previous studies, numerous genes have been identified in transcriptomics studies. This has not only increased our knowledge of sulphur metabolism but has also revealed links between metabolic processes, thus indicating a previously unexpected complex interconnectivity. The identification of response and control networks has been supported through metabolomics and proteomics studies. Due to the complex interlacing nature of biological processes, experimental validation using targeted or systems approaches is ongoing. There is still room for improvement in integrating the findings from studies of metabolomes, proteomes, and metabolic fluxes into a single unifying concept and to generate consistent models. We therefore suggest a joint effort of the sulphur research community to standardize data acquisition. Furthermore, focusing on a few different model plant systems would help overcome the problem of fragmented data, and would allow us to provide a standard data set against which future experiments can be designed and compared.

A Novel Method for Identification and Quantification of Sulfated Flavonoids in Plants by Neutral Loss Scan Mass Spectrometry

Sulfur is present in plants in a large range of essential primary metabolites, as well as in numerous natural products. Many of these secondary metabolites contain sulfur in the oxidized form of organic sulfate. However, except of glucosinolates, very little is known about other classes of such sulfated metabolites, mainly because of lack of specific and quantitative analytical methods. We developed an LC-MS method to analyze sulfated flavonoids, a group of sulfated secondary metabolites prominent, e.g., in plants of the genus Flaveria. The method uses a linear gradient of methanol/formic acid in water on a Restek Raptor C₁₈ Core-Shell column for separation of the compounds. The sulfated flavonoids are detected by mass spectrometry (MS) in a negative mode, using a neutral loss of 80 Da after a collision induced dissociation. With this method we were also able to quantify the sulfated flavonoids. We could detect all (mono)sulfated flavonoids described before in Flaveria plus a number of new ones, such as isorhamnetin-sulfate-glycoside. In addition, we showed that sulfated flavonoids represent a substantial sulfur pool in Flaveria, larger than the thiols glutathione and cysteine. The individual species possess different sulfated flavonoids, but there is no correlation between the qualitative pattern and type of photosynthesis. Similar to other sulfur-containing secondary compounds, the concentration of sulfated flavonoids in leaves is reduced by sulfur starvation. The new LC-MS method will enable qualitative and quantitative detection of these secondary metabolites in plants as a pre-requisite to addressing their functions.

Sulfation pathways from red to green

Sulfur is present in the amino acids cysteine and methionine and in a large range of essential coenzymes and cofactors and is therefore essential for all organisms. It is also a constituent of sulfate esters in proteins, carbohydrates, and numerous cellular metabolites. The sulfation and desulfation reactions modifying a variety of different substrates are commonly known as sulfation pathways. Although relatively little is known about the function of most sulfated metabolites, the synthesis of activated sulfate used in sulfation pathways is essential in both animal and plant kingdoms. In humans, mutations in the genes encoding the sulfation pathway enzymes underlie a number of developmental aberrations, and in flies and worms, their loss-of-function is fatal. In plants, a lower capacity for synthesizing activated sulfate for sulfation reactions results in dwarfism, and a complete loss of activated sulfate synthesis is also lethal. Here, we review the similarities and differences in sulfation pathways and associated processes in animals and plants, and we point out how they diverge from bacteria and yeast. We highlight the open questions concerning localization, regulation, and importance of sulfation pathways in both kingdoms and the ways in which findings from these "red" and "green" experimental systems may help reciprocally address questions specific to each of the systems.

Integrated metabolomics identifies CYP72A67 and CYP72A68 oxidases in the biosynthesis of Medicago truncatula oleanate sapogenins

INTRODUCTION

Triterpene saponins are important bioactive plant natural products found in many plant families including the Leguminosae.

OBJECTIVES

We characterize two Medicago truncatula cytochrome P450 enzymes, MtCYP72A67 and MtCYP72A68, involved in saponin biosynthesis including both in vitro and in planta evidence.

