MarVis-Pathway: integrative and exploratory pathway analysis of non-targeted metabolomics data

Mycorrhiza-induced resistance in citrus against Tetranychus urticae is plant species dependent and inversely correlated to basal immunity

BACKGROUND

Mycorrhizal plants show enhanced resistance to biotic stresses, but few studies have addressed mycorrhiza-induced resistance (MIR) against biotic challenges in woody plants, particularly citrus. Here we present a comparative study of two citrus species, Citrus aurantium, which is resistant to Tetranychus urticae, and Citrus reshni, which is highly susceptible to T. urticae. Although both mycorrhizal species are protected in locally infested leaves, they show very distinct responses to MIR.

RESULTS

Previous studies have indicated that C. aurantium is insensitive to MIR in systemic tissues and MIR-triggered antixenosis. Conversely, C. reshni is highly responsive to MIR which triggers local, systemic and indirect defense, and antixenosis against the pest. Transcriptional, hormonal and inhibition assays in C. reshni indicated the regulation of jasmonic acid (JA)- and abscisic acid-dependent responses in MIR. The phytohormone jasmonic acid isoleucine (JA-Ile) and the JA biosynthesis gene LOX2 are primed at early timepoints. Evidence indicates a metabolic flux from phenylpropanoids to specific flavones that are primed at 24 h post infestation (hpi). MIR also triggers the priming of naringenin in mycorrhizal C. reshni, which shows a strong correlation with several flavones and JA-Ile that over-accumulate in mycorrhizal plants. Treatment with an inhibitor of phenylpropanoid biosynthesis C4H enzyme impaired resistance and reduced the symbiosis, demonstrating that phenylpropanoids and derivatives mediate MIR in C. reshni.

CONCLUSION

MIR's effectiveness is inversely correlated to basal immunity in different citrus species, and provides multifaceted protection against T. urticae in susceptible C. reshni, activating rapid local and systemic defenses that are mainly regulated by the accumulation of specific flavones and priming of JA-dependent responses. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Wounding Triggers Wax Biosynthesis in Arabidopsis Leaves in an Abscisic Acid-Dependent and Jasmonoyl-Isoleucine-Dependent Manner

Wounding caused by insects or abiotic factors such as wind and hail can cause severe stress for plants. Intrigued by the observation that wounding induces expression of genes involved in surface wax synthesis in a jasmonoyl-isoleucine (JA-Ile)-independent manner, the role of wax biosynthesis and respective genes upon wounding was investigated. Wax, a lipid-based barrier, protects plants both from environmental threats and from an uncontrolled loss of water. Its biosynthesis is described to be regulated by abscisic acid (ABA), whereas the main wound signal is the hormone JA-Ile. We show in this study that genes coding for enzymes of surface wax synthesis are induced upon wounding in Arabidopsis thaliana leaves in a JA-Ile-independent but an ABA-dependent manner. Furthermore, the ABA-dependent transcription factor MYB96 is a key regulator of wax biosynthesis upon wounding. On the metabolite level, wound-induced wax accumulation is strongly reduced in JA-Ile-deficient plants, but this induction is only slightly decreased in ABA-reduced plants. To further analyze the ABA-dependent wound response, we conducted wounding experiments in high humidity. They show that high humidity prevents the wound-induced wax accumulation in A. thaliana leaves. Together the data presented in this study show that wound-induced wax accumulation is JA-Ile-dependent on the metabolite level, but the expression of genes coding for enzymes of wax synthesis is regulated by ABA.

Systemic analysis of metabolome reconfiguration in Arabidopsis after abiotic stressors uncovers metabolites that modulate defense against pathogens

Understanding plant immune responses is complex because of the high interdependence among biological processes in homeostatic networks. Hence, the integration of environmental cues causes network rewiring that interferes with defense responses. Similarly, plants retain molecular signatures configured under abiotic stress periods to rapidly respond to recurrent stress, and these can alter immunity. Metabolome changes imposed by abiotic stressors are persistent, although their impact on defense remains to be clarified. In this study, we profiled metabolomes of Arabidopsis plants under several abiotic stress treatments applied individually or simultaneously to capture temporal trajectories in metabolite composition during adverse conditions and recovery. Further systemic analysis was performed to address the relevance of metabolome changes and extract central features to be tested in planta. Our results demonstrate irreversibility in major fractions of metabolome changes as a general pattern in response to abiotic stress periods. Functional analysis of metabolomes and co-abundance networks points to convergence in the reconfiguration of organic acid and secondary metabolite metabolism. Arabidopsis mutant lines for components related to these metabolic pathways showed altered defense capacities against different pathogens. Collectively, our data suggest that sustained metabolome changes configured in adverse environments can act as modulators of immune responses and provide evidence for a new layer of regulation in plant defense.

Ex vivo metabolomics-A hypothesis-free approach to identify native substrate(s) and product(s) of orphan enzymes

Over the past decade, the number of fully sequenced genomes has increased at an awe-inspiring pace. Similarly, the quality and scope of tools for the prediction of both protein structure and function has seen vast improvements. However, to pinpoint the exact function of a protein, for instance the exact reaction catalyzed by an enzyme, experimental evidence is crucial. At the same time, this step is the main bottleneck when generating a conclusive model for the function of an enzyme and to interpret its function in a physiological context. Hence, a comprehensive experimental strategy for functional annotation of enzymes that is as efficient as possible is required. Ex vivo metabolomics is a powerful non-targeted approach that overcomes several of the challenges inherent to in vitro characterization of enzymes with unknown functions. By incubating the recombinant enzyme of interest in a quasi-native metabolite extract from its tissue of origin under specific environmental and developmental conditions, the complete native substrate range can be tested in a single assay. This unlocks compounds that are commercially unavailable or otherwise difficult to procure. Coupled with non-targeted metabolomics analysis, ex vivo has the capability to test for and identify even unexpected substrates and assign the respective products of the enzymatic reaction.

Metabolite fingerprinting: A powerful metabolomics approach for marker identification and functional gene annotation

Non-targeted metabolome approaches aim to detect metabolite markers related to stress, disease, developmental or genetic perturbation. In the later context, it is also a powerful means for functional gene annotation. A prerequisite for non-targeted metabolome analyses are methods for comprehensive metabolite extraction. We present three extraction protocols for a highly efficient extraction of metabolites from plant material with a very broad metabolite coverage. The presented metabolite fingerprinting workflow is based on liquid chromatography high resolution accurate mass spectrometry (LC-HRAM-MS), which provides suitable separation of the complex sample matrix for the analysis of compounds of different polarity by positive and negative electrospray ionization and mass spectrometry. The resulting data sets are then analyzed with the software suite MarVis and the web-based interface MetaboAnalyst. MarVis offers a straightforward workflow for statistical analysis, data merging as well as visualization of multivariate data, while MetaboAnalyst is used in our hands as complementary software for statistics, correlation networks and figure generation. Finally, MarVis provides access to species-specific metabolite and pathway data bases like KEGG and BioCyc and to custom data bases tailored by the user to connect the identified markers or features with metabolites. In addition, identified marker candidates can be interactively visualized and inspected in metabolic pathway maps by KEGG pathways for a more detailed functional annotation and confirmed by mass spectrometry fragmentation experiments or coelution with authentic standards. Together this workflow is a valuable toolbox to identify novel metabolites, metabolic steps or regulatory principles and pathways.

