Metabolomics: A Tool for Cultivar Phenotyping and Investigation of Grain Crops

Metabolomic and transcriptomic analyses highlight metabolic regulatory networks of Salvia miltiorrhiza in response to replant disease

BACKGROUND

Salvia miltiorrhiza, a well-known traditional Chinese medicine, frequently suffers from replant diseases that adversely affect its quality and yield. To elucidate S. miltiorrhiza's metabolic adaptations to replant disease, we analyzed its metabolome and transcriptome, comparing normal and replant diseased plants for the first time.

RESULTS

We identified 1,269 metabolites, 257 of which were differentially accumulated metabolites, and identified 217 differentially expressed genes. Integrated transcriptomic and metabolomic analyses revealed a significant up-regulation and co-expression of metabolites and genes associated with plant hormone signal transduction and flavonoid biosynthesis pathways in replant diseases. Within plant hormone signal transduction pathway, plants afflicted with replant disease markedly accumulated indole-3-acetic acid and abscisic acid, correlating with high expression of their biosynthesis-related genes (SmAmidase, SmALDH, SmNCED, and SmAAOX3). Simultaneously, changes in hormone concentrations activated plant hormone signal transduction pathways. Moreover, under replant disease, metabolites in the local flavonoid metabolite biosynthetic pathway were significantly accumulated, consistent with the up-regulated gene (SmHTC1 and SmHTC2). The qRT-PCR analysis largely aligned with the transcriptomic results, confirming the trends in gene expression. Moreover, we identified 10 transcription factors co-expressed with differentially accumulated metabolites.

CONCLUSIONS

Overall, we revealed the key genes and metabolites of S. miltiorrhiza under replant disease, establishing a robust foundation for future inquiries into the molecular responses to combat replant stress.

Critical Review of Selected Analytical Platforms for GC-MS Metabolomics Profiling-Case Study: HS-SPME/GC-MS Analysis of Blackberry's Aroma

Data processing and data extraction are the first, and most often crucial, steps in metabolomics and multivariate data analysis in general. There are several software solutions for these purposes in GC-MS metabolomics. It becomes unclear which platform offers what kind of data and how that information influences the analysis's conclusions. In this study, selected analytical platforms for GC-MS metabolomics profiling, SpectConnect and XCMS as well as MestReNova software, were used to process the results of the HS-SPME/GC-MS aroma analyses of several blackberry varieties. In addition, a detailed analysis of the identification of the individual components of the blackberry aroma club varieties was performed. In total, 72 components were detected in the XCMS platform, 119 in SpectConnect, and 87 and 167 in MestReNova, with automatic integral and manual correction, respectively, as well as 219 aroma components after manual analysis of GC-MS chromatograms. The obtained datasets were fed, for multivariate data analysis, to SIMCA software, and underwent the creation of PCA, OPLS, and OPLS-DA models. The results of the validation tests and VIP-pred. scores were analyzed in detail.

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.

Unveiling a differential metabolite modulation of sorghum varieties under increasing tunicamycin-induced endoplasmic reticulum stress

Plants trigger endoplasmic reticulum (ER) pathways to survive stresses, but the assistance of ER in plant tolerance still needs to be explored. Thus, we selected sensitive and tolerant contrasting abiotic stress sorghum varieties to test if they present a degree of tolerance to ER stress. Accordingly, this work evaluated crescent concentrations of tunicamycin (TM µg mL-1): control (0), lower (0.5), mild (1.5), and higher (2.5) on the initial establishment of sorghum seedlings CSF18 and CSF20. ER stress promoted growth and metabolism reductions, mainly in CSF18, from mild to higher TM. The lowest TM increased SbBiP and SbPDI chaperones, as well as SbbZIP60, and SbbIRE1 gene expressions, but mild and higher TM decreased it. However, CSF20 exhibited higher levels of SbBiP and SbbIRE1 transcripts. It corroborated different metabolic profiles among all TM treatments in CSF18 shoots and similarities between profiles of mild and higher TM in CSF18 roots. Conversely, TM profiles of both shoots and roots of CSF20 overlapped, although it was not complete under low TM treatment. Furthermore, ER stress induced an increase of carbohydrates (dihydroxyacetone in shoots, and cellobiose, maltose, ribose, and sucrose in roots), and organic acids (pyruvic acid in shoots, and butyric and succinic acids in roots) in CSF20, which exhibited a higher degree of ER stress tolerance compared to CSF18 with the root being the most affected plant tissue. Thus, our study provides new insights that may help to understand sorghum tolerance and the ER disturbance as significant contributor for stress adaptation and tolerance engineering.

Metabolomics: A suitable foodomics approach to the geographical origin traceability of Ethiopian Arabica specialty coffees

Coffee arabica, originated in Ethiopia, is considered a quality bean for its high sensory qualities, and has a special price in the world coffee market. The country is a pool of genetic diversity for Arabica coffee, and coffee from different regions has a distinct flavor profile. Their exceptional quality is attributed to their genetic diversity, favorable environmental conditions, and agroforestry-based production system. However, the country still needs to benefit from its single-origin product due to a lack of appropriate traceability information to register for its geographical indication. Certification of certain plants or plant-derived products emerged to inform consumers about their exceptional qualities due to their geographical origin and protect the product from fraud. The recently emerging foodomics approaches, namely proteomics, genomics, and metabolomics, are reported as suitable means of regional agri-food product authentication and traceability. Particularly, the metabolomics approach provides truthful information on product traceability. Despite efforts by some researchers to trace the geographical origin of Ethiopian Arabica coffees through stable isotope and phenolic compound profiling and elemental analysis, foodomics approaches are not used to trace the geographical origin of Arabica specialty coffees from various parts of the country. A metabolomics-based traceability system that demonstrates the connection between the exceptional attributes of Ethiopian Arabica specialty coffees and their geographic origin is recommended to maximize the benefit of single-origin coffees.

Mass Spectrometry-Based Investigation of Sugarcane Exposed to Five Different Pesticides

The use of agrochemicals has become a standard practice worldwide to ensure the productivity and quality of sugarcane crops. This study aimed to analyze the metabolic changes in sugarcane culms treated with five different nematicides. The experimental design was randomized in blocks, and agro-industrial and biometric variables were evaluated. The samples were extracted and then analyzed using LC-MS, LC-MS/MS, and LC-HRMS. The data obtained were submitted to statistical methods (PCA and PLS). Fragmentation patterns, retention time, and UV absorptions of the main features were analyzed. The plantations treated with carbosulfan (T4) obtained higher agricultural productivity and total recoverable sugar (TRS), while the use of benfuracarb (T3) was associated with lower growth and lower TRS. Statistical analysis revealed the contribution of the features at m/z 353 and m/z 515, assigned as chlorogenic acids, which discriminated the groups. The MS profile also supported the occurrence of flavonoids (C-glycosides and O-glycosides) in the samples.

Metabolic Variations among Three New Tea Varieties Cultivated in Shandong, China

Cultivar identification is a necessary step in tea breeding programs. Rapid identification methods would greatly improve these breeding processes. To preliminarily identify the three new Lucha tea varieties (LC6, LC7, and LC17) cultivated in Shandong, we measured their main agronomic characters and biochemical components. Then, we analyzed the metabolic profiles of these tea varieties and Fuding Dabaicha (FD) using a UPLC-ESI-MS/MS system. Their biochemical components indicated that the Lucha varieties had excellent varietal characteristics, with higher amino acid contents. Furthermore, secondary metabolism changed a lot in the Lucha tea varieties compared with that in the FD, with their accumulations of flavonoids and phenolic acids showing significant differences. These differential flavonoids were dominated by flavones and flavanone, flavonols, flavonoid carbonosides, and flavanols monomer. Flavanols especially, including epicatechin glucoside, epicatechin-3-(3″-O-methyl)gallate, epigallocatechin-3-O-(3,5-O-dimethyl)gallate, and epitheaflavic acid-3-O-Gallate, showed higher levels in the Lucha varieties. The phenolic acids containing caffeoyl groups showed higher levels in the Lucha varieties than those in the FD, while those containing galloyl groups showed a reverse pattern. Nitrogen metabolism, including amino acids, also showed obvious differences between the Lucha varieties and FD. The differential amino acids were mainly higher in the Lucha varieties, including 5-L-glutamyl-L-amino acid, N-monomethyl-L-arginine, and N-α-acetyl-L-ornithine. By using these approaches, we found that LC6, LC7, and LC17 were excellent varieties with a high yield and high quality for making green teas in Shandong.

Evaluation of Sustainable Recycled Products to Increase the Production of Nutraceutical and Antibacterial Molecules in Basil Plants by a Combined Metabolomic Approach

BACKGROUND

An important goal of modern medicine is the development of products deriving from natural sources to improve environmental sustainability. In this study, humic substances (HS) and compost teas (CTs) extracted from artichoke (ART) and coffee grounds (COF) as recycled biomasses were employed on Ocimum basilicum plants to optimize the yield of specific metabolites with nutraceutical and antibacterial features by applying sustainable strategies.

METHODS

The molecular characteristics of compost derivates were elucidated by Nuclear Magnetic Resonance spectroscopy to investigate the structure-activity relationship between organic extracts and their bioactive potential. Additionally, combined untargeted and targeted metabolomics workflows were applied to plants treated with different concentrations of compost extracts.

RESULTS

The substances HS-ART and CT-COF improved both antioxidant activity (TEAC values between 39 and 55 μmol g^-1) and the antimicrobial efficacy (MIC value between 3.7 and 1.3 μg mL^-1) of basil metabolites. The metabolomic approach identified about 149 metabolites related to the applied treatments. Targeted metabolite quantification further highlighted the eliciting effect of HS-ART and CT-COF on the synthesis of aromatic amino acids and phenolic compounds for nutraceutical application.

CONCLUSIONS

The combination of molecular characterization, biological assays, and an advanced metabolomic approach, provided innovative insight into the valorization of recycled biomass to increase the availability of natural compounds employed in the medical field.

Effect of Production Technology Intensity on the Grain Yield, Protein Content and Amino Acid Profile in Common and Durum Wheat Grain

Products derived from wheat grains are an important source of protein in the daily diet of people in many parts of the world. The biological value of protein is determined by its amino acid composition and the proportions of the individual amino acids. Synthesis of these compounds in wheat grains is influenced by genetic factors, as well as habitat conditions and the agrotechnology applied in cultivation. The aim of this study was to assess the effect of production technology (integrated, intensive) on the grain yield and the content amino acid profile of protein in common and durum wheat grain. Field research was conducted at the Experimental Station IUNG-PIB in Osiny (Poland) in two growing seasons. It was found that grain yield significantly depended on the weather conditions in the years of harvesting and genotype, but did not depend on the production technology. On the other hand, the protein content and their amino acid composition depended significantly on the production technology and genotype. A significantly higher content of protein substances was found in durum wheat grain. Increasing the intensity of production technology had a positive effect on the total protein content and the content of individual amino acids, both exogenous and endogenous. The amino acid limiting the biological value of protein contained in grains of both wheat species was lysine, and the deficiency of this amino acid was significantly lower in grain protein from intensive than integrated cultivation technology.

Anti-Quorum Sensing and Anti-Biofilm Activity of Pelargonium × hortorum Root Extract against Pseudomonas aeruginosa: Combinatorial Effect of Catechin and Gallic Acid

HPLC-UV was used to compare the major constituents of two Pelargonium × hortorum cultivars and Pelargonium sidoides root extract. It revealed the presence of catechin and gallic acid in high concentrations and the absence of umckalin in P. × hortorum root extracts. The antibacterial activity of these extracts was screened against 19 Pseudomonas aeruginosa clinical isolates. P. × hortorum root extracts showed the lowest MIC values (512-1024 µg/mL). This activity was concluded to be attributable to the high concentrations of catechin and gallic acid. The anti-biofilm activity of catechin, gallic acid, and their combination was examined by a crystal violet assay. The combination reduced the percentage of strong and moderate biofilm-forming isolates from 52.63% to 5.26%. The impact on lasI and lasR genes expression using qRT-PCR and simultaneous docking against LasR protein was explored. The combination downregulated lasI and lasR gene expression in eight and six P. aeruginosa isolates, respectively, and showed the greatest docking score. Additionally, the in vivo protection capability of this combination in infected mice showed enhancement in the survival rate. Our study revealed the potential biofilm and quorum-sensing-inhibitory activity of the catechin and gallic acid combination as a novel alternative to inhibit bacterial pathogenicity.

Metabolomics as a Prospective Tool for Soybean (Glycine max) Crop Improvement

Global demand for soybean and its products has stimulated research into the production of novel genotypes with higher yields, greater drought and disease tolerance, and shorter growth times. Genetic research may be the most effective way to continue developing high-performing cultivars with desirable agronomic features and improved nutritional content and seed performance. Metabolomics, which predicts the metabolic marker for plant performance under stressful conditions, is rapidly gaining interest in plant breeding and has emerged as a powerful tool for driving crop improvement. The development of increasingly sensitive, automated, and high-throughput analytical technologies, paired with improved bioinformatics and other omics techniques, has paved the way for wide characterization of genetic characteristics for crop improvement. The combination of chromatography (liquid and gas-based) with mass spectrometry has also proven to be an indisputable efficient platform for metabolomic studies, notably plant metabolic fingerprinting investigations. Nevertheless, there has been significant progress in the use of nuclear magnetic resonance (NMR), capillary electrophoresis, and Fourier-transform infrared spectroscopy (FTIR), each with its own set of benefits and drawbacks. Furthermore, utilizing multivariate analysis, principal components analysis (PCA), discriminant analysis, and projection to latent structures (PLS), it is possible to identify and differentiate various groups. The researched soybean varieties may be correctly classified by using the PCA and PLS multivariate analyses. As metabolomics is an effective method for evaluating and selecting wild specimens with desirable features for the breeding of improved new cultivars, plant breeders can benefit from the identification of metabolite biomarkers and key metabolic pathways to develop new genotypes with value-added features.

Metabolomics and Chemoinformatics in Agricultural Biotechnology Research: Complementary Probes in Unravelling New Metabolites for Crop Improvement

Simple Summary

The world is facing an overarching threat to food security, particularly in developing nations. The issue is further exacerbated by the apparent impacts of biotic and abiotic stresses driving down crop yields and productivity. Conventional strategies to improve yields and sustain productivity have been employed, including plant breeding for favourable and resilient agronomic traits. However, the efficacy and success rates of these methods are declining, partly due to the rapid changes in climate variability and the emergence of new and resistant phytopathogens. Additionally, the process of creating new and improved transgenic varieties of crops is long and can be expensive. Thus, new and innovative technologies are required for crop improvement. This review explores recent advances in the science of metabolomics and chemoinformatics, which have presented an avenue for rapid and robust analysis; moreover, it explores the elucidation of the complex plant metabolome, providing the opportunity to decipher the reactionary mechanisms of plants to the surrounding environment through their metabolic activity. As such, specific metabolites can, thus, be selected as biomarkers for crop improvement based on their functional characteristics under varying environmental conditions (growth, development, and defence). This new knowledge can enhance breeding practices through rapid and robust metabolic engineering techniques for sustainable agriculture.

Abstract

The United Nations (UN) estimate that the global population will reach 10 billion people by 2050. These projections have placed the agroeconomic industry under immense pressure to meet the growing demand for food and maintain global food security. However, factors associated with climate variability and the emergence of virulent plant pathogens and pests pose a considerable threat to meeting these demands. Advanced crop improvement strategies are required to circumvent the deleterious effects of biotic and abiotic stress and improve yields. Metabolomics is an emerging field in the omics pipeline and systems biology concerned with the quantitative and qualitative analysis of metabolites from a biological specimen under specified conditions. In the past few decades, metabolomics techniques have been extensively used to decipher and describe the metabolic networks associated with plant growth and development and the response and adaptation to biotic and abiotic stress. In recent years, metabolomics technologies, particularly plant metabolomics, have expanded to screening metabolic biomarkers for enhanced performance in yield and stress tolerance for metabolomics-assisted breeding. This review explores the recent advances in the application of metabolomics in agricultural biotechnology for biomarker discovery and the identification of new metabolites for crop improvement. We describe the basic plant metabolomics workflow, the essential analytical techniques, and the power of these combined analytical techniques with chemometrics and chemoinformatics tools. Furthermore, there are mentions of integrated omics systems for metabolomics-assisted breeding and of current applications.

Community metabolomics provides insights into mechanisms of pollution-induced community tolerance of periphyton

Chemical pollution is a major concern for freshwater ecosystems, but the impact and mechanisms of chemical stressors on communities are barely understood. Pollution stress beyond natural homeostatic capacities can trigger succession of tolerant species within a community, enhancing the overall community tolerance. This process was operationalized in the Pollution-Induced Community Tolerance (PICT) concept and applied in many case studies, however, the molecular mechanisms of community tolerance and implications for ecological functions remain largely unexplored. Our study aimed to demonstrate that 1) community metabolomics can unravel potential mechanisms of PICT in periphyton and 2) induced tolerance helps to maintain primary production under re-occuring pollution. To this end, we grew periphyton for 5 weeks with and without the model herbicide diuron in microcosms, quantified PICT, and determined the related metabolic fingerprint of periphyton by GC-MS-based untargeted metabolomics. Further, we explored the autotrophic community based on pigment composition and functional parameters including photosynthesis and gross primary production. Chronic diuron exposure resulted in a shift in pigment composition, higher community tolerance and an individual metabolic fingerprint in the contaminated communities. Opposing responses of selected metabolites during a short-term exposure indicated differences in diuron pre-adaptation in the different communities. Metabolites (threonic acid and two sugar acid lactones) were found to be related to tolerance development, suggesting that ascorbate metabolism was induced in contaminated communities. Despite these compensating mechanism, contaminated communities were compromised in production-to-respiration ratio and biomass. A ranking of sensitivity thresholds of different biological endpoints revealed that metabolites were less sensitive than photosynthetic parameters, which reflects the mode-of-action of the herbicide. In conclusion, we could demonstrate that community metabolomics is able to unravel complex biochemical changes and allows mechanistic insights into community tolerance. Moreover, we were able to show that induced community tolerance was insufficient to safeguard functions like primary production.

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.

Evaluation of ORAC, IR and NMR metabolomics for predicting ripening stage and variety in melon (Cucumis melo L.)

A combination of FTIR- and NMR-based metabolomics approaches coupled to multivariate data analysis techniques was used for the first time to characterize and explore the metabolic changes along the ripening of two Spanish melon landraces (Jimbee N and Jimbee XL). Furthermore, the fatty acids profile and the antioxidant capacity were investigated by GC-FID and ORAC method, respectively. Despite FTIR was able to identify changes in the sugars content between fruits of different maturity stages, it failed to discriminate between both varieties, being exceeded by NMR in both situations. Increased fruit maturation led to an increase of sucrose, fatty acids and β-carotene, accompanied by a decrease of glucose, fructose, citrate, amino acids, and polyphenols (which were positively correlated with fruits antioxidant activity).

Chemical Fingerprinting of Heat Stress Responses in the Leaves of Common Wheat by Fourier Transform Infrared Spectroscopy

Wheat (Triticum aestivum L.) is known to be negatively affected by heat stress, and its production is threatened by global warming, particularly in arid regions. Thus, efforts to better understand the molecular responses of wheat to heat stress are required. In the present study, Fourier transform infrared (FTIR) spectroscopy, coupled with chemometrics, was applied to develop a protocol that monitors chemical changes in common wheat under heat stress. Wheat plants at the three-leaf stage were subjected to heat stress at a 42 °C daily maximum temperature for 3 days, and this led to delayed growth in comparison to that of the control. Measurement of FTIR spectra and their principal component analysis showed partially overlapping features between heat-stressed and control leaves. In contrast, supervised machine learning through linear discriminant analysis (LDA) of the spectra demonstrated clear discrimination of heat-stressed leaves from the controls. Analysis of LDA loading suggested that several wavenumbers in the fingerprinting region (400-1800 cm^-1) contributed significantly to their discrimination. Novel spectrum-based biomarkers were developed using these discriminative wavenumbers that enabled the successful diagnosis of heat-stressed leaves. Overall, these observations demonstrate the versatility of FTIR-based chemical fingerprints for use in heat-stress profiling in wheat.

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.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

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.

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.

Genetic Improvement in Sunflower Breeding—Integrated Omics Approach

Foresight in climate change and the challenges ahead requires a systematic approach to sunflower breeding that will encompass all available technologies. There is a great scarcity of desirable genetic variation, which is in fact undiscovered because it has not been sufficiently researched as detection and designing favorable genetic variation largely depends on thorough genome sequencing through broad and deep resequencing. Basic exploration of genomes is insufficient to find insight about important physiological and molecular mechanisms unique to crops. That is why integrating information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and phenomics enables a comprehensive understanding of the molecular mechanisms in the background of architecture of many important quantitative traits. Omics technologies offer novel possibilities for deciphering the complex pathways and molecular profiling through the level of systems biology and can provide important answers that can be utilized for more efficient breeding of sunflower. In this review, we present omics profiling approaches in order to address their possibilities and usefulness as a potential breeding tools in sunflower genetic improvement.

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.

Metabolomic approaches for the determination of metabolites from pathogenic microorganisms: A review

Metabolomics is a high precision analytical approach to obtaining detailed information of varieties of metabolites produced in biological systems, including foods. This study reviews the use of metabolomic approaches such as liquid chromatography mass spectrometry (LCMS), gas chromatography mass spectrometry (GC-MS), matrix assisted laser desorption /ionization tandem time of flight mass spectrometry (MALDI-TOF-MS) and nuclear magnetic resonance (NMR) for investigating the presence of foodborne pathogens and their metabolites. Pathogenic fungi and their notable metabolites (mycotoxins) have been studied more extensively using metabolomics as compared to bacteria, necessitating further studies in this regard. Nevertheless, such identified fungal and bacteria metabolites could be used as biomarkers for a more rapid detection of these pathogens in food. Other important compounds detected through metabolomics could also be correlated to functionality of these pathogenic strains, determined by the composition of the foods in which they exist, thereby providing insights into their metabolism. Considering the prevalence of these food pathogens, metabolomics still has potentials in the determination of food-borne pathogenic microorganisms especially for the determination of pathogenic bacteria toxins and is expected to generate research interests for further studies and applications.

Metabolomics Analyses of Cotyledon and Plumule Showing the Potential Domestic Selection in Lotus Breeding

Lotus (Nelumbo nucifera) seeds are widely consumed as functional food or herbal medicine, of which cotyledon (CL) is the main edible part, and lotus plumule (LP) is commonly utilized in traditional Chinese medicine. However, few studies have been conducted to investigate the chemical components of CL and LP in dry lotus seeds, not to mention the comparison between wild and domesticated varieties. In this study, a widely targeted metabolomics approach based on Ultra Performance Liquid Chromatography-electrospray ionization-Tandem mass spectrometry (UPLC-ESI-MS/MS) was utilized to analyze the metabolites in CL and LP of China Antique (“CA”, a wild variety) and Jianxuan-17 (“JX”, a popular cultivar). A total of 402 metabolites were identified, which included flavonoids (23.08% to 27.84%), amino acids and derivatives (14.18–16.57%), phenolic acids (11.49–12.63%), and lipids (9.14–10.95%). These metabolites were classified into ten clusters based on their organ or cultivar-specific characters. Most of these metabolites were more abundant in LP than in CL for both varieties, except for metabolites belonging to organic acids and lipids. The analysis of differentially accumulated metabolites (DAMs) demonstrated that more than 25% of metabolites detected in our study were DAMs in CL and LP comparing “JX” with “CA”, most of which were less abundant in “JX”, including 35 flavonoids in LP, 23 amino acids and derivatives in CL, 7 alkaloids in CL, and 10 nucleotides and derivatives in LP, whereas all of 11 differentially accumulated lipids in LP were more abundant in “JX”. Together with the fact that the seed yield of “JX” is much higher than that of “CA”, these results indicated that abundant metabolites, especially the functional secondary metabolites (mainly flavonoids and alkaloids), were lost during the process of breeding selection.

Review: Metabolomics as a prediction tool for plants performance under environmental stress

Metabolomics as a diagnosis tool for plant performance has shown good features for breeding and crop improvement. Additionally, due to limitations in land area and the increasing climate changes, breeding projects focusing on abiotic stress tolerance are becoming essential. Nowadays no universal method is available to identify predictive metabolic markers. As a result, research aims must dictate the best method or combination of methods. To this end, we will introduce the key aspects to consider regarding growth scenarios and sampling strategies and discuss major analytical and data treatment approaches that are available to find metabolic markers of plant performance.

Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat

Genomic selection with genome-wide distributed molecular markers has evolved into a well-implemented tool in many breeding programs during the last decade. The resistance against Fusarium head blight (FHB) in wheat is probably one of the most thoroughly studied systems within this framework. Aside from the genome, other biological strata like the transcriptome have likewise shown some potential in predictive breeding strategies but have not yet been investigated for the FHB-wheat pathosystem. The aims of this study were thus to compare the potential of genomic with transcriptomic prediction, and to assess the merit of blending incomplete transcriptomic with complete genomic data by the single-step method. A substantial advantage of gene expression data over molecular markers has been observed for the prediction of FHB resistance in the studied diversity panel of breeding lines and released cultivars. An increase in prediction ability was likewise found for the single-step predictions, although this can mostly be attributed to an increased accuracy among the RNA-sequenced genotypes. The usage of transcriptomics can thus be seen as a complement to already established predictive breeding pipelines with pedigree and genomic data, particularly when more cost-efficient multiplexing techniques for RNA-sequencing will become more accessible in the future.

Biostimulants for Plant Growth and Mitigation of Abiotic Stresses: A Metabolomics Perspective

Adverse environmental conditions due to climate change, combined with declining soil fertility, threaten food security. Modern agriculture is facing a pressing situation where novel strategies must be developed for sustainable food production and security. Biostimulants, conceptually defined as non-nutrient substances or microorganisms with the ability to promote plant growth and health, represent the potential to provide sustainable and economically favorable solutions that could introduce novel approaches to improve agricultural practices and crop productivity. Current knowledge and phenotypic observations suggest that biostimulants potentially function in regulating and modifying physiological processes in plants to promote growth, alleviate stresses, and improve quality and yield. However, to successfully develop novel biostimulant-based formulations and programs, understanding biostimulant-plant interactions, at molecular, cellular and physiological levels, is a prerequisite. Metabolomics, a multidisciplinary omics science, offers unique opportunities to predictively decode the mode of action of biostimulants on crop plants, and identify signatory markers of biostimulant action. Thus, this review intends to highlight the current scientific efforts and knowledge gaps in biostimulant research and industry, in context of plant growth promotion and stress responses. The review firstly revisits models that have been elucidated to describe the molecular machinery employed by plants in coping with environmental stresses. Furthermore, current definitions, claims and applications of plant biostimulants are pointed out, also indicating the lack of biological basis to accurately postulate the mechanisms of action of plant biostimulants. The review articulates briefly key aspects in the metabolomics workflow and the (potential) applications of this multidisciplinary omics science in the biostimulant industry.

Molecular Basis Underlying Common Cutworm Resistance of the Primitive Soybean Landrace Peking

The common cutworm (CCW; Spodoptera litura) is one of the major insect pests of soybean in Asia and Oceania. Although quantitative trail loci related to CCW resistance have been introduced into leading soybean cultivars, these do not exhibit sufficient resistance against CCW. Thus, understanding the genetic and metabolic resistance mechanisms of CCW as well as integrating other new resistance genes are required. In this study, we focused on a primitive soybean landrace, Peking, which has retained resistances to various pests. We found a resistance to CCW in Peking by the detached-leaf feeding assay, and subsequently determined the genetic and metabolic basis of the resistance mechanism using chromosome segment substitution lines (CSSLs) of Peking. Several characteristic metabolites for Peking were identified by the metabolomic approach using liquid chromatography/mass spectrometry combined with a principle component analysis. The structure of seven metabolites were determined by nuclear magnetic resonance (NMR) analysis. The genomic segments of Peking on chromosome 06 (Chr06) and Chr20 had a clear association with these metabolites. Moreover, a line possessing a Peking genomic segment on Chr20 inhibited growth of the CCW. The genetic factors and the metabolites on Chr20 in Peking will be useful for understanding mechanisms underlying CCW resistance and breeding resistant soybean cultivars.

Towards superior plant-based foods using metabolomics

Metabolomics is proving a useful approach for many of the main future goals in agronomy and food production such as sustainability/crop resilience, food quality, safety, storage, and nutrition. Targeted and/or untargeted small-molecule analysis, coupled to chemometric analysis, has already unveiled a great deal of the complexity of plant-based foods, but there is still 'dark matter' to be discovered. Moreover, state-of-the-art food metabolomics offers insights into the molecular mechanisms underlying sensorial and nutritional characteristics of foods and thus enables higher precision and speed. This review describes recent applications of food metabolomics from fork to farm and focuses on the opportunities these bring to continue food innovation and support the shift to plant-based foods.

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.