METHODS

UHPLC-(-)ESI-QToF-MS was used to profile saponin accumulation across a collection of 106 M. truncatula ecotypes. The profiling results identified numerous ecotypes with high and low saponin accumulation in root and aerial tissues. Four ecotypes with significant differential saponin content in the root and/or aerial tissues were selected, and correlated gene expression profiling was performed.

RESULTS

Correlation analyses between gene expression and saponin accumulation revealed high correlations between saponin content with gene expression of β-amyrin synthase, MtCYP716A12, and two cytochromes P450 genes, MtCYP72A67 and MtCYP72A68. In vivo and in vitro biochemical assays using yeast microsomes containing MtCYP72A67 revealed hydroxylase activity for carbon 2 of oleanolic acid and hederagenin. This finding was supported by functional characterization of MtCYP72A67 using RNAi-mediated gene silencing in M. truncatula hairy roots, which revealed a significant reduction of 2β-hydroxylated sapogenins. In vivo and in vitro assays with MtCYP72A68 produced in yeast showed multifunctional oxidase activity for carbon 23 of oleanolic acid and hederagenin. These findings were supported by overexpression of MtCYP72A68 in M. truncatula hairy roots, which revealed significant increases of oleanolic acid, 2β-hydroxyoleanolic acid, hederagenin and total saponin levels.

CONCLUSIONS

The cumulative data support that MtCYP72A68 is a multisubstrate, multifunctional oxidase and MtCYP72A67 is a 2β-hydroxylase, both of which function during the early steps of triterpene-oleanate sapogenin biosynthesis.

[Biosynthesis of indole glucosinolates and ecological role of secondary modification pathways]

Indole glucosinolates are plant secondary metabolites derived from the amino acid tryptophan. They are part of a large group of sulfur-containing molecules almost exclusively found among Brassicales, which include the mustard family (Brassicaceae) with many edible plant species of major nutritional importance. These compounds mediate numerous interactions between these plants and their natural enemies and are therefore of major biological and economical interest. This literature review aims at taking stock of recent advances of our knowledge about the biosynthetic pathways of indole glucosinolates, but also about the defense strategies and ecological processes involving these metabolites.

Glucosinolates: Molecular structure, breakdown, genetic, bioavailability, properties and healthy and adverse effects

Glucosinolates are a large group of plant secondary metabolites with nutritional effects and biologically active compounds. Glucosinolates are mainly found in cruciferous plants such as Brassicaceae family, including common edible plants such as broccoli (Brassica oleracea var. italica), cabbage (B. oleracea var. capitata f. alba), cauliflower (B. oleracea var. botrytis), rapeseed (Brassica napus), mustard (Brassica nigra), and horseradish (Armoracia rusticana). If cruciferous plants are consumed without processing, myrosinase enzyme will hydrolyze the glucosinolates to various metabolites, such as isothiocyanates, nitriles, oxazolidine-2-thiones, and indole-3-carbinols. On the other hand, when cruciferous are cooked before consumption, myrosinase is inactivated and glucosinolates could be partially absorbed in their intact form through the gastrointestinal mucosa. This review paper summarizes the glucosinolate molecular breakdown, their genetic aspects from biosynthesis to precursors, their bioavailability (assimilation, absorption, and elimination of these molecules), their sensory properties, identified healthy and adverse effects, as well as the impact of processing on their bioavailability.