N-Hydroxy pipecolic acid methyl ester is involved in Arabidopsis immunity

The biosynthesis of N-hydroxy pipecolic acid (NHP) has been intensively studied, though knowledge on its metabolic turnover is still scarce. To close this gap, we discovered three novel metabolites via metabolite fingerprinting in Arabidopsis thaliana leaves after Pseudomonas infection and UV-C treatment. Exact mass information and fragmentation by tandem mass spectrometry (MS/MS) suggest a methylated derivative of NHP (MeNHP), an NHP-OGlc-hexosyl conjugate (NHP-OGlc-Hex), and an additional NHP-OGlc-derivative. All three compounds were formed in wild-type leaves but were not present in the NHP-deficient mutant fmo1-1. The identification of these novel NHP-based molecules was possible by a dual-infiltration experiment using a mixture of authentic NHP and D9-NHP standards for leaf infiltration followed by UV-C treatment. Interestingly, the signal intensity of MeNHP and other NHP-derived metabolites increased in ugt76b1-1 mutant plants. For MeNHP, we unequivocally determined the site of methylation at the carboxylic acid moiety. MeNHP application by leaf infiltration leads to the detection of a MeNHP-OGlc as well as NHP, suggesting MeNHP hydrolysis to NHP. This is in line with the observation that MeNHP infiltration is able to rescue the fmo1-1 susceptible phenotype against Hyaloperonospora arabidopsidis Noco 2. Together, these data suggest MeNHP as an additional storage or transport form of NHP.

Plastidic membrane lipids are oxidized by a lipoxygenase in Lobosphaera incisa

Green microalgae can accumulate neutral lipids, as part of a general lipid remodeling mechanism under stress such as nitrogen starvation. Lobosphaera incisa is of special interest because of its unique TAG acyl chain composition, especially 20:4 (n-6) can reach up to 21% of dry weight after nitrogen starvation. In order to identify factors that may influence the accumulation of polyunsaturated fatty acids (PUFAs), we identified recently a linoleate 13-lipoxygenase (LiLOX). It shares highest identity with plastidic enzymes from vascular plants and is induced upon nitrogen starvation. Here, we confirmed the localization of LiLOX in the stroma of plastids via transient expression in epithelial onion cells. In order to further characterize this enzyme, we focused on the identification of the endogenous substrate of LiLOX. In this regard, an ex vivo enzymatic assay, coupled with non-targeted analysis via mass spectrometry allowed the identification of MGDG, DGDG and PC as three substrate candidates, later confirmed via in vitro assays. Further investigation revealed that LiLOX has preferences towards the lipid class MGDG, which seems in agreement with its localization in the galactolipid rich plastid. Altogether, this study shows the first characterization of plastidic LOX from green algae, showing preference for MGDGs. However, lipidomics analysis did neither reveal an endogenous LiLOX product nor the final end product of MGDG oxidation. Nevertheless, the latter is a key to understanding the role of this enzyme and since its expression is highest during the degradation of the plastidic membrane, it is tempting to assume its involvement in this process.

Survey for Computer-Aided Tools and Databases in Metabolomics

Metabolomics has advanced from innovation and functional genomics tools and is currently a basis in the big data-led precision medicine era. Metabolomics is promising in the pharmaceutical field and clinical research. However, due to the complexity and high throughput data generated from such experiments, data mining and analysis are significant challenges for researchers in the field. Therefore, several efforts were made to develop a complete workflow that helps researchers analyze data. This paper introduces a review of the state-of-the-art computer-aided tools and databases in metabolomics established in recent years. The paper provides computational tools and resources based on functionality and accessibility and provides hyperlinks to web pages to download or use. This review aims to present the latest computer-aided tools, databases, and resources to the metabolomics community in one place.

A comprehensive survey of the approaches for pathway analysis using multi-omics data integration

Pathway analysis has been widely used to detect pathways and functions associated with complex disease phenotypes. The proliferation of this approach is due to better interpretability of its results and its higher statistical power compared with the gene-level statistics. A plethora of pathway analysis methods that utilize multi-omics setup, rather than just transcriptomics or proteomics, have recently been developed to discover novel pathways and biomarkers. Since multi-omics gives multiple views into the same problem, different approaches are employed in aggregating these views into a comprehensive biological context. As a result, a variety of novel hypotheses regarding disease ideation and treatment targets can be formulated. In this article, we review 32 such pathway analysis methods developed for multi-omics and multi-cohort data. We discuss their availability and implementation, assumptions, supported omics types and databases, pathway analysis techniques and integration strategies. A comprehensive assessment of each method's practicality, and a thorough discussion of the strengths and drawbacks of each technique will be provided. The main objective of this survey is to provide a thorough examination of existing methods to assist potential users and researchers in selecting suitable tools for their data and analysis purposes, while highlighting outstanding challenges in the field that remain to be addressed for future development.

Multi-omics analysis of xylem sap uncovers dynamic modulation of poplar defenses by ammonium and nitrate

Xylem sap is the major transport route for nutrients from roots to shoots. In the present study, we investigated how variations in nitrogen (N) nutrition affected the metabolome and proteome of xylem sap and the growth of the xylem endophyte Brennaria salicis, and we also report transcriptional re-wiring of leaf defenses in poplar (Populus × canescens). We supplied poplars with high, intermediate or low concentrations of ammonium or nitrate. We identified 288 unique proteins in xylem sap. Approximately 85% of the xylem sap proteins were shared among ammonium- and nitrate-supplied plants. The number of proteins increased with increasing N supply but the major functional categories (catabolic processes, cell wall-related enzymes, defense) were unaffected. Ammonium nutrition caused higher abundances of amino acids and carbohydrates, whereas nitrate caused higher malate levels in xylem sap. Pipecolic acid and N-hydroxy-pipecolic acid increased, whereas salicylic acid and jasmonoyl-isoleucine decreased, with increasing N nutrition. Untargeted metabolome analyses revealed 2179 features in xylem sap, of which 863 were differentially affected by N treatments. We identified 124 metabolites, mainly from specialized metabolism of the groups of salicinoids, phenylpropanoids, phenolics, flavonoids, and benzoates. Their abundances increased with decreasing N, except coumarins. Brennaria salicis growth was reduced in nutrient-supplemented xylem sap of low- and high- NO₃^- -fed plants compared to that of NH₄⁺ -fed plants. The drastic changes in xylem sap composition caused massive changes in the transcriptional landscape of leaves and recruited defenses related to systemic acquired and induced systemic resistance. Our study uncovers unexpected complexity and variability of xylem composition with consequences for plant defenses.

A non-targeted metabolomics analysis identifies wound-induced oxylipins in Physcomitrium patens

Plant oxylipins are a class of lipid-derived signaling molecules being involved in the regulation of various biotic and abiotic stress responses. A major class of oxylipins are the circular derivatives to which 12-oxo-phytodienoic acid (OPDA) and its metabolite jasmonic acid (JA) belong. While OPDA and its shorter chain homologue dinor-OPDA (dnOPDA) seem to be ubiquitously found in land plants ranging from bryophytes to angiosperms, the occurrence of JA and its derivatives is still under discussion. The bryophyte Physcomitrium patens has received increased scientific interest as a non-vascular plant model organism over the last decade. Therefore, we followed the metabolism upon wounding by metabolite fingerprinting with the aim to identify jasmonates as well as novel oxylipins in P. patens. A non-targeted metabolomics approach was used to reconstruct the metabolic pathways for the synthesis of oxylipins, derived from roughanic, linoleic, α-linolenic, and arachidonic acid in wild type, the oxylipin-deficient mutants of Ppaos1 and Ppaos2, the mutants of Ppdes being deficient in all fatty acids harboring a Δ⁶-double bond and the C20-fatty acid-deficient mutants of Ppelo. Beside of OPDA, iso-OPDA, dnOPDA, and iso-dnOPDA, three additional C18-compounds and a metabolite being isobaric to JA were identified to accumulate after wounding. These findings can now serve as foundation for future research in determining, which compound(s) will serve as native ligand(s) for the oxylipin-receptor COI1 in P. patens.

Plants Metabolome Study: Emerging Tools and Techniques

Metabolomics is now considered a wide-ranging, sensitive and practical approach to acquire useful information on the composition of a metabolite pool present in any organism, including plants. Investigating metabolomic regulation in plants is essential to understand their adaptation, acclimation and defense responses to environmental stresses through the production of numerous metabolites. Moreover, metabolomics can be easily applied for the phenotyping of plants; and thus, it has great potential to be used in genome editing programs to develop superior next-generation crops. This review describes the recent analytical tools and techniques available to study plants metabolome, along with their significance of sample preparation using targeted and non-targeted methods. Advanced analytical tools, like gas chromatography-mass spectrometry (GC-MS), liquid chromatography mass-spectroscopy (LC-MS), capillary electrophoresis-mass spectrometry (CE-MS), fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) matrix-assisted laser desorption/ionization (MALDI), ion mobility spectrometry (IMS) and nuclear magnetic resonance (NMR) have speed up precise metabolic profiling in plants. Further, we provide a complete overview of bioinformatics tools and plant metabolome database that can be utilized to advance our knowledge to plant biology.

