Data-Driven Characterization of Metabolome Reprogramming during Early Development of Sorghum Seedlings

Specialized metabolites are produced via discrete metabolic pathways. These small molecules play significant roles in plant growth and development, as well as defense against environmental stresses. These include damping off or seedling blight at a post-emergence stage. Targeted metabolomics was followed to gain insights into metabolome changes characteristic of different developmental stages of sorghum seedlings. Metabolites were extracted from leaves at seven time points post-germination and analyzed using ultra-high performance liquid chromatography coupled to mass spectrometry. Multivariate statistical analysis combined with chemometric tools, such as principal component analysis, hierarchical clustering analysis, and orthogonal partial least squares-discriminant analysis, were applied for data exploration and to reduce data dimensionality as well as for the selection of potential discriminant biomarkers. Changes in metabolome patterns of the seedlings were analyzed in the early, middle, and late stages of growth (7, 14, and 29 days post-germination). The metabolite classes were amino acids, organic acids, lipids, cyanogenic glycosides, hormones, hydroxycinnamic acid derivatives, and flavonoids, with the latter representing the largest class of metabolites. In general, the metabolite content showed an increase with the progression of the plant growth stages. Most of the differential metabolites were derived from tryptophan and phenylalanine, which contribute to innate immune defenses as well as growth. Quantitative analysis identified a correlation of apigenin flavone derivatives with growth stage. Data-driven investigations of these metabolomes provided new insights into the developmental dynamics that occur in seedlings to limit post-germination mortality.

microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

Studying Plant Specialized Metabolites Using Computational Metabolomics Strategies

Plant specialized metabolites have diversified vastly over the course of plant evolution, and they are considered key players in complex interactions between plants and their environment. The chemical diversity of these metabolites has been widely explored and utilized in agriculture and crop enhancement, the food industry, and drug development, among other areas. However, the immensity of the plant metabolome can make its exploration challenging. Here we describe a protocol for exploring plant specialized metabolites that combines high-resolution mass spectrometry and computational metabolomics strategies, including molecular networking, identification of structural motifs, as well as prediction of chemical structures and metabolite classes.

An Integrated Molecular Networking and Docking Approach to Characterize the Metabolome of Helichrysum splendidum and Its Pharmaceutical Potentials

South Africa is rich in diverse medicinal plants, and it is reported to have over 35% of the global Helichrysum species, many of which are utilized in traditional medicine. Various phytochemical studies have offered valuable insights into the chemistry of Helichrysum plants, hinting at bioactive components that define the medicinal properties of the plant. However, there are still knowledge gaps regarding the size and diversity of the Helichrysum chemical space. As such, continuous efforts are needed to comprehensively characterize the phytochemistry of Helichrysum, which will subsequently contribute to the discovery and exploration of Helichrysum-derived natural products for drug discovery. Thus, reported herein is a computational metabolomics work to comprehensively characterize the metabolic landscape of the medicinal herb Helichrysum splendidum, which is less studied. Metabolites were methanol-extracted and analyzed on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) system. Spectral data were mined using molecular networking (MN) strategies. The results revealed that the metabolic map of H. splendidum is chemically diverse, with chemical superclasses that include organic polymers, benzenoids, lipid and lipid-like molecules, alkaloids, and derivatives, phenylpropanoids and polyketides. These results point to a vastly rich chemistry with potential bioactivities, and the latter was demonstrated through computationally assessing the binding of selected metabolites with CDK-2 and CCNB1 anti-cancer targets. Molecular docking results showed that flavonoids (luteolin, dihydroquercetin, and isorhamnetin) and terpenoids (tiliroside and silybin) interact strongly with the CDK-2 and CCNB1 targets. Thus, this work suggests that these flavonoid and terpenoid compounds from H. splendidum are potentially anti-cancer agents through their ability to interact with these proteins involved in cancer pathways and progression. As such, these actionable insights are a necessary step for further exploration and translational studies for H. splendidum-derived compounds for drug discovery.

Metabolomic Reconfiguration in Primed Barley (Hordeum vulgare) Plants in Response to Pyrenophora teres f. teres Infection

Necrotrophic fungi affect a wide range of plants and cause significant crop losses. For the activation of multi-layered innate immune defences, plants can be primed or pre-conditioned to rapidly and more efficiently counteract this pathogen. Untargeted and targeted metabolomics analyses were applied to elucidate the biochemical processes involved in the response of 3,5-dichloroanthranilic acid (3,5-DCAA) primed barley plants to Pyrenophora teres f. teres (Ptt). A susceptible barley cultivar ('Hessekwa') at the third leaf growth stage was treated with 3,5-DCAA 24 h prior to infection using a Ptt conidia suspension. The infection was monitored over 2, 4, and 6 days post-inoculation. For untargeted studies, ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-MS) was used to analyse methanolic plant extracts. Acquired data were processed to generate the data matrices utilised in chemometric modelling and multi-dimensional data mining. For targeted studies, selected metabolites from the amino acids, phenolic acids, and alkaloids classes were quantified using multiple reaction monitoring (MRM) mass spectrometry. 3,5-DCAA was effective as a priming agent in delaying the onset and intensity of symptoms but could not prevent the progression of the disease. Unsupervised learning methods revealed clear differences between the sample extracts from the control plants and the infected plants. Both orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and 'shared and unique structures' (SUS) plots allowed for the extraction of potential markers of the primed and naïve plant responses to Ptt. These include classes of organic acids, fatty acids, amino acids, phenolic acids, and derivatives and flavonoids. Among these, 5-oxo-proline and citric acid were notable as priming response-related metabolites. Metabolites from the tricarboxylic acid pathway were only discriminant in the primed plant infected with Ptt. Furthermore, the quantification of targeted metabolites revealed that hydroxycinnamic acids were significantly more prominent in the primed infected plants, especially at 2 d.p.i. Our research advances efforts to better understand regulated and reprogrammed metabolic responses that constitute defence priming in barley against Ptt.

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health.

Metabolite profiling of susceptible and resistant wheat (Triticum aestivum) cultivars responding to Puccinia striiformis f. sp. tritici infection

BACKGROUND

Puccinia striiformis f. sp. tritici (Pst) is an economically devasting disease that is prominent in cereal crops such as wheat (Triticum aestivum). The fungal pathogen can cause approximately 30-70% losses in crop productivity and yields. Pst has become difficult to manage due to its ease of transmission through wind dispersal over long distances, and intercontinental dispersal has been previously reported. The ease of transmission has resulted in further destruction because of new and more virulent strains infecting crops previously resistant to a different strain.

RESULTS

In this study, a liquid chromatography-mass spectrometry-based untargeted metabolomics approach, in combination with multivariate data analytical tools, was used to elucidate the mechanistic nature of the defence systems of a Pst-resistant and a susceptible wheat cultivar infected with P. striiformis. We also investigated the time-dependant metabolic reconfiguration of infected plants over a four-week period. The untargeted metabolomic analysis revealed a time-course metabolic reprogramming involving phenylpropanoids (majority flavonoids), amino acids, lipids, benzoic acids, TCA cycle intermediates and benzoxazinoids responding to Pst infection. Interestingly, the results do not show a linear course for the decrease and increase (up-/down-regulation) of said classes of metabolites, but rather the up- or down-regulation of specific metabolites in response to the pathogen infection. The resistant Koonap cultivar had an abundance of phenolic compounds such as rutin, isoorintin-7-O-glucoside and luteolin-6-C-hexoside-O-hexoside. These compounds showed a decrease over time in control Koonap plants compared to an increase in Pst-infected plants. These metabolites were down-regulated in the susceptible Gariep cultivar, which could serve as biomarkers for plant responses to biotic stress and resistance against Pst.

CONCLUSIONS

Overall, an LC-MS-based metabolomics approach allowed for the metabolic profiling and analysis of the impact of plant-pathogen interactions on the overall plant metabolome and provided a real-time snapshot of the differential significant metabolic perturbations occurring in wheat plants responding to the Pst pathogen. The Pst-resistant Koonap cultivar showed a rapid accumulation of defence metabolites in response to pathogen infection compared to the susceptible Gariep cultivar. These findings provide insight into the mechanistic biochemical nature of plant-microbe interactions and the prospects of metabolic engineering for improved plant tolerance and resistance to biotic stresses.