Atypical Myrosinase as a Mediator of Glucosinolate Functions in Plants

Glucosinolates (GLSs) are a well-known class of specialized plant metabolites, distributed mostly in the order Brassicales. A vast research field in basic and applied sciences has grown up around GLSs owing to their presence in important agricultural crops and the model plant Arabidopsis thaliana, and their broad range of bioactivities beneficial to human health. The major purpose of GLSs in plants has been considered their function as a chemical defense against predators. GLSs are physically separated from a specialized class of beta-thioglucosidases called myrosinases, at the tissue level or at the single-cell level. They are brought together as a consequence of tissue damage, primarily triggered by herbivores, and their interaction results in the release of toxic volatile chemicals including isothiocyanates. In addition, recent studies have suggested that plants may adopt other strategies independent of tissue disruption for initiating GLS breakdown to cope with certain biotic/abiotic stresses. This hypothesis has been further supported by the discovery of an atypical class of GLS-hydrolyzing enzymes possessing features that are distinct from those of the classical myrosinases. Nevertheless, there is only little information on the physiological importance of atypical myrosinases. In this review, we focus on the broad diversity of the beta-glucosidase subclasses containing known atypical myrosinases in A. thaliana to discuss the hypothesis that numerous members of these subclasses can hydrolyze GLSs to regulate their diverse functions in plants. Also, the increasingly broadening functional repertoires of known atypical/classical myrosinases are described with reference to recent findings. Assessment of independent insights gained from A. thaliana with respect to (1) the phenotype of mutants lacking genes in the GLS metabolic/breakdown pathways, (2) fluctuation in GLS contents/metabolism under specific conditions, and (3) the response of plants to exogenous GLSs or their hydrolytic products, will enable us to reconsider the physiological importance of GLS breakdown in particular situations, which is likely to be regulated by specific beta-glucosidases.

Using metabolome data for mathematical modeling of plant metabolic systems

Plant metabolism is characterized by a wide diversity of metabolites, with systems far more complicated than those of microorganisms. Mathematical modeling is useful for understanding dynamic behaviors of plant metabolic systems for metabolic engineering. Time-series metabolome data has great potential for estimating kinetic model parameters to construct a genome-wide metabolic network model. However, data obtained by current metabolomics techniques does not meet the requirement for constructing accurate models. In this article, we highlight novel strategies and algorithms to handle the underlying difficulties and construct dynamic in vivo models for large-scale plant metabolic systems. The coarse but efficient modeling enables the prediction of unknown mechanisms regulating plant metabolism.

Gene Discovery of Characteristic Metabolic Pathways in the Tea Plant (Camellia sinensis) Using 'Omics'-Based Network Approaches: A Future Perspective

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant (Camellia sinensis) are the primary sources of the rich flavors, fresh taste, and health benefits of tea. The decoding of genes involved in these characteristic components is still significantly lagging, which lays an obstacle for applied genetic improvement and metabolic engineering. With the popularity of high-throughout transcriptomics and metabolomics, 'omics'-based network approaches, such as gene co-expression network and gene-to-metabolite network, have emerged as powerful tools for gene discovery of plant-specialized (secondary) metabolism. Thus, it is pivotal to summarize and introduce such system-based strategies in facilitating gene identification of characteristic metabolic pathways in the tea plant (or other plants). In this review, we describe recent advances in transcriptomics and metabolomics for transcript and metabolite profiling, and highlight 'omics'-based network strategies using successful examples in model and non-model plants. Further, we summarize recent progress in 'omics' analysis for gene identification of characteristic metabolites in the tea plant. Limitations of the current strategies are discussed by comparison with 'omics'-based network approaches. Finally, we demonstrate the potential of introducing such network strategies in the tea plant, with a prospects ending for a promising network discovery of characteristic metabolite genes in the tea plant.

Metabolomics 20 years on: what have we learned and what hurdles remain?

The term metabolome was coined in 1998, by analogy to genome, transcriptome and proteome. The first research papers using the terms metabolomics, metabonomics, metabolic profiling or metabolite profiling were published shortly thereafter. In this short review we reflect on the major achievements brought about by the use of these approaches, and document the knowledge and technology gaps that are currently constraining its further development. Finally, we detail why we think that the time is ripe to refocus our efforts on the understanding of metabolic function.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LC)-mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5-10 min, depending on user experience; data processing typically takes 1-3 h, and data analysis takes ∼30 min.