Mycorrhizal symbiosis primes the accumulation of antiherbivore compounds and enhances herbivore mortality in tomato

Plant association with arbuscular mycorrhizal fungi (AMF) can increase their ability to overcome multiple stresses, but their impact on plant interactions with herbivorous insects is controversial. Here we show higher mortality of the leaf-chewer Spodoptera exigua when fed on tomato plants colonized by the AMF Funneliformis mosseae, evidencing mycorrhiza-induced resistance. In search of the underlying mechanisms, an untargeted metabolomic analysis through ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS) was performed. The results showed that mycorrhizal symbiosis had a very limited impact on the leaf metabolome in the absence of stress, but significantly modulated the response to herbivory in the damaged area. A cluster of over accumulated metabolites was identified in those leaflets damaged by S. exigua feeding in mycorrhizal plants, while unwounded distal leaflets responded similar to those from non-mycorrhizal plants. These primed-compounds were mostly related to alkaloids, fatty acid derivatives and phenylpropanoid-polyamine conjugates. The deleterious effect on larval survival of some of these compounds, including the alkaloid physostigmine, the fatty acid derivatives 4-oxododecanedioic acid and azelaic acid, was confirmed. Thus, our results evidence the impact of AMF on metabolic reprograming upon herbivory that leads to a primed accumulation of defensive compounds.

The glycosyltransferase UGT76B1 modulates N-hydroxy-pipecolic acid homeostasis and plant immunity

The tradeoff between growth and defense is a critical aspect of plant immunity. Therefore, the plant immune response needs to be tightly regulated. Salicylic acid (SA) is an important plant hormone regulating defense against biotrophic pathogens. Recently, N-hydroxy-pipecolic acid (NHP) was identified as another regulator for plant innate immunity and systemic acquired resistance (SAR). Although the biosynthetic pathway leading to NHP formation is already been identified, how NHP is further metabolized is unclear. Here, we present UGT76B1 as a uridine diphosphate-dependent glycosyltransferase (UGT) that modifies NHP by catalyzing the formation of 1-O-glucosyl-pipecolic acid in Arabidopsis thaliana. Analysis of T-DNA and clustered regularly interspaced short palindromic repeats (CRISPR) knock-out mutant lines of UGT76B1 by targeted and nontargeted ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) underlined NHP and SA as endogenous substrates of this enzyme in response to Pseudomonas infection and UV treatment. ugt76b1 mutant plants have a dwarf phenotype and constitutive defense response which can be suppressed by loss of function of the NHP biosynthetic enzyme FLAVIN-DEPENDENT MONOOXYGENASE 1 (FMO1). This suggests that elevated accumulation of NHP contributes to the enhanced disease resistance in ugt76b1. Externally applied NHP can move to distal tissue in ugt76b1 mutant plants. Although glycosylation is not required for the long-distance movement of NHP during SAR, it is crucial to balance growth and defense.

Root-to-shoot signalling in mycorrhizal tomato plants upon Botrytis cinerea infection

Arbuscular mycorrhizal symbiosis is restricted in roots, but it also improves shoot responses against leaf challenges, a phenomenon known as Mycorrhiza-Induced Resistance (MIR). This study focuses on mycorrhizal root signals that may orchestrate shoot defence responses. Metabolomic analysis of non-mycorrhizal and mycorrhizal plants upon Botrytis cinerea infection showed that roots rearrange their metabolome mostly in response to the symbiosis, whereas in shoots a stronger impact of the infection is observed. Specific clusters of compounds in shoots and roots display a priming profile suggesting an implication in the enhanced resistance observed in mycorrhizal plants. Among the primed pathways in roots, lignans showed the highest number of hits followed by oxocarboxylic acids, compounds of the amino acid metabolism, and phytohormones. The lignan yatein was present at higher concentrations in roots, root efflux and leaves of mycorrhizal plants This lignan displayed in vitro antimicrobial activity against B. cinerea and it was also functional protecting tomato plants. Besides, several JA defence-related genes were upregulated in mycorrhizal roots regardless of the pathogen infection, whereas PIN-II was primed in roots of mycorrhizal infected plants. These observations suggest that the enhanced resistance in shoots during MIR may be coordinated by lignans and oxylipins with the participation of roots.

Exogenous strigolactones impact metabolic profiles and phosphate starvation signalling in roots

Strigolactones (SLs) are important ex-planta signalling molecules in the rhizosphere, promoting the association with beneficial microorganisms, but also affecting plant interactions with harmful organisms. They are also plant hormones in-planta, acting as modulators of plant responses under nutrient-deficient conditions, mainly phosphate (Pi) starvation. In the present work, we investigate the potential role of SLs as regulators of early Pi starvation signalling in plants. A short-term pulse of the synthetic SL analogue 2'-epi-GR24 promoted SL accumulation and the expression of Pi starvation markers in tomato and wheat under Pi deprivation. 2'-epi-GR24 application also increased SL production and the expression of Pi starvation markers under normal Pi conditions, being its effect dependent on the endogenous SL levels. Remarkably, 2'-epi-GR24 also impacted the root metabolic profile under these conditions, promoting the levels of metabolites associated to plant responses to Pi limitation, thus partially mimicking the pattern observed under Pi deprivation. The results suggest an endogenous role for SLs as Pi starvation signals. In agreement with this idea, SL-deficient plants were less sensitive to this stress. Based on the results, we propose that SLs may act as early modulators of plant responses to P starvation.

Lolium perenne apoplast metabolomics for identification of novel metabolites produced by the symbiotic fungus Epichloë festucae

Epichloë festucae is an endophytic fungus that forms a symbiotic association with Lolium perenne. Here we analysed how the metabolome of the ryegrass apoplast changed upon infection of this host with sexual and asexual isolates of E. festucae. A metabolite fingerprinting approach was used to analyse the metabolite composition of apoplastic wash fluid from uninfected and infected L. perenne. Metabolites enriched or depleted in one or both of these treatments were identified using a set of interactive tools. A genetic approach in combination with tandem MS was used to identify a novel product of a secondary metabolite gene cluster. Metabolites likely to be present in the apoplast were identified using MarVis in combination with the BioCyc and KEGG databases, and an in-house Epichloë metabolite database. We were able to identify the known endophyte-specific metabolites, peramine and epichloëcyclins, as well as a large number of unknown markers. To determine whether these methods can be applied to the identification of novel Epichloë-derived metabolites, we deleted a gene encoding a NRPS (lgsA) that is highly expressed in planta. Comparative MS analysis of apoplastic wash fluid from wild-type- vs mutant-infected plants identified a novel Leu/Ile glycoside metabolite present in the former.

Open-Source Software Tools, Databases, and Resources for Single-Cell and Single-Cell-Type Metabolomics

In this age of -omics data-guided big data revolution, metabolomics has received significant attention as compared to genomics, transcriptomics, and proteomics for its proximity to the phenotype, the promises it makes and the challenges it throws. Although metabolomes of entire organisms, organs, biofluids, and tissues are of immense interest, a cell-specific resolution is deemed critical for biomedical applications where a granular understanding of cellular metabolism at cell-type and subcellular resolution is desirable. Mass spectrometry (MS) is a versatile technique that is used to analyze a broad range of compounds from different species and cell-types, with high accuracy, resolution, sensitivity, selectivity, and fast data acquisition speeds. With recent advances in MS and spectroscopy-based platforms, the research community is able to generate high-throughput data sets from single cells. However, it is challenging to handle, store, process, analyze, and interpret data in a routine manner. In this treatise, I present a workflow of metabolomics data generation from single cells and single-cell types to their analysis, visualization, and interpretation for obtaining biological insights.