Metabolic Reprogramming of Barley in Response to Foliar Application of Dichlorinated Functional Analogues of Salicylic Acid as Priming Agents and Inducers of Plant Defence

Designing innovative biological crop protection strategies to stimulate natural plant immunity is motivated by the growing need for eco-friendly alternatives to conventional biocidal agrochemicals. Salicylic acid (SA) and analogues are known chemical inducers of priming plant immunity against environmental stresses. The aim of the study was to study the metabolic reprogramming in barley plants following an application of three proposed dichlorinated inducers of acquired resistance. 3,5-Dichloroanthranilic acid, 2,6-dichloropyridine-4-carboxylic acid, and 3,5-dichlorosalicylic acid were applied to barley at the third leaf stage of development and harvested at 12, 24, and 36 h post-treatment. Metabolites were extracted using methanol for untargeted metabolomics analyses. Samples were analysed by ultra-high performance liquid chromatography coupled to high-definition mass spectrometry (UHPLC-HDMS). Chemometric methods and bioinformatics tools were used to mine and interpret the generated data. Alterations in the levels of both primary and secondary metabolites were observed. The accumulation of barley-specific metabolites, hordatines, and precursors was observed from 24 h post-treatment. The phenylpropanoid pathway, a marker of induced resistance, was identified among the key mechanisms activated by the treatment with the three inducers. No salicylic acid or SA derivatives were annotated as signatory biomarkers; instead, jasmonic acid precursors and derivatives were found as discriminatory metabolites across treatments. The study highlights differences and similarities in the metabolomes of barley after treatment with the three inducers and points to the triggering chemical changes associated with defence and resistance. This report is the first of its kind, and the knowledge acquired provides deeper insight into the role of dichlorinated small molecules as inducers of plant immunity and can be used in metabolomics-guided plant improvement programmes.

Mass spectrometry DDA parameters and global coverage of the metabolome: Spectral molecular networks of momordica cardiospermoides plants

INTRODUCTION

Molecular networking (MN) has emerged as a key strategy to organize and annotate untargeted tandem mass spectrometry (MS/MS) data generated using either data independent- or dependent acquisition (DIA or DDA). The latter presents a time-efficient approach where full scan (MS¹) and MS² spectra are obtained with shorter cycle times. However, there are limitations related to DDA parameters, some of which are (i) intensity threshold and (ii) collision energy. The former determines ion prioritization for fragmentation, and the latter defines the fragmentation of selected ions. These DDA parameters inevitably determine the coverage and quality of spectral data, which would affect the outputs of MN methods.

OBJECTIVES

This study assessed the extent to which the quality of the tandem spectral data relates to MN topology and subsequent implications in the annotation of metabolites and chemical classification relative to the different DDA parameters employed.

METHODS

Herein, characterising the metabolome of Momordica cardiospermoides plants, we employ classical MN performance indicators to investigate the effects of collision energies and intensity thresholds on the topology of generated MN and propagated annotations.

RESULTS

We demonstrated that the lowest predefined intensity thresholds and collision energies result in comprehensive molecular networks. Comparatively, higher intensity thresholds and collision energies resulted in fewer MS² spectra acquisition, subsequently fewer nodes, and a limited exploration of the metabolome through MN.

CONCLUSION

Contributing to ongoing efforts and conversations on improving DDA strategies, this study proposes a framework in which multiple DDA parameters are utilized to increase the coverage of ions acquired and improve the global coverage of MN, propagated annotations, and the chemical classification performed.

Computational Metabolomics to Elucidate Molecular Signaling and Regulatory Mechanisms Associated with Biostimulant-Mediated Growth Promotion and Abiotic Stress Tolerance in Crop Plants

Biostimulants show potentials as sustainable strategies for improved crop development and stress resilience. However, the cellular and molecular mechanisms, in particular the signaling and regulatory events, governing the agronomically observed positive effects of biostimulants on plants remain enigmatic, thus hampering novel formulation and exploration of biostimulants. Metabolomics offers opportunities to elucidate metabolic and regulatory processes that define biostimulant-induced changes in the plant's biochemistry and physiology, thus contributing to decode the modes of action of biostimulants. Here, we describe an application of metabolomics to elucidate biostimulant effects on crop plants. Using the case study of a humic substance (HS)-based biostimulant applied on maize plants, under normal and nutrient-starved stress conditions, this chapter proposes key methodological guidance and considerations of computational metabolomics approach to investigate metabolic and regulatory reconfiguration and networks underlying biostimulant-induced physiological changes in plants. Computational metabolome mining tools, in the Global Natural Products Social Molecular Networking (GNPS) ecosystem, are highlighted as well as metabolic pathway and network analysis for biological interpretation of the data.

Metabolomic evaluation of PGPR defence priming in wheat (Triticum aestivum L.) cultivars infected with Puccinia striiformis f. sp. tritici (stripe rust)

Plant-microbe interactions are a phenomenal display of symbiotic/parasitic relationships between living organisms. Plant growth-promoting rhizobacteria (PGPR) are some of the most widely investigated plant-beneficial microbes due to their capabilities in stimulating plant growth and development and conferring protection to plants against biotic and abiotic stresses. As such, PGPR-mediated plant priming/induced systemic resistance (ISR) has become a hot topic among researchers, particularly with prospects of applications in sustainable agriculture. The current study applies untargeted ultra-high performance liquid chromatography-high-definition mass spectrometry (UHPLC-HDMS) to investigate PGPR-based metabolic reconfigurations in the metabolome of primed wheat plants against Puccinia striiformis f. sp. tricti (Pst). A seed bio-priming approach was adopted, where seeds were coated with two PGPR strains namely Bacillus subtilis and Paenibacillus alvei (T22) and grown under controlled conditions in a glasshouse. The plants were infected with Pst one-week post-germination, followed by weekly harvesting of leaf material. Subsequent metabolite extraction was carried out for analysis on a UHPLC-HDMS system for data acquisition. The data was chemometrically processed to reveal the underlying trends and data structures as well as potential signatory biomarkers for priming against Pst. Results showed notable metabolic reprogramming in primary and secondary metabolism, where the amino acid and organic acid content of primed-control, primed-challenged and non-primed-challenged plants were differentially reprogrammed. Similar trends were observed from the secondary metabolism, in which primed plants (particularly primed-challenged) showed an up-regulation of phenolic compounds (flavonoids, hydroxycinnamic acids-HCAs- and HCA amides) compared to the non-primed plants. The metabolomics-based semi-quantitative and qualitative assessment of the plant metabolomes revealed a time-dependent metabolic reprogramming in primed-challenged and primed-unchallenged plants, indicating the metabolic adaptations of the plants to stripe rust infection over time.

Providing metabolomics education and training: pedagogy and considerations

BACKGROUND

Metabolomics is a highly multidisciplinary and non-standardised research field. Metabolomics researchers must possess and apply extensive cross-disciplinary content knowledge, subjective experience-based judgement, and the associated diverse skill sets. Accordingly, appropriate educational and training initiatives are important in developing this knowledge and skills base in the metabolomics community. For these initiatives to be successful, they must consider both pedagogical best practice and metabolomics-specific contextual challenges.

AIM OF REVIEW

The aim of this review is to provide consolidated pedagogical guidance for educators and trainers in metabolomics educational and training programmes.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In this review, we discuss the principles of pedagogical best practice as they relate to metabolomics. We then discuss the challenges and considerations in developing and delivering education and training in metabolomics. Finally, we present examples from our own teaching practice to illustrate how pedagogical best practice can be integrated into metabolomics education and training programmes.

Bacillus for Plant Growth Promotion and Stress Resilience: What Have We Learned?

The rhizosphere is a thin film of soil that surrounds plant roots and the primary location of nutrient uptake, and is where important physiological, chemical, and biological activities are occurring. Many microbes invade the rhizosphere and have the capacity to promote plant growth and health. Bacillus spp. is the most prominent plant growth promoting rhizobacteria due to its ability to form long-lived, stress-tolerant spores. Bacillus-plant interactions are driven by chemical languages constructed by a wide spectrum of metabolites and lead to enhanced plant growth and defenses. Thus, this review is a synthesis and a critical assessment of the current literature on the application of Bacillus spp. in agriculture, highlighting gaps that remain to be explored to improve and expand on the Bacillus-based biostimulants. Furthermore, we suggest that omics sciences, with a focus on metabolomics, offer unique opportunities to illuminate the chemical intercommunications between Bacillus and plants, to elucidate biochemical and molecular details on modes of action of Bacillus-based formulations, to generate more actionable insights on cellular and molecular events that explain the Bacillus-induced growth promotion and stress resilience in plants.