Metabolomics: A Way Forward for Crop Improvement

Metabolomics is an emerging branch of "omics" and it involves identification and quantification of metabolites and chemical footprints of cellular regulatory processes in different biological species. The metabolome is the total metabolite pool in an organism, which can be measured to characterize genetic or environmental variations. Metabolomics plays a significant role in exploring environment-gene interactions, mutant characterization, phenotyping, identification of biomarkers, and drug discovery. Metabolomics is a promising approach to decipher various metabolic networks that are linked with biotic and abiotic stress tolerance in plants. In this context, metabolomics-assisted breeding enables efficient screening for yield and stress tolerance of crops at the metabolic level. Advanced metabolomics analytical tools, like non-destructive nuclear magnetic resonance spectroscopy (NMR), liquid chromatography mass-spectroscopy (LC-MS), gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography (HPLC), and direct flow injection (DFI) mass spectrometry, have sped up metabolic profiling. Presently, integrating metabolomics with post-genomics tools has enabled efficient dissection of genetic and phenotypic association in crop plants. This review provides insight into the state-of-the-art plant metabolomics tools for crop improvement. Here, we describe the workflow of plant metabolomics research focusing on the elucidation of biotic and abiotic stress tolerance mechanisms in plants. Furthermore, the potential of metabolomics-assisted breeding for crop improvement and its future applications in speed breeding are also discussed. Mention has also been made of possible bottlenecks and future prospects of plant metabolomics.

The glycosyltransferase UGT76E1 significantly contributes to 12-O-glucopyranosyl-jasmonic acid formation in wounded Arabidopsis thaliana leaves

Jasmonoyl-isoleucine (JA-Ile) is a phytohormone that orchestrates plant defenses in response to wounding, feeding insects, or necrotrophic pathogens. JA-Ile metabolism has been studied intensively, but its catabolism as a potentially important mechanism for the regulation of JA-Ile-mediated signaling is not well-understood. Especially the enzyme(s) responsible for specifically glycosylating 12-hydroxy-jasmonic acid (12-OH-JA) and thereby producing 12-O-glucopyranosyl-jasmonic acid (12-O-Glc-JA) is still elusive. Here, we used co-expression analyses of available Arabidopsis thaliana transcriptomic data, identifying four UDP-dependent glycosyltransferase (UGT) genes as wound-induced and 12-OH-JA-related, namely, UGT76E1, UGT76E2, UGT76E11, and UGT76E12 We heterologously expressed and purified the corresponding proteins to determine their individual substrate specificities and kinetic parameters. We then used an ex vivo metabolite-fingerprinting approach to investigate these proteins in conditions as close as possible to their natural environment, with an emphasis on greatly extending the range of potential substrates. As expected, we found that UGT76E1 and UGT76E2 are 12-OH-JA-UGTs, with UGT76E1 contributing a major in vivo UGT activity, as deduced from Arabidopsis mutants with abolished or increased UGT gene expression. In contrast, recombinant UGT76E11 acted on an unidentified compound and also glycosylated two other oxylipins, 11-hydroxy-7,9,13-hexadecatrienoic acid (11-HHT) and 13-hydroxy-9,11,15-octadecatrienoic acid (13-HOT), which were also accepted by recombinant UGT76E1, UGT76E2, and UGT76E12 enzymes. UGT76E12 glycosylated 12-OH-JA only to a low extent, but also accepted an artificial hydroxylated fatty acid and low amounts of kaempferol. In conclusion, our findings have elucidated the missing step in the wound-induced synthesis of 12-O-glucopyranosyl-jasmonic acid in A. thaliana.

Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community

The use of multiple omics techniques (i.e., genomics, transcriptomics, proteomics, and metabolomics) is becoming increasingly popular in all facets of life science. Omics techniques provide a more holistic molecular perspective of studied biological systems compared to traditional approaches. However, due to their inherent data differences, integrating multiple omics platforms remains an ongoing challenge for many researchers. As metabolites represent the downstream products of multiple interactions between genes, transcripts, and proteins, metabolomics, the tools and approaches routinely used in this field could assist with the integration of these complex multi-omics data sets. The question is, how? Here we provide some answers (in terms of methods, software tools and databases) along with a variety of recommendations and a list of continuing challenges as identified during a peer session on multi-omics integration that was held at the recent 'Australian and New Zealand Metabolomics Conference' (ANZMET 2018) in Auckland, New Zealand (Sept. 2018). We envisage that this document will serve as a guide to metabolomics researchers and other members of the community wishing to perform multi-omics studies. We also believe that these ideas may allow the full promise of integrated multi-omics research and, ultimately, of systems biology to be realized.

Current Trends in Cancer Biomarker Discovery Using Urinary Metabolomics: Achievements and New Challenges

BACKGROUND

The development of effective screening methods for early cancer detection is one of the foremost challenges facing modern cancer research. Urinary metabolomics has recently emerged as a potentially transformative approach to cancer biomarker discovery owing to its noninvasive sampling characteristics and robust analytical feasibility.

OBJECTIVE

To provide an overview of new developments in urinary metabolomics, cover the most promising aspects of hyphenated techniques in untargeted and targeted metabolomics, and to discuss technical and clinical limitations in addition to the emerging challenges in the field of urinary metabolomics and its application to cancer biomarker discovery.

METHODS

A systematic review of research conducted in the past five years on the application of urinary metabolomics to cancer biomarker discovery was performed. Given the breadth of this topic, our review focused on the five most widely studied cancers employing urinary metabolomics approaches, including lung, breast, bladder, prostate, and ovarian cancers.

RESULTS

As an extension of conventional metabolomics, urinary metabolomics has benefitted from recent technological developments in nuclear magnetic resonance, mass spectrometry, gas and liquid chromatography, and capillary electrophoresis that have improved urine metabolome coverage and analytical reproducibility. Extensive metabolic profiling in urine has revealed a significant number of altered metabolic pathways and putative biomarkers, including pteridines, modified nucleosides, and acylcarnitines, that have been associated with cancer development and progression.

CONCLUSION

Urinary metabolomics presents a transformative new approach toward cancer biomarker discovery with high translational capacity to early cancer screening.

Analytical Methods for Detection of Plant Metabolomes Changes in Response to Biotic and Abiotic Stresses

Abiotic and biotic stresses are the main reasons of substantial crop yield losses worldwide. Research devoted to reveal mechanisms of plant reactions during their interactions with the environment are conducted on the level of genome, transcriptome, proteome, and metabolome. Data obtained during these studies would permit to define biochemical and physiological mechanisms of plant resistance or susceptibility to affecting factors/stresses. Metabolomics based on mass spectrometric techniques is an important part of research conducted in the direction of breeding new varieties of crop plants tolerant to the affecting stresses and possessing good agronomical features. Studies of this kind are carried out on model, crop and resurrection plants. Metabolites profiling yields large sets of data and due to this fact numerous advanced statistical and bioinformatic methods permitting to obtain qualitative and quantitative evaluation of the results have been developed. Moreover, advanced integration of metabolomics data with these obtained on other omics levels: genome, transcriptome and proteome should be carried out. Such a holistic approach would bring us closer to understanding biochemical and physiological processes of the cell and whole plant interacting with the environment and further apply these observations in successful breeding of stress tolerant or resistant crop plants.

Comprehensive LC-MS-Based Metabolite Fingerprinting Approach for Plant and Fungal-Derived Samples

Liquid chromatography-mass spectrometry (LC-MS)-based nontargeted metabolome approaches aim to detect chemotypes as markers for stress, disease, developmental, or genetic perturbation. Herein, we present a metabolite fingerprinting workflow, which is applicable for the analysis of tissues and fluids derived from plants and fungi. This is based on a broad metabolite coverage by a two-phase extraction and the separate analysis of polar, and nonpolar compounds by positive as well as negative electrospray ionization. For analysis of the resulting comprehensive data sets, the interactive and user-friendly data mining software MarVis-Suite is used. It supports statistical analysis, adduct correction, data merging, as well as visualization of multivariate data. Finally, MarVis shapes marker identification to the organism of interest. Therefore, it provides access to the species-specific databases KEGG and BioCyc and to custom databases tailored by the user.

Root metabolic plasticity underlies functional diversity in mycorrhiza-enhanced stress tolerance in tomato

Arbuscular mycorrhizal (AM) symbioses can improve plant tolerance to multiple stresses. We compared three AM fungi (AMF) from different genera, one of them isolated from a dry and saline environment, in terms of their ability to increase tomato tolerance to moderate or severe drought or salt stress. Plant physiological parameters and metabolic profiles were compared in order to find the molecular mechanisms underlying plant protection against stress. Mycorrhizal growth response was determined, and ultrahigh-performance LC-MS was used to compare the metabolic profile of plants under the different treatments. All AMF increased plant tolerance to stress, and the positive effects of the symbiosis were correlated with the severity of the stress. The AMF isolated from the stressful environment was the most effective in improving plant tolerance to salt stress. Differentially accumulated compounds were identified and the antistress properties of some of them were confirmed. We demonstrate that AM symbioses increase plant metabolic plasticity to cope with stress. Some responses were common to all AMF tested, while others were specifically related to particular isolates. Important metabolism reprograming was evidenced upon salt stress, and we identified metabolic pathways and compounds differentially accumulated in mycorrhizas that may underlie their enhanced tolerance to stress.

MYB72-dependent coumarin exudation shapes root microbiome assembly to promote plant health

Plant roots nurture a tremendous diversity of microbes via exudation of photosynthetically fixed carbon sources. In turn, probiotic members of the root microbiome promote plant growth and protect the host plant against pathogens and pests. In the Arabidopsis thaliana-Pseudomonas simiae WCS417 model system the root-specific transcription factor MYB72 and the MYB72-controlled β-glucosidase BGLU42 emerged as important regulators of beneficial rhizobacteria-induced systemic resistance (ISR) and iron-uptake responses. MYB72 regulates the biosynthesis of iron-mobilizing fluorescent phenolic compounds, after which BGLU42 activity is required for their excretion into the rhizosphere. Metabolite fingerprinting revealed the antimicrobial coumarin scopoletin as a dominant metabolite that is produced in the roots and excreted into the rhizosphere in a MYB72- and BGLU42-dependent manner. Shotgun-metagenome sequencing of root-associated microbiota of Col-0, myb72, and the scopoletin biosynthesis mutant f6'h1 showed that scopoletin selectively impacts the assembly of the microbial community in the rhizosphere. We show that scopoletin selectively inhibits the soil-borne fungal pathogens Fusarium oxysporum and Verticillium dahliae, while the growth-promoting and ISR-inducing rhizobacteria P. simiae WCS417 and Pseudomonas capeferrum WCS358 are highly tolerant of the antimicrobial effect of scopoletin. Collectively, our results demonstrate a role for coumarins in microbiome assembly and point to a scenario in which plants and probiotic rhizobacteria join forces to trigger MYB72/BGLU42-dependent scopolin production and scopoletin excretion, resulting in improved niche establishment for the microbial partner and growth and immunity benefits for the host plant.

MYB72-dependent coumarin exudation shapes root microbiome assembly to promote plant health

Plant roots nurture a large diversity of soil microbes via exudation of chemical compounds into the rhizosphere. In turn, beneficial root microbiota promote plant growth and immunity. The root-specific transcription factor MYB72 has emerged as a central regulator in this process. Here, we show that MYB72 regulates the excretion of the coumarin scopoletin, an iron-mobilizing phenolic compound with selective antimicrobial activity that shapes the root-associated microbial community. Selected soil-borne fungal pathogens appeared to be highly sensitive to the antimicrobial activity of scopoletin, while two MYB72-inducing beneficial rhizobacteria were tolerant. Our results suggest that probiotic root-associated microbes that activate the iron-deficiency response during colonization stimulate MYB72-dependent excretion of scopoletin, thereby potentially improving their niche establishment and enhancing plant growth and protection.

Plant roots nurture a tremendous diversity of microbes via exudation of photosynthetically fixed carbon sources. In turn, probiotic members of the root microbiome promote plant growth and protect the host plant against pathogens and pests. In the Arabidopsis thaliana–Pseudomonas simiae WCS417 model system the root-specific transcription factor MYB72 and the MYB72-controlled β-glucosidase BGLU42 emerged as important regulators of beneficial rhizobacteria-induced systemic resistance (ISR) and iron-uptake responses. MYB72 regulates the biosynthesis of iron-mobilizing fluorescent phenolic compounds, after which BGLU42 activity is required for their excretion into the rhizosphere. Metabolite fingerprinting revealed the antimicrobial coumarin scopoletin as a dominant metabolite that is produced in the roots and excreted into the rhizosphere in a MYB72- and BGLU42-dependent manner. Shotgun-metagenome sequencing of root-associated microbiota of Col-0, myb72, and the scopoletin biosynthesis mutant f6′h1 showed that scopoletin selectively impacts the assembly of the microbial community in the rhizosphere. We show that scopoletin selectively inhibits the soil-borne fungal pathogens Fusarium oxysporum and Verticillium dahliae, while the growth-promoting and ISR-inducing rhizobacteria P. simiae WCS417 and Pseudomonas capeferrum WCS358 are highly tolerant of the antimicrobial effect of scopoletin. Collectively, our results demonstrate a role for coumarins in microbiome assembly and point to a scenario in which plants and probiotic rhizobacteria join forces to trigger MYB72/BGLU42-dependent scopolin production and scopoletin excretion, resulting in improved niche establishment for the microbial partner and growth and immunity benefits for the host plant.

Mycorrhizal tomato plants fine tunes the growth-defence balance upon N depleted root environments

In low nutritive environments, the uptake of N by arbuscular mycorrhizal (AM) fungi may confer competitive advantages for the host. The present study aims to understand how mycorrhizal tomato plants perceive and then prepare for an N depletion in the root environment. Plants colonized by Rhizophagus irregularis displayed improved responses to a lack of N than nonmycorrhizal (NM) plants. These responses were accomplished by a complex metabolic and transcriptional rearrangement that mostly affected the gibberellic acid and jasmonic acid pathways involving DELLA and JAZ1 genes, which were responsive to changes in the C/N imbalance of the plant. N starved mycorrhizal plants showed lower C/N equilibrium in the shoots than starved NM plants and concomitantly a downregulation of the JAZ1 repressor and the increased expression of the DELLA gene, which translated into a more active oxylipin pathway in mycorrhizal plants. In addition, the results support a priorization in AM plants of stress responses over growth. Therefore, these plants were better prepared for an expected stress. Furthermore, most metabolites that were severely reduced in NM plants following the N depletion remained unaltered in starved AM plants compared with those normally fertilized, suggesting that the symbiosis buffered the stress, improving plant development in a stressed environment.

Beyond genomics: understanding exposotypes through metabolomics

BACKGROUND

Over the past 20 years, advances in genomic technology have enabled unparalleled access to the information contained within the human genome. However, the multiple genetic variants associated with various diseases typically account for only a small fraction of the disease risk. This may be due to the multifactorial nature of disease mechanisms, the strong impact of the environment, and the complexity of gene-environment interactions. Metabolomics is the quantification of small molecules produced by metabolic processes within a biological sample. Metabolomics datasets contain a wealth of information that reflect the disease state and are consequent to both genetic variation and environment. Thus, metabolomics is being widely adopted for epidemiologic research to identify disease risk traits. In this review, we discuss the evolution and challenges of metabolomics in epidemiologic research, particularly for assessing environmental exposures and providing insights into gene-environment interactions, and mechanism of biological impact.