Untargeted metabolite profiling to elucidate rhizosphere and leaf metabolome changes of wheat cultivars (Triticum aestivum L.) treated with the plant growth-promoting rhizobacteria Paenibacillus alvei (T22) and Bacillus subtilis

The rhizosphere is a highly complex and biochemically diverse environment that facilitates plant–microbe and microbe–microbe interactions, and this region is found between plant roots and the bulk soil. Several studies have reported plant root exudation and metabolite secretion by rhizosphere-inhabiting microbes, suggesting that these metabolites play a vital role in plant–microbe interactions. However, the biochemical constellation of the rhizosphere soil is yet to be fully elucidated and thus remains extremely elusive. In this regard, the effects of plant growth-promoting rhizobacteria (PGPR)–plant interactions on the rhizosphere chemistry and above ground tissues are not fully understood. The current study applies an untargeted metabolomics approach to profile the rhizosphere exo-metabolome of wheat cultivars generated from seed inoculated (bio-primed) with Paenibacillus (T22) and Bacillus subtilis strains and to elucidate the effects of PGPR treatment on the metabolism of above-ground tissues. Chemometrics and molecular networking tools were used to process, mine and interpret the acquired mass spectrometry (MS) data. Global metabolome profiling of the rhizosphere soil of PGPR-bio-primed plants revealed differential accumulation of compounds from several classes of metabolites including phenylpropanoids, organic acids, lipids, organoheterocyclic compounds, and benzenoids. Of these, some have been reported to function in plant–microbe interactions, chemotaxis, biocontrol, and plant growth promotion. Metabolic perturbations associated with the primary and secondary metabolism were observed from the profiled leaf tissue of PGPR-bio-primed plants, suggesting a distal metabolic reprograming induced by PGPR seed bio-priming. These observations gave insights into the hypothetical framework which suggests that PGPR seed bio-priming can induce metabolic changes in plants leading to induced systemic response for adaptation to biotic and abiotic stress. Thus, this study contributes knowledge to ongoing efforts to decipher the rhizosphere metabolome and mechanistic nature of biochemical plant–microbe interactions, which could lead to metabolome engineering strategies for improved plant growth, priming for defense and sustainable agriculture.

Hordatines and Associated Precursors Dominate Metabolite Profiles of Barley (Hordeum vulgare L.) Seedlings: A Metabolomics Study of Five Cultivars

In the process of enhancing crop potential, metabolomics offers a unique opportunity to biochemically describe plant metabolism and to elucidate metabolite profiles that govern specific phenotypic characteristics. In this study we report an untargeted metabolomic profiling of shoots and roots of barley seedlings performed to reveal the chemical makeup therein at an early growth stage. The study was conducted on five cultivars of barley: ‘Overture’, ‘Cristalia’, ‘Deveron’, ‘LE7′ and ‘Genie’. Seedlings were grown for 16 days post germination under identical controlled conditions, and methanolic extracts were analysed on an ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC–HRMS) system. In addition, an unsupervised pattern identification technique, principal component analysis (PCA), was performed to process the generated multidimensional data. Following annotation of specific metabolites, several classes were revealed, among which phenolic acids represented the largest group in extracts from both shoot and root tissues. Interestingly, hordatines, barley-specific metabolites, were not found in the root tissue. In addition, metabolomic profiling revealed metabolites potentially associated with the plants’ natural protection system against potential pathogens. The study sheds light on the chemical composition of barley at a young developmental stage and the information gathered could be useful in plant research and biomarker-based breeding programs.

Metabolomic Characterisation of Discriminatory Metabolites Involved in Halo Blight Disease in Oat Cultivars Caused by Pseudomonas syringae pv. coronafaciens

The metabolome is the underlying biochemical layer of the phenotype and offers a functional readout of the cellular mechanisms involved in a biological system. Since metabolites are considered end-products of regulatory processes at a cellular level, their levels are considered the definitive response of the biological system to genetic or environmental variations. The metabolome thus serves as a metabolic fingerprint of the biochemical events that occur in a biological system under specific conditions. In this study, an untargeted metabolomics approach was applied to elucidate biochemical processes implicated in oat plant responses to Pseudomonas syringae pv. coronafaciens (Ps-c) infection, and to identify signatory markers related to defence responses and disease resistance against halo blight. Metabolic changes in two oat cultivars (“Dunnart” and “SWK001”) responding to Ps-c, were examined at the three-leaf growth stage and metabolome changes monitored over a four-day post-inoculation period. Hydromethanolic extracts were analysed using an ultra-high-performance liquid chromatography (UHPLC) system coupled to a high-definition mass spectrometer (MS) analytical platform. The acquired multi-dimensional data were processed using multivariate statistical analysis and chemometric modelling. The validated chemometric models indicated time- and cultivar-related metabolic changes, defining the host response to the bacterial inoculation. Further multivariate analyses of the data were performed to profile differential signatory markers, putatively associated with the type of launched defence response. These included amino acids, phenolics, phenolic amides, fatty acids, flavonoids, alkaloids, terpenoids, lipids, saponins and plant hormones. Based on the results, metabolic alterations involved in oat defence responses to Ps-c were elucidated and key signatory metabolic markers defining the defence metabolome were identified. The study thus contributes toward a more holistic understanding of the oat metabolism under biotic stress.

Rhizosphere Tripartite Interactions and PGPR-Mediated Metabolic Reprogramming towards ISR and Plant Priming: A Metabolomics Review

Plant growth-promoting rhizobacteria (PGPR) are beneficial microorganisms colonising the rhizosphere. PGPR are involved in plant growth promotion and plant priming against biotic and abiotic stresses. Plant-microbe interactions occur through chemical communications in the rhizosphere and a tripartite interaction mechanism between plants, pathogenic microbes and plant-beneficial microbes has been defined. However, comprehensive information on the rhizosphere communications between plants and microbes, the tripartite interactions and the biochemical implications of these interactions on the plant metabolome is minimal and not yet widely available nor well understood. Furthermore, the mechanistic nature of PGPR effects on induced systemic resistance (ISR) and priming in plants at the molecular and metabolic levels is yet to be fully elucidated. As such, research investigating chemical communication in the rhizosphere is currently underway. Over the past decades, metabolomics approaches have been extensively used in describing the detailed metabolome of organisms and have allowed the understanding of metabolic reprogramming in plants due to tripartite interactions. Here, we review communication systems between plants and microorganisms in the rhizosphere that lead to plant growth stimulation and priming/induced resistance and the applications of metabolomics in understanding these complex tripartite interactions.

Metabolic Circuits in Sap Extracts Reflect the Effects of a Microbial Biostimulant on Maize Metabolism under Drought Conditions

The use of microbial biostimulants in the agricultural sector is increasingly gaining momentum and drawing scientific attention to decode the molecular interactions between the biostimulants and plants. Although these biostimulants have been shown to improve plant health and development, the underlying molecular phenomenology remains enigmatic. Thus, this study is a metabolomics work to unravel metabolic circuits in sap extracts from maize plants treated with a microbial biostimulant, under normal and drought conditions. The biostimulant, which was a consortium of different Bacilli strains, was applied at the planting stage, followed by drought stress application. The maize sap extracts were collected at 5 weeks after emergence, and the extracted metabolites were analyzed on liquid chromatography-mass spectrometry platforms. The acquired data were mined using chemometrics and bioinformatics tools. The results showed that under both well-watered and drought stress conditions, the application of the biostimulant led to differential changes in the profiles of amino acids, hormones, TCA intermediates, phenolics, steviol glycosides and oxylipins. These metabolic changes spanned several biological pathways and involved a high correlation of the biochemical as well as structural metabolic relationships that coordinate the maize metabolism. The hypothetical model, postulated from this study, describes metabolic events induced by the microbial biostimulant for growth promotion and enhanced defences. Such understanding of biostimulant-induced changes in maize sap pinpoints to the biochemistry and molecular mechanisms that govern the biostimulant-plant interactions, which contribute to ongoing efforts to generate actionable knowledge of the molecular and physiological mechanisms that define modes of action of biostimulants.

Comparative Metabolite Profiling of Wheat Cultivars (Triticum aestivum) Reveals Signatory Markers for Resistance and Susceptibility to Stripe Rust and Aluminium (Al3+) Toxicity

Plants continuously produce essential metabolites that regulate their growth and development. The enrichment of specific metabolites determines plant interactions with the immediate environment, and some metabolites become critical in defence responses against biotic and abiotic stresses. Here, an untargeted UHPLC-qTOF-MS approach was employed to profile metabolites of wheat cultivars resistant or susceptible to the pathogen Puccinia striiformis f. sp. tritici (Pst) and Aluminium (Al³⁺) toxicity. Multivariate statistical analysis (MVDA) tools, viz. principal component analysis (PCA) and hierarchical cluster analysis (HiCA) were used to qualify the correlation between the identified metabolites and the designated traits. A total of 100 metabolites were identified from primary and secondary metabolisms, including phenolic compounds, such as flavonoid glycosides and hydroxycinnamic acid (HCA) derivatives, fatty acids, amino acids, and organic acids. All metabolites were significantly variable among the five wheat cultivars. The Pst susceptible cultivars demonstrated elevated concentrations of HCAs compared to their resistant counterparts. In contrast, ‘Koonap’ displayed higher levels of flavonoid glycosides, which could point to its resistant phenotype to Pst and Al³⁺ toxicity. The data provides an insight into the metabolomic profiles and thus the genetic background of Pst- and Al³⁺-resistant and susceptible wheat varieties. This study demonstrates the prospects of applied metabolomics for chemotaxonomic classification, phenotyping, and potential use in plant breeding and crop improvement.

Mass Spectral Molecular Networking to Profile the Metabolome of Biostimulant Bacillus Strains

Beneficial soil microbes like plant growth-promoting rhizobacteria (PGPR) significantly contribute to plant growth and development through various mechanisms activated by plant-PGPR interactions. However, a complete understanding of the biochemistry of the PGPR and microbial intraspecific interactions within the consortia is still enigmatic. Such complexities constrain the design and use of PGPR formulations for sustainable agriculture. Therefore, we report the application of mass spectrometry (MS)-based untargeted metabolomics and molecular networking (MN) to interrogate and profile the intracellular chemical space of PGPR Bacillus strains: B. laterosporus, B. amyloliquefaciens, B. licheniformis 1001, and B. licheniformis M017 and their consortium. The results revealed differential and diverse chemistries in the four Bacillus strains when grown separately, and also differing from when grown as a consortium. MolNetEnhancer networks revealed 11 differential molecular families that are comprised of lipids and lipid-like molecules, benzenoids, nucleotide-like molecules, and organic acids and derivatives. Consortium and B. amyloliquefaciens metabolite profiles were characterized by the high abundance of surfactins, whereas B. licheniformis strains were characterized by the unique presence of lichenysins. Thus, this work, applying metabolome mining tools, maps the microbial chemical space of isolates and their consortium, thus providing valuable insights into molecular information of microbial systems. Such fundamental knowledge is essential for the innovative design and use of PGPR-based biostimulants.

Metabolomics assessment of vitamin D impact in Pam3CSK4 stimulation

Mycobacterium tuberculosis, a causative agent of tuberculosis, is amongst the leading causes of mycobacterial mortality worldwide. Although several studies have proposed the possible therapeutic role of vitamin D in antimycobacterial...

A Global Metabolic Map Defines the Effects of a Si-Based Biostimulant on Tomato Plants under Normal and Saline Conditions

The ongoing unpredictability of climate changes is exponentially exerting a negative impact on crop production, further aggravating detrimental abiotic stress effects. Several research studies have been focused on the genetic modification of crop plants to achieve more crop resilience against such stress factors; however, there has been a paradigm shift in modern agriculture focusing on more organic, eco-friendly and long-lasting systems to improve crop yield. As such, extensive research into the use of microbial and nonmicrobial biostimulants has been at the core of agricultural studies to improve crop growth and development, as well as to attain tolerance against several biotic and abiotic stresses. However, the molecular mechanisms underlying the biostimulant activity remain enigmatic. Thus, this study is a liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics approach to unravel the hypothetical biochemical framework underlying effects of a nonmicrobial biostimulant (a silicon-based formulation) on tomato plants (Solanum lycopersium) under salinity stress conditions. This metabolomics study postulates that Si-based biostimulants could alleviate salinity stress in tomato plants through modulation of the primary metabolism involving changes in the tricarboxylic acid cycle, fatty acid and numerous amino acid biosynthesis pathways, with further reprogramming of several secondary metabolism pathways such as the phenylpropanoid pathway, flavonoid biosynthesis pathways including flavone and flavanol biosynthesis. Thus, the postulated hypothetical framework, describing biostimulant-induced metabolic events in tomato plants, provides actionable knowledge necessary for industries and farmers to, confidently and innovatively, explore, design, and fully implement Si-based formulations and strategies into agronomic practices for sustainable agriculture and food production.

A Metabolomics Approach and Chemometric Tools for Differentiation of Barley Cultivars and Biomarker Discovery

One of the ultimate goals of plant breeding is the development of new crop cultivars capable of withstanding increasing environmental stresses, to sustain the constantly growing population and economic demands. Investigating the chemical composition of the above and underground tissues of cultivars is crucial for the understanding of common and specific traits thereof. Using an untargeted metabolomics approach together with appropriate chemometrics tools, the differential metabolite profiles of leaf and root extracts from five cultivars of barley (‘Erica’, ‘Elim’, ‘Hessekwa’, ‘S16’ and ‘Agulhas’) were explored and potential signatory biomarkers were revealed. The study was conducted on seedlings grown for 21 days under identical controlled conditions. An ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) was employed to analyse hydromethanolic leaf and root extracts of barley cultivars. Furthermore, unsupervised and supervised learning algorithms were applied to mine the generated data and to pinpoint cultivar-specific metabolites. Among all the classes of metabolites annotated, phenolic acids and derivatives formed the largest group and also represented the most discriminatory metabolites. In roots, saponarin, an important allelochemical differentially distributed across cultivars, was the only flavonoid annotated. The application of an untargeted metabolomics approach in phenotyping grain crops such as barley was demonstrated, and the metabolites responsible for differentiating between the selected cultivars were revealed. The study provides insights into the chemical architecture of barley, an agro-economically relevant cereal crop; and reiterates the importance of metabolomics tools in plant breeding practices for crop improvement.

Plant Responses to Abiotic Stresses and Rhizobacterial Biostimulants: Metabolomics and Epigenetics Perspectives

In response to abiotic stresses, plants mount comprehensive stress-specific responses which mediate signal transduction cascades, transcription of relevant responsive genes and the accumulation of numerous different stress-specific transcripts and metabolites, as well as coordinated stress-specific biochemical and physiological readjustments. These natural mechanisms employed by plants are however not always sufficient to ensure plant survival under abiotic stress conditions. Biostimulants such as plant growth-promoting rhizobacteria (PGPR) formulation are emerging as novel strategies for improving crop quality, yield and resilience against adverse environmental conditions. However, to successfully formulate these microbial-based biostimulants and design efficient application programs, the understanding of molecular and physiological mechanisms that govern biostimulant-plant interactions is imperatively required. Systems biology approaches, such as metabolomics, can unravel insights on the complex network of plant-PGPR interactions allowing for the identification of molecular targets responsible for improved growth and crop quality. Thus, this review highlights the current models on plant defence responses to abiotic stresses, from perception to the activation of cellular and molecular events. It further highlights the current knowledge on the application of microbial biostimulants and the use of epigenetics and metabolomics approaches to elucidate mechanisms of action of microbial biostimulants.

Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview

Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. The dawn of a new era characterized by the emergence of fourth industrial revolution (4IR) technologies has redefined the ideological boundaries of research and applications in plant sciences. Recent technological advances and machine learning (ML)-based computational tools and omics data analysis approaches are allowing scientists to derive comprehensive metabolic descriptions and models for the target plant species under specific conditions. Such accurate metabolic descriptions are imperatively essential for devising a roadmap for the next generation of crops that are resilient to environmental deterioration. By synthesizing the recent literature and collating data on metabolomics studies on plant responses to abiotic stresses, in the context of the 4IR era, we point out the opportunities and challenges offered by omics science, analytical intelligence, computational tools and big data analytics. Specifically, we highlight technological advancements in (plant) metabolomics workflows and the use of machine learning and computational tools to decipher the dynamics in the chemical space that define plant responses to abiotic stress conditions.

Metabolomics for Biomarker Discovery: Key Signatory Metabolic Profiles for the Identification and Discrimination of Oat Cultivars

The first step in crop introduction-or breeding programmes-requires cultivar identification and characterisation. Rapid identification methods would therefore greatly improve registration, breeding, seed, trade and inspection processes. Metabolomics has proven to be indispensable in interrogating cellular biochemistry and phenotyping. Furthermore, metabolic fingerprints are chemical maps that can provide detailed insights into the molecular composition of a biological system under consideration. Here, metabolomics was applied to unravel differential metabolic profiles of various oat (Avena sativa) cultivars (Magnifico, Dunnart, Pallinup, Overberg and SWK001) and to identify signatory biomarkers for cultivar identification. The respective cultivars were grown under controlled conditions up to the 3-week maturity stage, and leaves and roots were harvested for each cultivar. Metabolites were extracted using 80% methanol, and extracts were analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to a quadrupole time-of-flight (qTOF) high-definition mass spectrometer analytical platform. The generated data were processed and analysed using multivariate statistical methods. Principal component analysis (PCA) models were computed for both leaf and root data, with PCA score plots indicating cultivar-related clustering of the samples and pointing to underlying differential metabolic profiles of these cultivars. Further multivariate analyses were performed to profile differential signatory markers, which included carboxylic acids, amino acids, fatty acids, phenolic compounds (hydroxycinnamic and hydroxybenzoic acids, and associated derivatives) and flavonoids, among the respective cultivars. Based on the key signatory metabolic markers, the cultivars were successfully distinguished from one another in profiles derived from both leaves and roots. The study demonstrates that metabolomics can be used as a rapid phenotyping tool for cultivar differentiation.

A Metabolomic Landscape of Maize Plants Treated With a Microbial Biostimulant Under Well-Watered and Drought Conditions

Microbial plant biostimulants have been successfully applied to improve plant growth, stress resilience and productivity. However, the mechanisms of action of biostimulants are still enigmatic, which is the main bottleneck for the fully realization and implementation of biostimulants into the agricultural industry. Here, we report the elucidation of a global metabolic landscape of maize (Zea mays L) leaves in response to a microbial biostimulant, under well-watered and drought conditions. The study reveals that the increased pool of tricarboxylic acid (TCA) intermediates, alterations in amino acid levels and differential changes in phenolics and lipids are key metabolic signatures induced by the application of the microbial-based biostimulant. These reconfigurations of metabolism gravitate toward growth-promotion and defense preconditioning of the plant. Furthermore, the application of microbial biostimulant conferred enhanced drought resilience to maize plants via altering key metabolic pathways involved in drought resistance mechanisms such as the redox homeostasis, strengthening of the plant cell wall, osmoregulation, energy production and membrane remodeling. For the first time, we show key molecular events, metabolic reprogramming, activated by a microbial biostimulant for plant growth promotion and defense priming. Thus, these elucidated metabolomic insights contribute to ongoing efforts in decoding modes of action of biostimulants and generating fundamental scientific knowledgebase that is necessary for the development of the plant biostimulants industry, for sustainable food security.

Lipopolysaccharides trigger synthesis of the allelochemical sorgoleone in cell cultures of Sorghum bicolor

The use of plant cell suspension culture systems has demonstrated to be highly suitable for metabolomics investigations of inducible defense responses. Here we report on sorghum cell suspension cultures that were elicited with purified lipopolysaccharides from the sorghum pathogen Burkholderia andropogonis, to activate metabolic pathways involved in the chemical defenses of the plant. Metabolomic analysis using liquid chromatography coupled to mass spectrometry identified a resorcinol phenolic lipid, annotated as sorgoleone, as one of the biomarkers associated with the LPS-induced response. Sorgoleone is a semiochemical and an allelochemical, synthesized by specialized root hair cells and the major component of the hydrophobic root exudate of sorghum. Its detection in undifferentiated cells might indicate a previously undescribed role for this phytochemical in plant defense responses.

Reproducible molecular networking of untargeted mass spectrometry data using GNPS

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.

Adaptive defence-related changes in the metabolome of Sorghum bicolor cells in response to lipopolysaccharides of the pathogen Burkholderia andropogonis

Plant cell suspension culture systems are valuable for the study of complex biological systems such as inducible defence responses and aspects of plant innate immunity. Perturbations to the cellular metabolome can be investigated using metabolomic approaches in order to reveal the underlying metabolic mechanism of cellular responses. Lipopolysaccharides from the sorghum pathogen, Burkholderia andropogonis (LPSB.a.), were purified, chemically characterised and structurally elucidated. The lipid A moiety consists of tetra- and penta-acylated 1,4'-bis-phosphorylated disaccharide backbone decorated by aminoarabinose residues, while the O-polysaccharide chain consists of linear trisaccharide repeating units of [→2)-α-Rha3CMe-(1 → 3)-α-Rha-(1 → 3)-α-Rha-(1 → ]. The effect of LPSB.a. in triggering metabolic reprogramming in Sorghum bicolor cells were investigated using untargeted metabolomics with liquid chromatography coupled to mass spectrometry detection. Cells were treated with LPSB.a. and the metabolic changes monitored over a 30 h time period. Alterations in the levels of phytohormones (jasmonates, zeatins, traumatic-, azelaic- and abscisic acid), which marked the onset of defence responses and accumulation of defence-related metabolites, were observed. Phenylpropanoids and indole alkaloids as well as oxylipins that included di- and trihydroxyoctadecedienoic acids were identified as signatory biomarkers, with marked secretion into the extracellular milieu. The study demonstrated that sorghum cells recognise LPSB.a. as a 'microbe-associated molecular pattern', perturbing normal cellular homeostasis. The molecular features of the altered metabolome were associated with phytohormone-responsive metabolomic reconfiguration of primary and secondary metabolites originating from various metabolic pathways, in support of defence and immunity.

Rhizobacteria-induced systemic tolerance against drought stress in Sorghum bicolor (L.) Moench

Induction of systemic tolerance in sorghum [Sorghum bicolor (L.) Moench] against drought stress was studied by screening a large collection of rhizobacterial isolates for their potential to exhibit this essential plant growth-promoting trait. This was done by means of a greenhouse assay that measured the relative change in both plant height and -biomass (roots and shoots) between rhizobacteria-primed versus non-primed (naïve) plants under drought stress conditions. In order to elucidate the metabolomic changes in S. bicolor that conferred the drought stress tolerance after treatment (priming) with selected isolates, untargeted ultra-high performance liquid chromatography-high definition mass spectrometry (UHPLC-HDMS)-based metabolomics was carried out. Intracellular metabolites were methanol-extracted from rhizobacteria-primed and naïve S. bicolor roots and shoots. Extracts were analysed on a UHPLC-HDMS system and the generated data were chemometrically mined to determine signatory metabolic profiles and bio-markers related to induced systemic tolerance. The metabolomic results showed significant treatment-related differential metabolic reprogramming between rhizobacteria-primed and naïve plants, correlating to the ability of the selected isolates to protect S. bicolor against drought stress. The selected isolates, identified by means of 16S rRNA gene sequencing as members of the genera Bacillus and Pseudomonas, were screened for 1-aminocyclopropane-1-carboxylate (ACC) deaminase activity by means of an in vitro assay and the presence of the acdS gene was subsequently confirmed by PCR for strain N66 (Pseudomonas sp.). The underlying key metabolic changes in the enhanced drought stress tolerance observed in rhizobacteria-primed S. bicolor plants included (1) augmented antioxidant capacity; (2) growth promotion and root architecture modification as a result of the upregulation of the hormones gibberellic acid, indole acetic acid and cytokinin; (3) the early activation of induce systemic tolerance through the signalling hormones brassinolides, salicylic acid and jasmonic acid and signalling molecules sphingosine and psychosine; (4) the production of the osmolytes proline, glutamic acid and choline; (5) the production of the epicuticular wax docosanoic acid and (6) ACC deaminase activity resulting in lowered ethylene levels. These results unravelled key molecular details underlying the PGPR-induced systemic tolerance in sorghum plants, providing insights for the plant priming for abiotic stress.

Rhizobacteria-induced systemic tolerance against drought stress in Sorghum bicolor (L.) Moench

Induction of systemic tolerance in sorghum [Sorghum bicolor (L.) Moench] against drought stress was studied by screening a large collection of rhizobacterial isolates for their potential to exhibit this essential plant growth-promoting trait. This was done by means of a greenhouse assay that measured the relative change in both plant height and -biomass (roots and shoots) between rhizobacteria-primed versus non-primed (naïve) plants under drought stress conditions. In order to elucidate the metabolomic changes in S. bicolor that conferred the drought stress tolerance after treatment (priming) with selected isolates, untargeted ultra-high performance liquid chromatography-high definition mass spectrometry (UHPLC-HDMS)-based metabolomics was carried out. Intracellular metabolites were methanol-extracted from rhizobacteria-primed and naïve S. bicolor roots and shoots. Extracts were analysed on a UHPLC-HDMS system and the generated data were chemometrically mined to determine signatory metabolic profiles and bio-markers related to induced systemic tolerance. The metabolomic results showed significant treatment-related differential metabolic reprogramming between rhizobacteria-primed and naïve plants, correlating to the ability of the selected isolates to protect S. bicolor against drought stress. The selected isolates, identified by means of 16S rRNA gene sequencing as members of the genera Bacillus and Pseudomonas, were screened for 1-aminocyclopropane-1-carboxylate (ACC) deaminase activity by means of an in vitro assay and the presence of the acdS gene was subsequently confirmed by PCR for strain N66 (Pseudomonas sp.). The underlying key metabolic changes in the enhanced drought stress tolerance observed in rhizobacteria-primed S. bicolor plants included (1) augmented antioxidant capacity; (2) growth promotion and root architecture modification as a result of the upregulation of the hormones gibberellic acid, indole acetic acid and cytokinin; (3) the early activation of induce systemic tolerance through the signalling hormones brassinolides, salicylic acid and jasmonic acid and signalling molecules sphingosine and psychosine; (4) the production of the osmolytes proline, glutamic acid and choline; (5) the production of the epicuticular wax docosanoic acid and (6) ACC deaminase activity resulting in lowered ethylene levels. These results unravelled key molecular details underlying the PGPR-induced systemic tolerance in sorghum plants, providing insights for the plant priming for abiotic stress.

Multi-platform metabonomics unravel amino acids as markers of HIV/combination antiretroviral therapy-induced oxidative stress

Infection by the human immunodeficiency virus (HIV) elicits an immune response wherein neutrophils produce reactive oxygen species (ROS) to defend against pathogen invasion. Consequently, disproportionate levels of ROS in relation to antioxidants lead to oxidative stress (OS), which plays a key role in HIV disease progression and pathogenesis. There is a close relationship between oxidative stress status and HIV infection/progression, both separately and in the presence of combination antiretroviral therapy (cART). Biomarkers of oxidative stress present an additional means of monitoring HIV disease progression and/or management. Thus, the objective of this study was to apply untargeted nuclear magnetic resonance (NMR)-based metabonomics followed by targeted quantitative gas chromatography-mass spectrometry (GC/MS) analyses to identify predictors of oxidative stress in HIV infected individuals, with or without cART. Untargeted NMR-based metabonomics allowed a global profiling of metabolic perturbations in HIV-infected sera. The cohort consisted of 21 HIV-negative control subjects (HIV^-) and 113 HIV-infected individuals, of which 100 were on cART. Significant differences in metabolic features corresponding to changes in glucose, lipids, phenylalanine, glutamic acid, aspartic acid and branched amino acids were observed, which point to oxidative stress and insulin resistance. To further confirm oxidative stress, targeted GC/MS-based metabonomics, performed in succession, allowed for a quantitative description of a total of 9 oxidative stress-related metabolites. Significant up-regulation of aspartic acid, phenylalanine and glutamic acid were observed in the HIV-infected cohorts as compared to controls. Tryptophan and tyrosine were down-regulated whereas cystine levels were increased in HIV-infected and untreated individuals as compared to both HIV treated and negative control subjects. Pathway analysis also revealed 11 metabolic pathways to be significantly altered by infection and/or treatment. These pathways included aminoacyl-tRNA biosynthesis, nitrogen metabolism and phenylalanine, tyrosine and tryptophan biosynthesis. This pilot study demonstrated the use of multiplatform metabonomic strategies to elucidate metabolic markers that would be essential in predicting HIV/cART-induced oxidative stress. This could aid and contribute in HIV treatment and management programmes.

Differential Metabolic Reprogramming in Paenibacillus alvei-Primed Sorghum bicolor Seedlings in Response to Fusarium pseudograminearum Infection

Metabolic changes in sorghum seedlings in response to Paenibacillus alvei (NAS-6G6)-induced systemic resistance against Fusarium pseudograminearum crown rot were investigated by means of untargeted ultra-high performance liquid chromatography-high definition mass spectrometry (UHPLC-HDMS). Treatment of seedlings with the plant growth-promoting rhizobacterium P. alvei at a concentration of 1 × 108 colony forming units mL-1 prior to inoculation with F. pseudograminearum lowered crown rot disease severity significantly at the highest inoculum dose of 1 × 106 spores mL-1. Intracellular metabolites were subsequently methanol-extracted from treated and untreated sorghum roots, stems and leaves at 1, 4 and 7 days post inoculation (d.p.i.) with F. pseudograminearum. The extracts were analysed on an UHPLC-HDMS platform, and the data chemometrically processed to determine metabolic profiles and signatures related to priming and induced resistance. Significant treatment-related differences in primary and secondary metabolism post inoculation with F. pseudograminearum were observed between P. alvei-primed versus naïve S. bicolor seedlings. The differential metabolic reprogramming in primed plants comprised of a quicker and/or enhanced upregulation of amino acid-, phytohormone-, phenylpropanoid-, flavonoid- and lipid metabolites in response to inoculation with F. pseudograminearum.

The Metabolomics Society-Current State of the Membership and Future Directions

Background: In 2017, the Metabolomics Society conducted a survey among its members to assess the degree of its current success, define opportunities for improving its service to the community and make plans to establish future goals and direction of the Society. Methods: A 32-question online survey was sent via e-mail to all Metabolomics Society members as of 19 June 2017 (n = 644). In addition to the direct e-mails, the link to access the survey was made available through social media. The survey was open until 10 August 2017. Question-specific data were reported using the summary data generated by SurveyMonkey and additional stratified analyses performed using Stata 15. Results: The number of respondents was 394 (61%) with 348 (88%) completing the multiple-choice questions in survey. Metabolomics Society annual meetings, networking and the opportunity to join the global metabolomics community were among the most important benefits expressed by the Metabolomics Society members. Conclusions: The survey collected the first data focusing on membership issues from Society members. The Society should focus on collecting and monitoring of demographic data during the membership registration process; continuing to support the early-career members of the Society; and developing initiatives that focus on member networking to retain and increase Society membership.

Deciphering the Resistance Mechanism of Tomato Plants Against Whitefly-Mediated Tomato Curly Stunt Virus Infection through Ultra-High-Performance Liquid Chromatography Coupled to Mass Spectrometry (UHPLC-MS)-Based Metabolomics Approaches

Begomoviruses, such as the Tomato curly stunt virus (ToCSV), pose serious economic consequences due to severe crop losses. Therefore, the development and screening of possible resistance markers is imperative. While some tomato cultivars exhibit differential resistance to different begomovirus species, in most cases, the mechanism of resistance is not fully understood. In this study, the response of two near-isogenic lines of tomato (Solanum lycopersicum), differing in resistance against whitefly-mediated ToCSV infection were investigated using untargeted ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS)-based metabolomics. The responses of the two lines were deciphered using multivariate statistics models. Principal component analysis (PCA) scores plots from various time intervals revealed that the resistant line responded more rapidly with changes to the metabolome than the susceptible counterpart. Moreover, the metabolic reprogramming of chemically diverse metabolites that span a range of metabolic pathways was associated with the defence response. Biomarkers primarily included hydroxycinnamic acids conjugated to quinic acid, galactaric acid, and glucose. Minor constituents included benzenoids, flavonoids, and steroidal glycoalkaloids. Interestingly, when reduced to the level of metabolites, the phytochemistry of the infected plants' responses was very similar. However, the resistant phenotype was strongly associated with the hydroxycinnamic acid derivatives deployed in response to infection. In addition, the resistant line was able to mount a stronger and quicker response.

Differential metabolic signatures in naturally and lactic acid bacteria (LAB) fermented ting (a Southern African food) with different tannin content, as revealed by gas chromatography mass spectrometry (GC-MS)-based metabolomics

Fermented whole grain (WG) sorghum food products including WG-ting can be obtained from different sample sources and fermentation conditions, leading subsequently to variations in the molecular composition of the products. There is however, a lack of detailed understanding and description of differential molecular profiles of these food products. Thus, the current study is a nontargeted gas chromatography-mass spectrometry (GC-MS)-based metabolomics approach to descriptively elucidate metabolic profiles of two WG-sorghum types [high tannin (HT) and low tannin (LT)] and their derived WG-ting products obtained via fermentation. Metabolites were extracted with 80% aqueous methanol and analyzed on a gas chromatography high resolution time of flight mass spectrometry (GC-HRTOF-MS) system. Chemometric methods such as principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) were applied to mine the generated data. Our results showed that tannin contents influenced the composition of the raw sorghum and derived WG-ting samples. Metabolite signatures that differentiated raw HT- and LT-sorghum included cyclic compounds, pesticides, 2,4-di-tert-butylphenol, fatty acid esters, and sugar derivatives. Furthermore, fermentation of the HT- and LT-sorghum into WG-ting led to an increase in the levels of fatty acids, fatty acid esters and some other compounds which are vital from a dietary and health context. Equally observed were reduction of some phenols, cyclic compounds, a pesticide and ketone. Thus, the results demonstrated that the inherent metabolic composition of raw sorghum would lead to differential metabolic changes in the fermented products such as WG-ting, with subsequent dietary and health implications. Fermenting ting with Lactobacillus fermentum FUA 3321 was most desirable as relevant metabolites were observed in both HT- and LT-ting samples. Furthermore, the study highlights the applicability of GC-MS metabolomics in understanding WG-ting fermentation.

Time-resolved decoding of metabolic signatures of in vitro growth of the hemibiotrophic pathogen Colletotrichum sublineolum

Metabolomics has emerged as a powerful approach to comprehensively interrogate cellular biochemistry. As such, we applied an untargeted liquid chromatography-mass spectrometry metabolomic strategy to elucidate metabolome changes in the anthracnose-causing hemibiotrophic sorghum pathogen, Colletotrichum sublineolum. An in vitro batch culture study model with different carbon sources, glucose, arabinose and rhamnose, were used to support fungal growth over a period of twelve days. Metabolites representing the intracellular and extracellular (secreted) metabolomes were extracted with methanol and subjected to LC-MS analyses. Chemometric modelling revealed a metabolic variation trajectory, comprising three distinct stages that metabolically describe the adaptation of the fungus to diminishing nutrients. Selected marker gene expression indicated stage one (0-3 d.p.i) as corresponding to the early logarithmic phase. Stage two can be interpreted as an intermediate transitionary stage with stage three corresponding to the stationary phase (9-12 d.p.i). Stage one was characterised by up-regulation of endo-metabolites such as ferricrocin, fatty acids and flavone-conjugates, while stage three was characterised by the secretion of phytotoxins, including colletotrichin and colletotric acid. Ultimately, results from our in vitro model reveal previously unknown insights into the dynamic aspects of metabolome reprogramming in the growth phases of Colletotrichum spp as determined by nutrients obtainable from plant cell walls.

Untargeted Metabolomics Reveal Defensome-Related Metabolic Reprogramming in Sorghum bicolor against Infection by Burkholderia andropogonis

Burkholderia andropogonis is the causal agent of bacterial leaf stripe, one of the three major bacterial diseases affecting Sorghum bicolor. However, the biochemical aspects of the pathophysiological host responses are not well understood. An untargeted metabolomics approach was designed to understand molecular mechanisms underlying S. bicolor⁻B. andropogonis interactions. At the 4-leaf stage, two sorghum cultivars (NS 5511 and NS 5655) differing in disease tolerance, were infected with B. andropogonis and the metabolic changes monitored over time. The NS 5511 cultivar displayed delayed signs of wilting and lesion progression compared to the NS 5655 cultivar, indicative of enhanced resistance. The metabolomics results identified statistically significant metabolites as biomarkers associated with the sorghum defence. These include the phytohormones salicylic acid, jasmonic acid, and zeatin. Moreover, metabolic reprogramming in an array of chemically diverse metabolites that span a wide range of metabolic pathways was associated with the defence response. Signatory biomarkers included aromatic amino acids, shikimic acid, metabolites from the phenylpropanoid and flavonoid pathways, as well as fatty acids. Enhanced synthesis and accumulation of apigenin and derivatives thereof was a prominent feature of the altered metabolomes. The analyses revealed an intricate and dynamic network of the sorghum defence arsenal towards B. andropogonis in establishing an enhanced defensive capacity in support of resistance and disease suppression. The results pave the way for future analysis of the biosynthesis of signatory biomarkers and regulation of relevant metabolic pathways in sorghum.

Metabolomics in Plant Priming Research: The Way Forward?

A new era of plant biochemistry at the systems level is emerging, providing detailed descriptions of biochemical phenomena at the cellular and organismal level. This new era is marked by the advent of metabolomics—the qualitative and quantitative investigation of the entire metabolome (in a dynamic equilibrium) of a biological system. This field has developed as an indispensable methodological approach to study cellular biochemistry at a global level. For protection and survival in a constantly-changing environment, plants rely on a complex and multi-layered innate immune system. This involves surveillance of ‘self’ and ‘non-self,’ molecule-based systemic signalling and metabolic adaptations involving primary and secondary metabolites as well as epigenetic modulation mechanisms. Establishment of a pre-conditioned or primed state can sensitise or enhance aspects of innate immunity for faster and stronger responses. Comprehensive elucidation of the molecular and biochemical processes associated with the phenotypic defence state is vital for a better understanding of the molecular mechanisms that define the metabolism of plant–pathogen interactions. Such insights are essential for translational research and applications. Thus, this review highlights the prospects of metabolomics and addresses current challenges that hinder the realisation of the full potential of the field. Such limitations include partial coverage of the metabolome and maximising the value of metabolomics data (extraction of information and interpretation). Furthermore, the review points out key features that characterise both the plant innate immune system and enhancement of the latter, thus underlining insights from metabolomic studies in plant priming. Future perspectives in this inspiring area are included, with the aim of stimulating further studies leading to a better understanding of plant immunity at the metabolome level.

Mass spectrometry in untargeted liquid chromatography/mass spectrometry metabolomics: Electrospray ionisation parameters and global coverage of the metabolome

RATIONALE

Liquid chromatography coupled to mass spectrometry (LC/MS) is a dominant analytical platform in metabolomics, because of the high sensitivity and resolution, thus enabling large-scale coverage of metabolomes. Correspondingly, electrospray ionisation (ESI) is the favoured ionisation method in untargeted LC/MS metabolomics given the ability to produce large numbers of ions. In the workflow of LC/ESI-MS metabolomics, maximising the ionisation efficiency over a wide mass range is inevitably an essential and determining step, subsequently defining the extent of coverage of the metabolome under investigation. Thus in this study, electronic factors related to the functioning of the ESI source, namely the capillary and sample cone voltages, were explored to investigate the influence on the data acquired in metabolomic investigations.

METHODS

Hydromethanolic samples from an untargeted study (sorghum plants responding dynamically to fungal infection) were analysed on a high-resolution/definition LC/ESI-MS system. Here the capillary and sample cone voltages of the ZSpray™ ESI source were varied between 1.5-3.0 kV and 10.0-40.0 V, respectively. The acquired data were processed with MarkerLynx™ software and analysed using central composite design response surface methodology and chemometric approaches (principal component analysis and orthogonal projection latent structures-discriminant analysis).

RESULTS

The results evidently demonstrate that both capillary and sampling cone voltages not only significantly influence the recorded MS signals with regard to the number and abundance of features, but also the overall structure of the collected data. This consequently impacts on the information extracted from the data and thus affects coverage of the metabolome.

CONCLUSIONS

The observations postulate in that, untargeted LC/MS metabolomics, 'what you see is what you ionise'. Although there is convergence of collected data under different ESI conditions, the nuances observed indicate that the exploration of different ion source settings could be the best trade-off in expanding and maximising the metabolome coverage in untargeted metabolomic experiments.

Metabolomic Analysis of Defense-Related Reprogramming in Sorghum bicolor in Response to Colletotrichum sublineolum Infection Reveals a Functional Metabolic Web of Phenylpropanoid and Flavonoid Pathways

The metabolome of a biological system provides a functional readout of the cellular state, thus serving as direct signatures of biochemical events that define the dynamic equilibrium of metabolism and the correlated phenotype. Hence, to elucidate biochemical processes involved in sorghum responses to fungal infection, a liquid chromatography-mass spectrometry-based untargeted metabolomic study was designed. Metabolic alterations of three sorghum cultivars responding to Colletotrichum sublineolum, were investigated. At the 4-leaf growth stage, the plants were inoculated with fungal spore suspensions and the infection monitored over time: 0, 3, 5, 7, and 9 days post inoculation. Non-infected plants were used as negative controls. The metabolite composition of aqueous-methanol extracts were analyzed on an ultra-high performance liquid chromatography system coupled to high-definition mass spectrometry. The acquired multidimensional data were processed to create data matrices for multivariate statistical analysis and chemometric modeling. The computed chemometric models indicated time- and cultivar-related metabolic changes that reflect sorghum responses to the fungal infection. Metabolic pathway and correlation-based network analyses revealed that this multi-component defense response is characterized by a functional metabolic web, containing defense-related molecular cues to counterattack the pathogen invasion. Components of this network are metabolites from a range of interconnected metabolic pathways with the phenylpropanoid and flavonoid pathways being the central hub of the web. One of the key features of this altered metabolism was the accumulation of an array of phenolic compounds, particularly de novo biosynthesis of the antifungal 3-deoxyanthocynidin phytoalexins, apigeninidin, luteolinidin, and related conjugates. The metabolic results were complemented by qRT-PCR gene expression analyses that showed upregulation of defense-related marker genes. Unraveling key characteristics of the biochemical mechanism underlying sorghum-C. sublineolum interactions, provided valuable insights with potential applications in breeding crop plants with enhanced disease resistance. Furthermore, the study contributes to ongoing efforts toward a comprehensive understanding of the regulation and reprogramming of plant metabolism under biotic stress.

Methylation of the Vitamin D Receptor (VDR) Gene, Together with Genetic Variation, Race, and Environment Influence the Signaling Efficacy of the Toll-Like Receptor 2/1-VDR Pathway

BACKGROUND

The disparity in prevalence of infectious diseases across the globe is common knowledge. Vitamin D receptor (VDR)-mediated toll-like receptor (TLR) 2/1 signaling produces antimicrobial peptides, which is critical as a first line of defense in innate immunity. Numerous studies disclosed the independent role of genetic polymorphisms in this pathway, vitamin D status or season and more recently epigenetics, as factors contributing to infectious disease predisposition. Few studies address the interaction between environment, genetics, and epigenetics. Here, we hypothesized that VDR-mediated TLR2/1 signaling is influenced by a combination of environment, epigenetics and genetics, collectively influencing differential innate immunity.

METHODS

Healthy Black and White South Africans (n = 100) donated blood, while ultraviolet index (UVI) was recorded for the duration of the study. LC-MS/MS supported 25(OH)D₃ quantification. Monocyte/macrophage cultures, supplemented with/without 1,25(OH)₂D₃, were activated with the TLR2/1 elicitor, Pam₃CSK₄. VDR, cathelicidin antimicrobial peptide, hCAP-18, and 25-hydroxyvitamin D₃-24-hydroxylase expression were quantified by RT-qPCR or flow cytometry. Pyrosequencing facilitated VDR methylation analysis and single-nucleotide polymorphism (SNP) genotyping in regions pinpointed through a bioinformatics workflow.

RESULTS

Season interacted with race showing 25(OH)D₃ deficiency in Blacks. UVI correlated with 25(OH)D₃ and VDR methylation, likely influencing race differences in the latter. Regarding the TLR2/1 pathway, race differences in SNP genotype distribution were confirmed and functional analysis of VDR-mediated signaling showed interaction between race, season, and 25(OH)D₃ status. Multivariate OPLS-DA mirrored several interactions between UVI, 25(OH)D₃ status, DNA sequence, and methylation variants. Methylation of the third cytosine-phosphate-guanine dinucleotide (CpG) in the promoter CpG island (CGI) 1062, CGI 1062 CpG 3, significantly discriminated a 5.7-fold above average mean in VDR protein level upon TLR2/1 elicitation, the variation of which was further influenced by 25(OH)D₃ status and the VDR SNP TaqI.

CONCLUSION

Regulation of VDR-mediated TLR2/1 signaling is multifactorial, involving interaction between environment [UVI and consequent 25(OH)D₃ status], epigenetics (VDR methylation at key regulatory sites), and genetics (TLR1, TIRAP, and VDR SNPs).

Highlighting mass spectrometric fragmentation differences and similarities between hydroxycinnamoyl-quinic acids and hydroxycinnamoyl-isocitric acids

Background

Plants contain a myriad of metabolites which exhibit diverse biological activities. However, in-depth analyses of these natural products with current analytical platforms remains an undisputed challenge due to the multidimensional chemo-diversity of these molecules, amplified by both isomerization and conjugation. In this study, we looked at molecules such as hydroxyl-cinnamic acids (HCAs), which are known to exist as positional and geometrical isomers conjugated to different organic acids namely quinic- and isocitric acid.

Objective

The study aimed at providing a more defined distinction between HCA conjugates from Amaranthus viridis and Moringa oleifera, using mass spectrometry (MS) approaches.

Methods

Here, we used a UHPLC–MS/MS targeted approach to analyze isobaric HCA conjugates extracted from the aforementioned plants.

Results

Mass spectrometry results showed similar precursor ions and fragmentation pattern; however, distinct differences were seen with ions at m/z 155 and m/z 111 which are associated with isocitric acid conjugates.

Conclusion

Our results highlight subtle differences between these two classes of compounds based on the MS fingerprints, enabling confidence differentiation of the compounds. Thus, these findings provide a template reference for accurate and confident annotation of such compounds in other plants.

Electronic supplementary material

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Deciphering the influence of column chemistry and mass spectrometry settings for the analyses of geometrical isomers of L-chicoric acid

Resolving the chemo-diversity of plant extract samples is an essential step for in-depth analyses of natural products which often exhibit promising biological activities. One of the challenges in this endeavor has been the confident differentiation of geometrical isomers. In this study, we investigated these aspects in chromatography (column chemistry and mobile phase composition) and mass spectrometry settings with regards to better differentiation of geometrical isomers. A standard of a hydroxycinnamic acid (HCA) derivative, L-chicoric acid (L-CA) - a di-acylated caffeoyltartaric acid ester found in a number of plant families - was used. Geometrical isomers of L-CA were formed by exposing the compound to ultraviolet (UV) radiation, to mimic the natural environment. The high performance liquid chromatography photo-diode array (HPLC-PDA) and ultra-high performance liquid chromatography mass spectrometry (UHPLC-MS) platforms were used to analyze the trans and cis geometrical isomers of L-CA. The HPLC-PDA results confirmed the generation of two cis geometrical isomers following UV exposure of the authentic trans-L-CA standard. Furthermore, the HPLC-PDA analyses demonstrated that the changes in both column chemistry (reverse-phase: C₁₈, biphenyl, phenyl-hexyl and pentafluorophenyl propyl) and mobile phase composition (aqueous acetonitrile and aqueous methanol) affect the chromatographic elution profiles of the L-CA isomers. The MS results, on the other hand, revealed undisputed fragmentation differences between the geometrical isomers of L-CA. Thus, this study demonstrates that the identification of the L-CA isomers can be achieved more efficiently and confidently with good chromatography coupled to well-optimized mass spectrometry conditions, a requirement which has been proven impossible with other types of HCA derivatives. Moreover, differences in the binding modes of L-CA geometrical isomers to the HIV type 1 integrase enzyme were observed, suggesting a synergistic anti-HIV-1 activity of these isomers.

Untargeted metabolomics analysis reveals dynamic changes in azelaic acid- and salicylic acid derivatives in LPS-treated Nicotiana tabacum cells

To counteract biotic stress factors, plants employ multilayered defense mechanisms responsive to pathogen-derived elicitor molecules, and regulated by different phytohormones and signaling molecules. Here, lipopolysaccharide (LPS), a microbe-associated molecular pattern (MAMP) molecule, was used to induce defense responses in Nicotiana tabacum cell suspensions. Intracellular metabolites were extracted with methanol and analyzed using a liquid chromatography-mass spectrometry (UHPLC-qTOF-MS/MS) platform. The generated data were processed and examined with multivariate and univariate statistical tools. The results show time-dependent dynamic changes and accumulation of glycosylated signaling molecules, specifically those of azelaic acid, salicylic acid and methyl-salicylate as contributors to the altered metabolomic state in LPS-treated cells.

Ergosterol, an orphan fungal microbe-associated molecular pattern (MAMP)

Fungal pathogens continue to pose a significant threat to crop production and food supply. The early stages of plant-fungus interactions are mostly mediated by microbe-associated molecular pattern (MAMP) molecules, perceived by plant pattern recognition receptors (PRRs). Currently, the identified fungal MAMP molecules include chitin, chitosan, β-glucans, elicitins and ergosterol. Although the molecular battles between host plants and infecting fungal phytopathogens have been studied extensively, many aspects still need to be investigated to obtain a holistic understanding of the intrinsic mechanisms, which is paramount in combating fungal plant diseases. Here, an overview is given of the most recent findings concerning an 'orphan' fungal MAMP molecule, ergosterol, and we present what is currently known from a synopsis of different genes, proteins and metabolites found to play key roles in induced immune responses in plant-fungus interactions. Clearly, integrative investigations are still needed to provide a comprehensive systems-based understanding of the dynamics associated with molecular mechanisms in plant-ergosterol interactions and associated host responses.

Multi-platform metabolomic analyses of ergosterol-induced dynamic changes in Nicotiana tabacum cells

Metabolomics is providing new dimensions into understanding the intracellular adaptive responses in plants to external stimuli. In this study, a multi-technology-metabolomic approach was used to investigate the effect of the fungal sterol, ergosterol, on the metabolome of cultured tobacco cells. Cell suspensions were treated with different concentrations (0-1000 nM) of ergosterol and incubated for different time periods (0-24 h). Intracellular metabolites were extracted with two methods: a selective dispersive liquid-liquid micro-extraction and a general methanol extraction. Chromatographic techniques (GC-FID, GC-MS, GC × GC-TOF-MS, UHPLC-MS) and (1)H NMR spectroscopy were used for quantitative and qualitative analyses. Multivariate data analyses (PCA and OPLS-DA models) were used to extract interpretable information from the multidimensional data generated from the analytical techniques. The results showed that ergosterol triggered differential changes in the metabolome of the cells, leading to variation in the biosynthesis of secondary metabolites. PCA scores plots revealed dose- and time-dependent metabolic variations, with optimal treatment conditions being found to be 300 nM ergosterol and an 18 h incubation period. The observed ergosterol-induced metabolic changes were correlated with changes in defence-related metabolites. The 'defensome' involved increases in terpenoid metabolites with five antimicrobial compounds (the bicyclic sesquiterpenoid phytoalexins: phytuberin, solavetivone, capsidiol, lubimin and rishitin) and other metabolites (abscisic acid and phytosterols) putatively identified. In addition, various phenylpropanoid precursors, cinnamic acid derivatives and - conjugates, coumarins and lignin monomers were annotated. These annotated metabolites revealed a dynamic reprogramming of metabolic networks that are functionally correlated, with a high complexity in their regulation.

Development and Optimization of an UPLC-QTOF-MS/MS Method Based on an In-Source Collision Induced Dissociation Approach for Comprehensive Discrimination of Chlorogenic Acids Isomers from Momordica Plant Species

Chlorogenic acids (CGA) have been profiled in the leaves of Momordica balsamina, Momordica charantia, and Momordica foetida. All three species were found to contain the trans and cis isomers of 4-acyl para-coumaroylquinic acid (pCoQA), caffeoylquinic acid (CQA), and feruloylquinic acid (FQA). To the best of our knowledge, this is the first report of pCoQA and FQA and their cis isomers in these Momordica species. These profiles were obtained by a newly developed UPLC-qTOF-MS method based on the in-source collision induced dissociation (ISCID) method optimized to mimic the MS(2) and MS(3) fragmentation of an ion trap-based MS. The presence of the cis isomers is believed to be due to high UV exposure of these plants. Furthermore, the absence of the 3-acyl and 5-acyl CGA molecules points to a metabolic mark that is unusual and represents a very interesting biochemical phenotype of these species. Our optimized ISCID method was also shown to be able to distinguish between the geometrical isomers of all three forms of CGA, a phenomenon previously deemed impossible with other common mass spectrometry systems used for CGA analyses.