MAIN TEXT

Metabolomics can be used to measure the complex global modulating effect that an exposure event has on an individual phenotype. Combining information derived from all levels of protein synthesis and subsequent enzymatic action on metabolite production can reveal the individual exposotype. We discuss some of the methodological and statistical challenges in dealing with this type of high-dimensional data, such as the impact of study design, analytical biases, and biological variance. We show examples of disease risk inference from metabolic traits using metabolome-wide association studies. We also evaluate how these studies may drive precision medicine approaches, and pharmacogenomics, which have up to now been inefficient. Finally, we discuss how to promote transparency and open science to improve reproducibility and credibility in metabolomics.

CONCLUSIONS

Comparison of exposotypes at the human population level may help understanding how environmental exposures affect biology at the systems level to determine cause, effect, and susceptibilities. Juxtaposition and integration of genomics and metabolomics information may offer additional insights. Clinical utility of this information for single individuals and populations has yet to be routinely demonstrated, but hopefully, recent advances to improve the robustness of large-scale metabolomics will facilitate clinical translation.

Accurate and easy method for systemin quantification and examining metabolic changes under different endogenous levels

BACKGROUND

Systemin has been extensively studied since it was discovered and is described as a peptidic hormone in tomato plants and other Solanaceae. Jasmonic acid and systemin are proposed to act through a positive feed-back loop with jasmonic acid, playing synergistic roles in response to both wounding and insect attack. Despite its biological relevance, most studies regarding the function of systemin in defence have been studied via PROSYSTEMIN (PROSYS) gene expression, which encodes the propeptide prosystemin that is later cleaved to systemin (SYS). Interestingly, hardly any studies have been based on quantification of the peptide.

RESULTS

In this study, a simple and accurate method for systemin quantification was developed to understand its impact on plant metabolism. The basal levels of systemin were found to be extremely low. To study the role of endogenous systemin on plant metabolism, systemin was quantified in a transgenic line overexpressing the PROSYS gene (PS+) and in a silenced antisense line (PS-). We evaluated the relevance of systemin in plant metabolism by analysing the metabolomic profiles of both lines compared to wildtype plants through untargeted metabolomic profiling. Compounds within the lignan biosynthesis and tyrosine metabolism pathways strongly accumulated in PS+ compared to wild-type plants and to plants from the PS- line. The exogenous treatments with SYS enhanced accumulation of lignans, which confirms the role of SYS in cell wall reinforcement. Unexpectedly, PS+ plants displayed wild-type levels of jasmonic acid (JA) but elevated accumulation of 12-oxo-phytodienoic acid (OPDA), suggesting that PS+ should not be used as an over-accumulator of JA in experimental setups.

CONCLUSIONS

A simple method, requiring notably little sample manipulation to quantify the peptide SYS, is described. Previous studies were based on genetic changes. In our study, SYS accumulated at extremely low levels in wild-type tomato leaves, showed slightly higher levels in the PROSYSTEMIN-overexpressing plants and was absent in the silenced lines. These small changes have a significant impact on plant metabolism. SA and OPDA, but not JA, were higher in the PROSYS-overexpressing plants.

Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis

BACKGROUND

Abiotic stresses are the major limiting factors that affect plant growth, development, yield and final quality. Deciphering the underlying mechanisms of plants' adaptations to stresses using few datasets might overlook the different aspects of stress tolerance in plants, which might be simultaneously and consequently operated in the system. Fortunately, the accumulated microarray expression data offer an opportunity to infer abiotic stress-specific gene expression patterns through meta-analysis. In this study, we propose to combine microarray gene expression data under control, cold, drought, heat, and salt conditions and determined modules (gene sets) of genes highly associated with each other according to the observed expression data.

RESULTS

By analyzing the expression variations of the Eigen genes from different conditions, we had identified two, three, and five gene modules as cold-, heat-, and salt-specific modules, respectively. Most of the cold- or heat-specific modules were differentially expressed to a particular degree in shoot samples, while most of the salt-specific modules were differentially expressed to a particular degree in root samples. A gene ontology (GO) analysis on the stress-specific modules suggested that the gene modules exclusively enriched stress-related GO terms and that different genes under the same GO terms may be alternatively disturbed in different conditions. The gene regulatory events for two genes, DREB1A and DEAR1, in the cold-specific gene module had also been validated, as evidenced through the literature search.

CONCLUSIONS

Our protocols study the specificity of the gene modules that were specifically activated under a particular type of abiotic stress. The biplot can also assist to visualize the stress-specific gene modules. In conclusion, our approach has the potential to further elucidate mechanisms in plants and beneficial for future experiments design under different abiotic stresses.

Central metabolite and sterol profiling divides tobacco male gametophyte development and pollen tube growth into eight metabolic phases

While changes in the transcriptome and proteome of developing pollen have been investigated in tobacco and other species, the metabolic consequences remain rather unclear. Here, a broad range of metabolites was investigated in close succession of developmental stages. Thirteen stages of tobacco male gametophyte development were collected, ranging from tetrads to pollen tubes. Subsequently, the central metabolome and sterol composition were analyzed by GC-mass spectrometry (MS), monitoring 77 metabolites and 29 non-identified analytes. The overall results showed that development and tube growth could be divided into eight metabolic phases with the phase including mitosis I being most distinct. During maturation, compounds such as sucrose and proline accumulated. These were degraded after rehydration, while γ-aminobutyrate transiently increased, possibly deriving from proline breakdown. Sterol analysis revealed that tetrads harbor similar sterols as leaves, but throughout maturation unusual sterols increased. Lastly, two further sterols exclusively accumulated in pollen tubes. This study allows a deeper look into metabolic changes during the development of a quasi-single cell type. Metabolites accumulating during maturation might accelerate pollen germination and tube growth, protect from desiccation, and feed pollinators. Future studies of the underlying processes orchestrating the changes in metabolite levels might give valuable insights into cellular regulation of plant metabolism.

Divergent co-transcriptomes of different host cells infected with Toxoplasma gondii reveal cell type-specific host-parasite interactions

The apicomplexan parasite Toxoplasma gondii infects various cell types in avian and mammalian hosts including humans. Infection of immunocompetent hosts is mostly asymptomatic or benign, but leads to development of largely dormant bradyzoites that persist predominantly within neurons and muscle cells. Here we have analyzed the impact of the host cell type on the co-transcriptomes of host and parasite using high-throughput RNA sequencing. Murine cortical neurons and astrocytes, skeletal muscle cells (SkMCs) and fibroblasts differed by more than 16,200 differentially expressed genes (DEGs) before and after infection with T. gondii. However, only a few hundred of them were regulated by infection and these largely diverged in neurons, SkMCs, astrocytes and fibroblasts indicating host cell type-specific transcriptional responses after infection. The heterogeneous transcriptomes of host cells before and during infection coincided with ~5,400 DEGs in T. gondii residing in different cell types. Finally, we identified gene clusters in both T. gondii and its host, which correlated with the predominant parasite persistence in neurons or SkMCs as compared to astrocytes or fibroblasts. Thus, heterogeneous expression profiles of different host cell types and the parasites’ ability to adapting to them may govern the parasite-host cell interaction during toxoplasmosis.

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics

The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification. There is a wide range of available software that not only aids in this but also in the related area of peak alignment; however, for the uninitiated, choosing which program to use is a daunting task. For this reason, we provide an overview of the pros and cons of the software as well as comments regarding the level of programing skills required to effectively exploit their basic functions. In addition, the torrent of available genome and transcriptome sequences that followed the advent of next-generation sequencing has opened up further valuable resources for metabolite identification. All things considered, we posit that only via a continued communal sharing of information such as that deposited in the databases described within the article are we likely to be able to make significant headway toward improving our coverage of the plant metabolome.

Integrated omics analysis of specialized metabolism in medicinal plants

Medicinal plants are a rich source of highly diverse specialized metabolites with important pharmacological properties. Until recently, plant biologists were limited in their ability to explore the biosynthetic pathways of these metabolites, mainly due to the scarcity of plant genomics resources. However, recent advances in high-throughput large-scale analytical methods have enabled plant biologists to discover biosynthetic pathways for important plant-based medicinal metabolites. The reduced cost of generating omics datasets and the development of computational tools for their analysis and integration have led to the elucidation of biosynthetic pathways of several bioactive metabolites of plant origin. These discoveries have inspired synthetic biology approaches to develop microbial systems to produce bioactive metabolites originating from plants, an alternative sustainable source of medicinally important chemicals. Since the demand for medicinal compounds are increasing with the world's population, understanding the complete biosynthesis of specialized metabolites becomes important to identify or develop reliable sources in the future. Here, we review the contributions of major omics approaches and their integration to our understanding of the biosynthetic pathways of bioactive metabolites. We briefly discuss different approaches for integrating omics datasets to extract biologically relevant knowledge and the application of omics datasets in the construction and reconstruction of metabolic models.

Green light for lipid fingerprinting

The use of targeted lipidomic approaches for the analysis of plant lipids has steadily increased during recent years. We review recent developments of these methods and suggest the introduction of discovery lipidomics as additional approach through a new workflow, lipid fingerprinting, that integrates the advantages of shotgun lipidomics (quantitative data) with LC-MS-based strategies (higher resolution and/or coverage). This article is part of a Special Issue entitled:BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

Integrated analysis of rice transcriptomic and metabolomic responses to elevated night temperatures identifies sensitivity- and tolerance-related profiles

Transcript and metabolite profiling were performed on leaves from six rice cultivars under high night temperature (HNT) condition. Six genes were identified as central for HNT response encoding proteins involved in transcription regulation, signal transduction, protein-protein interactions, jasmonate response and the biosynthesis of secondary metabolites. Sensitive cultivars showed specific changes in transcript abundance including abiotic stress responses, changes of cell wall-related genes, of ABA signaling and secondary metabolism. Additionally, metabolite profiles revealed a highly activated TCA cycle under HNT and concomitantly increased levels in pathways branching off that could be corroborated by enzyme activity measurements. Integrated data analysis using clustering based on one-dimensional self-organizing maps identified two profiles highly correlated with HNT sensitivity. The sensitivity profile included genes of the functional bins abiotic stress, hormone metabolism, cell wall, signaling, redox state, transcription factors, secondary metabolites and defence genes. In the tolerance profile, similar bins were affected with slight differences in hormone metabolism and transcription factor responses. Metabolites of the two profiles revealed involvement of GABA signaling, thus providing a link to the TCA cycle status in sensitive cultivars and of myo-inositol as precursor for inositol phosphates linking jasmonate signaling to the HNT response specifically in tolerant cultivars.

Computational Strategies for Biological Interpretation of Metabolomics Data

Biological interpretation of metabolomics data relies on two basic steps: metabolite identification and functional analysis. These two steps need to be applied in a coordinated manner to enable effective data understanding. The focus of this chapter is to introduce the main computational concepts and workflows during this process. After a general overview of the field, three sections will be presented: the first section will introduce the main computational methods and bioinformatics tools for metabolite identification using spectra from common analytical platforms; the second section will focus on introducing major bioinformatics approaches for functional enrichment analysis of metabolomics data; and the last section will discuss the three main workflows in current metabolomics studies, including the chemometrics approach, the metabolic profiling approach and the more recent chemo-enrichment analysis approach. The chapter ends with summary and future perspectives on computational metabolomics.

Eigenvector metabolite analysis reveals dietary effects on the association among metabolite correlation patterns, gene expression, and phenotypes

INTRODUCTION

'Multi-omics' datasets obtained from an organism of interest reared under different environmental treatments are increasingly common. Identifying the links among metabolites and transcripts can help to elucidate our understanding of the impact of environment at different levels within the organism. However, many methods for characterizing physiological connections cannot address unidentified metabolites.

OBJECTIVES

Here, we use Eigenvector Metabolite Analysis (EvMA) to examine links between metabolomic, transcriptomic, and phenotypic variation data and to assess the impact of environmental factors on these associations. Unlike other methods, EvMA can be used to analyze datasets that include unidentified metabolites and unannotated transcripts.

METHODS

To demonstrate the utility of EvMA, we analyzed metabolomic, transcriptomic, and phenotypic datasets produced from 20 Drosophila melanogaster genotypes reared on four dietary treatments. We used a hierarchical distance-based method to cluster the metabolites. The links between metabolite clusters, gene expression, and overt phenotypes were characterized using the eigenmetabolite (first principal component) of each cluster.

RESULTS

EvMA recovered chemically related groups of metabolites within the clusters. Using the eigenmetabolite, we identified genes and phenotypes that significantly correlated with each cluster. EvMA identifies new connections between the phenotypes, metabolites, and gene transcripts. Conclusion EvMA provides a simple method to identify correlations between metabolites, gene expression, and phenotypes, which can allow us to partition multivariate datasets into meaningful biological modules and identify under-studied metabolites and unannotated gene transcripts that may be central to important biological processes. This can be used to inform our understanding of the effect of environmental mechanisms underlying physiological states of interest.

The Nitrogen Availability Interferes with Mycorrhiza-Induced Resistance against Botrytis cinerea in Tomato

Mycorrhizal plants are generally quite efficient in coping with environmental challenges. It has been shown that the symbiosis with arbuscular mycorrhizal fungi (AMF) can confer resistance against root and foliar pathogens, although the molecular mechanisms underlying such mycorrhiza-induced resistance (MIR) are poorly understood. Tomato plants colonized with the AMF Rhizophagus irregularis display enhanced resistance against the necrotrophic foliar pathogen Botrytis cinerea. Leaves from arbuscular mycorrhizal (AM) plants develop smaller necrotic lesions, mirrored also by a reduced levels of fungal biomass. A plethora of metabolic changes takes place in AMF colonized plants upon infection. Certain changes located in the oxylipin pathway indicate that several intermediaries are over-accumulated in the AM upon infection. AM plants react by accumulating higher levels of the vitamins folic acid and riboflavin, indolic derivatives and phenolic compounds such as ferulic acid and chlorogenic acid. Transcriptional analysis support the key role played by the LOX pathway in the shoots associated with MIR against B. cinerea. Interestingly, plants that have suffered a short period of nitrogen starvation appear to react by reprogramming their metabolic and genetic responses by prioritizing abiotic stress tolerance. Consequently, plants subjected to a transient nitrogen depletion become more susceptible to B. cinerea. Under these experimental conditions, MIR is severely affected although still functional. Many metabolic and transcriptional responses which are accumulated or activated by MIR such NRT2 transcript induction and OPDA and most Trp and indolic derivatives accumulation during MIR were repressed or reduced when tomato plants were depleted of N for 48 h prior infection. These results highlight the beneficial roles of AMF in crop protection by promoting induced resistance not only under optimal nutritional conditions but also buffering the susceptibility triggered by transient N depletion.

Metabolome Analysis Reveals Betaine Lipids as Major Source for Triglyceride Formation, and the Accumulation of Sedoheptulose during Nitrogen-Starvation of Phaeodactylum tricornutum

Oleaginous microalgae are considered as a promising resource for the production of biofuels. Especially diatoms arouse interest as biofuel producers since they are most productive in carbon fixation and very flexible to environmental changes in the nature. Naturally, triacylglycerol (TAG) accumulation in algae only occurs under stress conditions like nitrogen-limitation. We focused on Phaeodactylum strain Pt4 (UTEX 646), because of its ability to grow in medium with low salinity and therefore being suited when saline water is less available or for wastewater cultivation strategies. Our data show an increase in neutral lipids during nitrogen-depletion and predominantly 16:0 and 16:1(n-7) accumulated in the TAG fraction. The molecular species composition of TAG suggests a remodeling primarily from the betaine lipid diacylglyceroltrimethylhomoserine (DGTS), but a contribution of the chloroplast galactolipid monogalactosyldiacylglycerol (MGDG) cannot be excluded. Interestingly, the acyl-CoA pool is rich in 20:5(n-3) and 22:6(n-3) in all analyzed conditions, but these fatty acids are almost excluded from TAG. Other metabolites most obviously depleted under nitrogen-starvation were amino acids, lyso-phospholipids and tricarboxylic acid (TCA) cycle intermediates, whereas sulfur-containing metabolites as dimethylsulfoniopropionate, dimethylsulfoniobutyrate and methylsulfate as well as short acyl chain carnitines, propanoyl-carnitine and butanoyl-carnitine increased upon nitrogen-starvation. Moreover, the Calvin cycle may be de-regulated since sedoheptulose accumulated after nitrogen-depletion. Together the data provide now the basis for new strategies to improve lipid production and storage in Phaeodactylum strain Pt4.

Characterization of a Pipecolic Acid Biosynthesis Pathway Required for Systemic Acquired Resistance

Systemic acquired resistance (SAR) is an immune response induced in the distal parts of plants following defense activation in local tissue. Pipecolic acid (Pip) accumulation orchestrates SAR and local resistance responses. Here, we report the identification and characterization of SAR-DEFICIENT4 (SARD4), which encodes a critical enzyme for Pip biosynthesis in Arabidopsis thaliana Loss of function of SARD4 leads to reduced Pip levels and accumulation of a Pip precursor, Δ¹-piperideine-2-carboxylic acid (P2C). In Escherichia coli, expression of the aminotransferase ALD1 leads to production of P2C and addition of SARD4 results in Pip production, suggesting that a Pip biosynthesis pathway can be reconstituted in bacteria by coexpression of ALD1 and SARD4. In vitro experiments showed that ALD1 can use l-lysine as a substrate to produce P2C and P2C is converted to Pip by SARD4. Analysis of sard4 mutant plants showed that SARD4 is required for SAR as well as enhanced pathogen resistance conditioned by overexpression of the SAR regulator FLAVIN-DEPENDENT MONOOXYGENASE1. Compared with the wild type, pathogen-induced Pip accumulation is only modestly reduced in the local tissue of sard4 mutant plants, but it is below detection in distal leaves, suggesting that Pip is synthesized in systemic tissue by SARD4-mediated reduction of P2C and biosynthesis of Pip in systemic tissue contributes to SAR establishment.

Functional Characterization of CYP94-Genes and Identification of a Novel Jasmonate Catabolite in Flowers

Over the past decades much research focused on the biosynthesis of the plant hormone jasmonyl-isoleucine (JA-Ile). While many details about its biosynthetic pathway as well about its physiological function are established nowadays, knowledge about its catabolic fate is still scarce. Only recently, the hormonal inactivation mechanisms became a stronger research focus. Two major pathways have been proposed to inactivate JA-Ile: i) The cleavage of the jasmonyl-residue from the isoleucine moiety, a reaction that is catalyzed by specific amido-hydrolases, or ii), the sequential oxidation of the ω-end of the pentenyl side-chain. This reaction is catalyzed by specific members of the cytochrome P450 (CYP) subfamily CYP94: CYP94B1, CYP94B3 and CYP94C1. In the present study, we further investigated the oxidative fate of JA-Ile by expanding the analysis on Arabidopsis thaliana mutants, lacking only one (cyp94b1, cyp94b2, cyp94b3, cyp94c1), two (cyp94b1xcyp94b2, cyp94b1xcyp94b3, cyp94b2xcyp94b3), three (cyp94b1xcyp94b2xcyp94b3) or even four (cyp94b1xcyp94b2xcyp94b3xcyp94c1) CYP94 functionalities. The results obtained in the present study show that CYP94B1, CYP94B2, CYP94B3 and CYP94C1 are responsible for catalyzing the sequential ω-oxidation of JA-Ile in a semi-redundant manner. While CYP94B-enzymes preferentially hydroxylate JA-Ile to 12-hydroxy-JA-Ile, CYP94C1 catalyzes primarily the subsequent oxidation, yielding 12-carboxy-JA-Ile. In addition, data obtained from investigating the triple and quadruple mutants let us hypothesize that a direct oxidation of unconjugated JA to 12-hydroxy-JA is possible in planta. Using a non-targeted metabolite fingerprinting analysis, we identified unconjugated 12-carboxy-JA as novel jasmonate derivative in floral tissues. Using the same approach, we could show that deletion of CYP94-genes might not only affect JA-homeostasis but also other signaling pathways. Deletion of CYP94B1, for example, led to accumulation of metabolites that may be characteristic for plant stress responses like systemic acquired resistance. Evaluation of the in vivo function of the different CYP94-enzymes on the JA-sensitivity demonstrated that particularly CYP94B-enzymes might play an essential role for JA-response, whereas CYP94C1 might only be of minor importance.

Non-targeted metabolomics by high resolution mass spectrometry in HPRT knockout mice

AIMS

Lesch-Nyhan disease (LND) is characterized by hyperuricemia as well as neurological and neuropsychiatric symptoms including repetitive self-injurious behavior. Symptoms are caused by a deficiency of the enzyme hypoxanthine-guanine phosphoribosyltransferase (HPRT) as a result of a mutation on the X chromosome. To elucidate the pathophysiology of LND, we performed a metabolite screening for brain and serum extracts from HPRT knockout mice as an animal model for LND.

MAIN METHODS

Analyses were performed by high performance liquid chromatography (HPLC)-coupled quadrupole time-of-flight mass spectrometry (QTOF-MS).

KEY FINDINGS

In brain extracts, we found six metabolites with significantly different contents in wild-type and HPRT-deficient mice. Two compounds we could identify as 5-aminoimidazole-4-carboxamide ribotide (AICAR) and 1-methylimidazole-4-acetic acid (1-MI4AA). Whereas AICAR was accumulated in brains of HPRT knockout mice, 1-MI4AA was decreased in these mice.

SIGNIFICANCE

Both metabolites play a role in histidine metabolism and, as a consequence, histamine metabolism. AICAR, in addition, is part of the purine metabolism. Our findings may help to better understand the mechanisms leading to the behavioral phenotype of LND.

A previously undescribed jasmonate compound in flowering Arabidopsis thaliana - The identification of cis-(+)-OPDA-Ile

Jasmonates (JAs) are plant hormones that integrate external stress stimuli with physiological responses. (+)-7-iso-JA-L-Ile is the natural JA ligand of COI1, a component of a known JA receptor. The upstream JA biosynthetic precursor cis-(+)-12-oxo-phytodienoic acid (cis-(+)-OPDA) has been reported to act independently of COI1 as an essential signal in several stress-induced and developmental processes. Wound-induced increases in the endogenous levels of JA/JA-Ile are accompanied by two to tenfold increases in the concentration of OPDA, but its means of perception and metabolism are unknown. To screen for putative OPDA metabolites, vegetative tissues of flowering Arabidopsis thaliana were extracted with 25% aqueous methanol (v/v), purified by single-step reversed-phase polymer-based solid-phase extraction, and analyzed by high throughput mass spectrometry. This enabled the detection and quantitation of a low abundant OPDA analog of the biologically active (+)-7-iso-JA-L-Ile in plant tissue samples. Levels of the newly identified compound and the related phytohormones JA, JA-Ile and cis-(+)-OPDA were monitored in wounded leaves of flowering Arabidopsis lines (Col-0 and Ws) and compared to the levels observed in Arabidopsis mutants deficient in the biosynthesis of JA (dde2-2, opr3) and JA-Ile (jar1). The observed cis-(+)-OPDA-Ile levels varied widely, raising questions concerning its role in Arabidopsis stress responses.

Data Fusion in Metabolomics and Proteomics for Biomarker Discovery

Proteomics and metabolomics provide key insights into status and dynamics of biological systems. These molecular studies reveal the complex mechanisms involved in disease or aging processes. Invaluable information can be obtained using various analytical techniques such as nuclear magnetic resonance, liquid chromatography, or gas chromatography coupled to mass spectrometry. Each method has inherent advantages and drawbacks, but they are complementary in terms of biological information.The fusion of different measurements is a complex topic. We describe here a framework allowing combining multiple data sets, provided by different analytical platforms. For each platform, the relevant information is extracted in the first step. The obtained latent variables are then fused and further analyzed. The influence of the original variables is then calculated back and interpreted.

Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies

Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided.