Metabolomics: A Way Forward for Crop Improvement

Unraveling the genetic and molecular basis of heat stress in cotton

Human activities and climate change have resulted in frequent and intense weather fluctuations, leading to diverse abiotic stresses on crops which hampers greatly their metabolic activities. Heat stress, a prevalent abiotic factor, significantly influences cotton plant biological activities resulting in reducing yield and production. We must deepen our understanding of how plants respond to heat stress across various dimensions, encompassing genes, RNAs, proteins, metabolites for effective cotton breeding. Multi-omics methods, primarily genomics, transcriptomics, proteomics, metabolomics, and phenomics, proves instrumental in studying cotton's responses to abiotic stresses. Integrating genomics, transcriptomics, proteomics, and metabolomic is imperative for our better understanding regarding genetics and molecular basis of heat tolerance in cotton. The current review explores fundamental omics techniques, covering genomics, transcriptomics, proteomics, and metabolomics, to highlight the progress made in cotton omics research.

Metabolite-based genome-wide association studies enable the dissection of the genetic bases of flavonoids, betaine and spermidine in wolfberry (Lycium)

Wolfberry is a plant with medicinal and food values. However, its bioactive ingredients and the corresponding genetic bases have not been determined. Here, we de novo generated a chromosome-level genome assembly for wolfberry, yielding a genome sequence of ~1.77 Gb with contig N50 of 50.55 Mb and 39 224 predicted gene models. A variation map, using 307 re-sequenced accessions, was called based on this genome assembly. Furthermore, the fruit metabolome of these accessions was profiled using 563 annotated metabolites, which separated Lycium barbarum L. and non-L. barbarum L. The flavonoids, coumarins, alkaloids and nicotinic acid contents were higher in the former than in the latter. A metabolite-based genome-wide association study mapped 156 164 significant single nucleotide polymorphisms corresponding to 340 metabolites. This included 19 219 unique lead single nucleotide polymorphisms in 1517 significant association loci, of which three metabolites, flavonoids, betaine and spermidine, were highlighted. Two candidate genes, LbUGT (evm.TU.chr07.2692) and LbCHS (evm.TU.chr07.2738), with non-synonymous mutations, were associated with the flavonoids content. LbCHS is a structural gene that interacts with a nearby MYB transcription factor (evm.TU.chr07.2726) both in L. barbarum and L. ruthenicum. Thus, these three genes might be involved in the biosynthesis/metabolism of flavonoids. LbSSADH (evm.TU.chr09.627) was identified as possibly participating in betaine biosynthesis/metabolism. Four lycibarbarspermidines (E-G and O) were identified, and only the lycibarbarspermidines O content was higher in L. barbarum varieties than in non-L. barbarum varieties. The evm.TU.chr07.2680 gene associated with lycibarbarspermidines O was annotated as an acetyl-CoA-benzylalcohol acetyltransferase, suggesting that it is a candidate gene for spermidine biosynthesis. These results provide novel insights into the specific metabolite profile of non-L. barbarum L. and the genetic bases of flavonoids, betaine and spermidine biosynthesis/metabolism.

Latest Review Papers in Molecular Plant Sciences 2023

Success in sustaining food security in the face of global climate change depends on the multi-disciplinary efforts of plant science, physics, mathematics, and computer sciences, whereby each discipline contributes specific concepts, information, and tools [...].

Functional insight into multi-omics-based interventions for climatic resilience in sorghum (Sorghum bicolor): a nutritionally rich cereal crop

MAIN CONCLUSION

The article highlights omics-based interventions in sorghum to combat food and nutritional scarcity in the future. Sorghum with its unique ability to thrive in adverse conditions, has become a tremendous highly nutritive, and multipurpose cereal crop. It is resistant to various types of climatic stressors which will pave its way to a future food crop. Multi-omics refers to the comprehensive study of an organism at multiple molecular levels, including genomics, transcriptomics, proteomics, and metabolomics. Genomic studies have provided insights into the genetic diversity of sorghum and led to the development of genetically improved sorghum. Transcriptomics involves analysing the gene expression patterns in sorghum under various conditions. This knowledge is vital for developing crop varieties with enhanced stress tolerance. Proteomics enables the identification and quantification of the proteins present in sorghum. This approach helps in understanding the functional roles of specific proteins in response to stress and provides insights into metabolic pathways that contribute to resilience and grain production. Metabolomics studies the small molecules, or metabolites, produced by sorghum, provides information about the metabolic pathways that are activated or modified in response to environmental stress. This knowledge can be used to engineer sorghum varieties with improved metabolic efficiency, ultimately leading to better crop yields. In this review, we have focused on various multi-omics approaches, gene expression analysis, and different pathways for the improvement of Sorghum. Applying omics approaches to sorghum research allows for a holistic understanding of its genome function. This knowledge is invaluable for addressing challenges such as climate change, resource limitations, and the need for sustainable agriculture.

Integrative analysis of the transcriptome and metabolome reveals Bacillus atrophaeus WZYH01-mediated salt stress mechanism in maize (Zea mays L.)

Maize is an important food crop that is affected by salt stress during growth, which can hinder plant growth and result in a significant decrease in yield. The application of plant growth-promoting rhizobacteria can improve this situation to a certain extent. However, the gene network of rhizosphere-promoting bacteria regulating the response of maize to salt stress remains elusive. Here, we used metabolomics and transcriptomics techniques to elucidate potential gene networks and salt-response pathways in maize. Phenotypic analysis showed that the Bacillus atrophaeus treatment improved the plant height, leaf area, biomass, ion, nutrient and stomatal indicators of maize. Metabolomic analysis identified that differentially expressed metabolites (DEMs) were primarily concentrated in the arginine, proline and phytohormone signaling metabolic pathways. 4-Hydroxyphenylacetylglutamic acid, L-histidinol, oxoglutaric acid, L-glutamic acid, L-arginine, and L-tyrosine were significantly increased in the Bacillus atrophaeus treatment. Weighted gene coexpression network analysis (WGCNA) identified several hub genes associated with salt response: Zm00001eb155540 and Zm00001eb088790 (ABC transporter family), Zm00001eb419060 (extra-large GTP-binding protein family), Zm00001eb317200 (calcium-transporting ATPase), Zm00001eb384800 (aquaporin NIP1-4) and Zm00001eb339170 (cytochrome P450). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that genes related to plant hormone signal transduction and the MAPK signaling pathway were involved in the response to the effect of Bacillus atrophaeus under salt stress. In the plant hormone signal transduction pathway, 3 differentially expressed genes (DEGs) encoding EIN3/EILs protein, 3 DEGs encoding GH3, 1 DEG encoding PYR/PYL and 6 DEGs encoding PP2C were all upregulated in Bacillus atrophaeus treatment. In the MAPK signaling pathway, 2 DEGs encoding CAT1 and 2 DEGs encoding WRKY22/WRKY29 were significantly upregulated, and the expression of DEGs encoding RbohD was downregulated by the application of Bacillus atrophaeus. In conclusion, the application of Bacillus atrophaeus under salt stress regulated key physiological and molecular processes in plants, which could stimulate the expression of genes related to ion transport and nutrients in maize, alleviate salt stress and promote maize growth to some extent, deepening our understanding of the application of Bacillus atrophaeus under salt stress to improve the salt-response gene network of maize growth.

Metabolomics-driven investigation of plant defense response against pest and pathogen attack

The advancement of metabolomics has assisted in the identification of various bewildering characteristics of the biological system. Metabolomics is a standard approach, facilitating crucial aspects of system biology with absolute quantification of metabolites using minimum samples, based on liquid/gas chromatography, mass spectrometry and nuclear magnetic resonance. The metabolome profiling has narrowed the wide gaps of missing information and has enhanced the understanding of a wide spectrum of plant-environment interactions by highlighting the complex pathways regulating biochemical reactions and cellular physiology under a particular set of conditions. This high throughput technique also plays a prominent role in combined analyses of plant metabolomics and other omics datasets. Plant metabolomics has opened a wide paradigm of opportunities for developing stress-tolerant plants, ensuring better food quality and quantity. However, despite advantageous methods and databases, the technique has a few limitations, such as ineffective 3D capturing of metabolites, low comprehensiveness, and lack of cell-based sampling. In the future, an expansion of plant-pathogen and plant-pest response towards the metabolite architecture is necessary to understand the intricacies of plant defence against invaders, elucidation of metabolic pathway operational during defence and developing a direct correlation between metabolites and biotic stresses. Our aim is to provide an overview of metabolomics and its utilities for the identification of biomarkers or key metabolites associated with biotic stress, devising improved diagnostic methods to efficiently assess pest and pathogen attack and generating improved crop varieties with the help of combined application of analytical and molecular tools.

Drought stress in Lens culinaris: effects, tolerance mechanism, and its smart reprogramming by using modern biotechnological approaches

Among legumes, lentil serves as an imperative source of dietary proteins and are considered an important pillar of global food and nutritional security. The crop is majorly cultivated in arid and semi-arid regions and exposed to different abiotic stresses. Drought stress is a polygenic stress that poses a major threat to the crop productivity of lentils. It negatively influenced the seed emergence, water relations traits, photosynthetic machinery, metabolites, seed development, quality, and yield in lentil. Plants develop several complex physiological and molecular protective mechanisms for tolerance against drought stress. These complicated networks are enabled to enhance the cellular potential to survive under extreme water-scarce conditions. As a result, proper drought stress-mitigating novel and modern approaches are required to improve lentil productivity. The currently existing biotechnological techniques such as transcriptomics, genomics, proteomics, metabolomics, CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/cas9), and detection of QTLs (quantitative trait loci), proteins, and genes responsible for drought tolerance have gained appreciation among plant breeders for developing climate-resilient lentil varieties. In this review, we critically elaborate the impact of drought on lentil, mechanisms employed by plants to tolerate drought, and the contribution of omics approaches in lentils for dealing with drought, providing deep insights to enhance lentil productivity and improve resistance against abiotic stresses. We hope this updated review will directly help the lentil breeders to develop resistance against drought stress.

Graphical Abstract

Systematic Metabolic Profiling of Mice with Sleep-Deprivation

Adequate sleep is essential for the biological maintenance of physical energy. Lack of sleep can affect thinking, lead to emotional anxiety, reduce immunity, and interfere with endocrine and metabolic processes, leading to disease. Previous studies have focused on long-term sleep deprivation and the risk of cancer, heart disease, diabetes, and obesity. However, systematic metabolomics analyses of blood, heart, liver, spleen, kidney, brown adipose tissue, and fecal granules have not been performed. This study aims to systematically assess the metabolic changes in the target organs caused by sleep deprivation in vivo, to search for differential metabolites and the involved metabolic pathways, to further understand the impact of sleep deprivation on health, and to provide strong evidence for the need for early intervention.

Omics-driven exploration and mining of key functional genes for the improvement of food and fiber crops

The deployment of omics technologies has obtained an incredible boost over the past few decades with the advances in next-generation sequencing (NGS) technologies, innovative bioinformatics tools, and the deluge of available biological information. The major omics technologies in the limelight are genomics, transcriptomics, proteomics, metabolomics, and phenomics. These biotechnological advances have modernized crop breeding and opened new horizons for developing crop varieties with improved traits. The genomes of several crop species are sequenced, and a huge number of genes associated with crucial economic traits have been identified. These identified genes not only provide insights into the understanding of regulatory mechanisms of crop traits but also decipher practical grounds to assist in the molecular breeding of crops. This review discusses the potential of omics technologies for the acquisition of biological information and mining of the genes associated with important agronomic traits in important food and fiber crops, such as wheat, rice, maize, potato, tomato, cassava, and cotton. Different functional genomics approaches for the validation of these important genes are also highlighted. Furthermore, a list of genes discovered by employing omics approaches is being represented as potential targets for genetic modifications by the latest genome engineering methods for the development of climate-resilient crops that would in turn provide great impetus to secure global food security.

Differences in the metabolites of brown and milled rice grains of semiwaxy and conventional japonica varieties

In this study, we analyzed the differences in metabolites between semiwaxy japonica rice (Yangnongxiang 28 [YNX28]) and conventional japonica rice (Hongyang 5 [HY5]) before and after brown rice milling. The metabolites of brown and milled rice grains from the two rice varieties were analyzed by LC-MS-based nontargeted metabolomics. A total of 266 differentially abundant metabolites (DMs) were tentatively identified in brown rice grains of YNX28 (YNX28B) compared with milled rice grains of YNX28 (YNX28H), and these included 248 upregulated and 12 downregulated DMs. A total of 273 (234 upregulated and 39 downregulated) DMs were tentatively identified in brown rice grains of HY5 (HY5B) compared with milled rice grains of this variety (HY5H). Kyoto Encyclopedia of Genes and Genomes pathway involved and enrichment analyses revealed that 53 and 7 metabolite pathways were enriched and significantly enriched (p < 0.05), respectively, in the DMs identified in YNX28B compared with YNX28H, and the main enriched pathways were related to starch and sucrose metabolism, glycerol phospholipid metabolism, arginine and proline metabolism, and glycine, serine and threonine metabolism. Forty-six metabolite pathways were enriched in DMs identified in HY5B compared with HY5H, and these included 16 pathways that were significantly enriched (p < 0.05); in addition, the main enriched pathways were related to starch and sucrose metabolism, glycerol phospholipid metabolism, arginine and proline metabolism, and glycine, serine and threonine metabolism. This study provides a theoretical reference for further on the changes in metabolites during rice processing and provides a basis for improving the nutritional quality in rice. PRACTICAL APPLICATION: Original data were obtained regarding the changes of different metabolites in semiwaxy japonica rice and conventional japonica rice before and after processing. The purpose of this study was to investigate the difference of metabolite loss in two rice varieties before and after processing. This paper reports on the differences of metabolites between the two types of japonica rice before and after processing, as well as the changes of key metabolites before and after processing, it also provides important theoretical basis for developing new rice varieties with good nutritional quality.

Comparative metabolomics study on areca nut from China and Southeast Asia (Thailand and Indonesia)

INTRODUCTION

Areca nut is an economic crop and an important component in traditional Chinese medicine (TCM) and ethnomedicine. The crop is rich in alkaloids and flavonoids. Most previous studies have focused on the chemical components, especially alkaloids, in crops from certain areca nut-producing areas.

OBJECTIVE

The purpose of this study was to compare the differences in areca nut seeds in two main cultivation areas, identify differential metabolites, and evaluate seed quality in different production areas.

METHODS

A widely targeted metabolomics method based on ultrahigh-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC-QQQ-MS), combined with the TCM systems pharmacology (TCMSP) database and multivariate statistical analysis, was used in this study to maximise the differentiation between quality characteristics of areca nut seeds from China and Southeast Asian regions.

RESULTS

Altogether, 1031 metabolites were identified in areca nut seeds; by querying the TCMSP database, 375 metabolites were identified as the main active ingredients. Moreover, the research showed that the metabolic profiles of areca nut seeds from China (ASCN) and Southeast Asia (ASSA) exhibit significant differences, and the difference is mainly reflected in 318 compounds. The relative content of 146 metabolites in ASCN was significantly higher than that in ASSA. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) comparative analysis, areca nut seed metabolites in Chinese production areas were determined to have a wider metabolic pathway.

CONCLUSION

The areca nut seeds from cultivation areas possess many metabolites that are beneficial for health, including alkaloids, amino acids, phenolic acids, and lipids. Thus, compared with ASSA, ASCN have a higher medicinal value. This study provides a direction for the subsequent development and utilisation of areca nut seeds.

Smart reprograming of plants against salinity stress using modern biotechnological tools

Climate change gives rise to numerous environmental stresses, including soil salinity. Salinity/salt stress is the second biggest abiotic factor affecting agricultural productivity worldwide by damaging numerous physiological, biochemical, and molecular processes. In particular, salinity affects plant growth, development, and productivity. Salinity responses include modulation of ion homeostasis, antioxidant defense system induction, and biosynthesis of numerous phytohormones and osmoprotectants to protect plants from osmotic stress by decreasing ion toxicity and augmented reactive oxygen species scavenging. As most crop plants are sensitive to salinity, improving salt tolerance is crucial in sustaining global agricultural productivity. In response to salinity, plants trigger stress-related genes, proteins, and the accumulation of metabolites to cope with the adverse consequence of salinity. Therefore, this review presents an overview of salinity stress in crop plants. We highlight advances in modern biotechnological tools, such as omics (genomics, transcriptomics, proteomics, and metabolomics) approaches and different genome editing tools (ZFN, TALEN, and CRISPR/Cas system) for improving salinity tolerance in plants and accomplish the goal of "zero hunger," a worldwide sustainable development goal proposed by the FAO.

Targeted Metabolomics Study on the Effect of Vinegar Processing on the Chemical Changes and Antioxidant Activity of Angelica sinensis

Angelica sinensis (Oliv.) Diels (A. sinensis) has a long processing history. In order to obtain a more valuable composition and higher antioxidant behavior, it is often processed by stir-frying and vinegar treatment. However, the underlying mechanism of chemical changes remains ambiguous. Using UPLC-QQQ-MS/MS alongside targeted metabolomics techniques, this study probed the variances between crude and processed A. sinensis. We identified 1046 chemical components in total, 123 differential components in stir-fried A. sinensis, and 167 in vinegar-treated ones were screened through multivariate statistical analysis. Moreover, 83 significant compounds, encompassing amino acids, phenolic acids, etc., were identified across both processing methods. The in vitro antioxidant activities of these A. sinensis forms were assessed, revealing a positive correlation between most of the unique components emerging after processing and the antioxidant capabilities. Notably, post-processing, the chemical composition undergoes significant alterations, enhancing the antioxidant activity. Specific compounds, including 4-hydroxybenzaldehyde, syringetin-3-O-glucoside, and salicylic acid, greatly influence antioxidant activity during processing.

Rhododendron chrysanthum's Primary Metabolites Are Converted to Phenolics More Quickly When Exposed to UV-B Radiation

The plant defense system is immediately triggered by UV-B irradiation, particularly the production of metabolites and enzymes involved in the UV-B response. Although substantial research on UV-B-related molecular responses in Arabidopsis has been conducted, comparatively few studies have examined the precise consequences of direct UV-B treatment on R. chrysanthum. The ultra-high-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) methodology and TMT quantitative proteomics are used in this study to describe the metabolic response of R. chrysanthum to UV-B radiation and annotate the response mechanism of the primary metabolism and phenolic metabolism of R. chrysanthum. The outcomes demonstrated that following UV-B radiation, the primary metabolites (L-phenylalanine and D-lactose*) underwent considerable changes to varying degrees. This gives a solid theoretical foundation for investigating the use of precursor substances, such as phenylalanine, to aid plants in overcoming abiotic stressors. The external application of ABA produced a considerable increase in the phenolic content and improved the plants' resistance to UV-B damage. Our hypothesis is that externally applied ABA may work in concert with UV-B to facilitate the transformation of primary metabolites into phenolic compounds. This hypothesis offers a framework for investigating how ABA can increase a plant's phenolic content in order to help the plant withstand abiotic stressors. Overall, this study revealed alterations and mechanisms of primary and secondary metabolic strategies in response to UV-B radiation.

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.

Integrated Metabolome and Transcriptome Analysis of Petal Anthocyanin Accumulation Mechanism in Gloriosa superba 'Rothschildiana' during Different Flower Development Stages

Flower color is a key ornamental trait in plants. The petals of Gloriosa superba 'Rothschildiana' petals undergo a color transformation from yellow to red during their development, but the molecular mechanism of this process remains unexplored. This study examines the anthocyanin profiles and gene expression patterns of 'Rothschildiana' petals across four developmental stages: bud (S1), initial opening (S2), half opening (S3), and full opening stage (S4). A total of 59 anthocyanins were identified with significant increases in cyanidin-3,5-O-diglucoside, cyanidin-3-O-glucoside, pelargonidin-3-O-glucoside, and pelargonidin-3,5-O-diglucoside levels observed during petal maturation. Transcriptome analysis revealed 46 differentially expressed genes implicated in flavonoid and anthocyanin biosynthesis. Additionally, three gene modules were found to be associated with anthocyanin accumulation throughout flower development. Expression levels of genes associated with auxin, abscisic acid, brassinosteroid signaling, and transcription factors such as NACs and WRKYs underwent significant changes and exhibited strong correlations with several flavonoid and anthocyanin biosynthetic genes in these modules. These findings offer novel insights into the molecular underpinnings of flower color variation and lay the groundwork for the improvement of G. superba.

Rethinking underutilized cereal crops: pan-omics integration and green system biology

MAIN CONCLUSION

Due to harsh lifestyle changes, in the present era, nutritional security is needed along with food security so it is necessary to include underutilized cereal crops (UCCs) in our daily diet to counteract the rising danger of human metabolic illness. We can attain both the goal of zero hunger and nutritional security by developing improved UCCs using advanced pan-omics (genomics, transcriptomics, proteomics, metabolomics, nutrigenomics, phenomics and ionomics) practices. Plant sciences research progressed profoundly since the last few decades with the introduction of advanced technologies and approaches, addressing issues of food demand of the growing population, nutritional security challenges and climate change. However, throughout the expansion and popularization of commonly consumed major cereal crops such as wheat and rice, other cereal crops such as millet, rye, sorghum, and others were impeded, despite their potential medicinal and nutraceutical qualities. Undoubtedly neglected underutilized cereal crops (UCCs) also have the capability to withstand diverse climate change. To relieve the burden of major crops, it is necessary to introduce the new crops in our diet in the way of UCCs. Introgression of agronomically and nutritionally important traits by pan-omics approaches in UCCs could be a defining moment for the population's well-being on the globe. This review discusses the importance of underutilized cereal crops, as well as the application of contemporary omics techniques and advanced bioinformatics tools that could open up new avenues for future study and be valuable assets in the development and usage of UCCs in the perspective of green system biology. The increased and improved use of UCCs is dependent on number of factors that necessitate a concerted research effort in agricultural sciences. The emergence of functional genomics with molecular genetics might gear toward the reawakening of interest in underutilized cereals crops. The need of this era is to focus on potential UCCs in advanced agriculture and breeding programmes. Hence, targeting the UCCs, might provide a bright future for better health and scientific rationale for its use.

Metabolic pathways engineering for drought or/and heat tolerance in cereals

Drought (D) and heat (H) are the two major abiotic stresses hindering cereal crop growth and productivity, either singly or in combination (D/+H), by imposing various negative impacts on plant physiological and biochemical processes. Consequently, this decreases overall cereal crop production and impacts global food availability and human nutrition. To achieve global food and nutrition security vis-a-vis global climate change, deployment of new strategies for enhancing crop D/+H stress tolerance and higher nutritive value in cereals is imperative. This depends on first gaining a mechanistic understanding of the mechanisms underlying D/+H stress response. Meanwhile, functional genomics has revealed several stress-related genes that have been successfully used in target-gene approach to generate stress-tolerant cultivars and sustain crop productivity over the past decades. However, the fast-changing climate, coupled with the complexity and multigenic nature of D/+H tolerance suggest that single-gene/trait targeting may not suffice in improving such traits. Hence, in this review-cum-perspective, we advance that targeted multiple-gene or metabolic pathway manipulation could represent the most effective approach for improving D/+H stress tolerance. First, we highlight the impact of D/+H stress on cereal crops, and the elaborate plant physiological and molecular responses. We then discuss how key primary metabolism- and secondary metabolism-related metabolic pathways, including carbon metabolism, starch metabolism, phenylpropanoid biosynthesis, γ-aminobutyric acid (GABA) biosynthesis, and phytohormone biosynthesis and signaling can be modified using modern molecular biotechnology approaches such as CRISPR-Cas9 system and synthetic biology (Synbio) to enhance D/+H tolerance in cereal crops. Understandably, several bottlenecks hinder metabolic pathway modification, including those related to feedback regulation, gene functional annotation, complex crosstalk between pathways, and metabolomics data and spatiotemporal gene expressions analyses. Nonetheless, recent advances in molecular biotechnology, genome-editing, single-cell metabolomics, and data annotation and analysis approaches, when integrated, offer unprecedented opportunities for pathway engineering for enhancing crop D/+H stress tolerance and improved yield. Especially, Synbio-based strategies will accelerate the development of climate resilient and nutrient-dense cereals, critical for achieving global food security and combating malnutrition.

Approach strategies and application of metabolomics to biotechnology in plants

Metabolomics refers to the technology for the comprehensive analysis of metabolites and low-molecular-weight compounds in a biological system, such as cells or tissues. Metabolites play an important role in biological phenomena through their direct involvement in the regulation of physiological mechanisms, such as maintaining cell homeostasis or signal transmission through protein-protein interactions. The current review aims provide a framework for how the integrated analysis of metabolites, their functional actions and inherent biological information can be used to understand biological phenomena related to the regulation of metabolites and how this information can be applied to safety assessments of crops created using biotechnology. Advancement in technology and analytical instrumentation have led new ways to examine the convergence between biology and chemistry, which has yielded a deeper understanding of complex biological phenomena. Metabolomics can be utilized and applied to safety assessments of biotechnology products through a systematic approach using metabolite-level data processing algorithms, statistical techniques, and database development. The integration of metabolomics data with sequencing data is a key step towards improving additional phenotypical evidence to elucidate the degree of environmental affects for variants found in genome associated with metabolic processes. Moreover, information analysis technology such as big data, machine learning, and IT investment must be introduced to establish a system for data extraction, selection, and metabolomic data analysis for the interpretation of biological implications of biotechnology innovations. This review outlines the integrity of metabolomics assessments in determining the consequences of genetic engineering and biotechnology in plants.

PlantMetSuite: A User-Friendly Web-Based Tool for Metabolomics Analysis and Visualisation

The advancement of mass spectrometry technologies has revolutionised plant metabolomics research by enabling the acquisition of raw metabolomics data. However, the identification, analysis, and visualisation of these data require specialised tools. Existing solutions lack a dedicated plant-specific metabolite database and pose usability challenges. To address these limitations, we developed PlantMetSuite, a web-based tool for comprehensive metabolomics analysis and visualisation. PlantMetSuite encompasses interactive bioinformatics tools and databases specifically tailored to plant metabolomics data, facilitating upstream-to-downstream analysis in metabolomics and supporting integrative multi-omics investigations. PlantMetSuite can be accessed directly through a user's browser without the need for installation or programming skills. The tool is freely available and will undergo regular updates and expansions to incorporate additional libraries and newly published metabolomics analysis methods. The tool's significance lies in empowering researchers with an accessible and customisable platform for unlocking plant metabolomics insights.

Intra- and Interspecies Differences of Two Cecropia Species from Tabasco, Mexico, Determined through the Metabolic Analysis and 1H-NMR-Based Fingerprinting of Hydroalcoholic Extracts

The genus Cecropia is used in the traditional medicine of Tabasco, Mexico, in diabetes and hypertension treatments, mainly without distinction of the species. This contribution aimed to carry out the metabolic analysis and Proton Nuclear Magnetic Resonance (¹H-NMR) spectroscopy-based fingerprinting of the hydroalcoholic leaf extracts of Cecropia peltata (Cp) and Cecropia obtusifolia (Co) collected in five sub-regions of the State of Tabasco (Cp1, "Centro"; Cp2, "Chontalpa"; Cp3, "Pantanos"; Cp4, "Ríos" and Co5, "Sierra"). Firstly, the extracts were evaluated for their Total Phenol Content (TPC) and Total Flavonoid Content (TFC) by spectrophotometric methods. In addition, metabolic analysis was performed using High-Performance Liquid Chromatography with Diode-Array Detection HPLC-DAD, which allowed the quantification of the chemical markers: chlorogenic acid, isoorientin, and orientin, as well as a vitexin analog. Finally, metabolomic analysis was carried out based on the ¹H-NMR spectra. The Cp4 extract (C. peltata from the "Ríos" sub-region) presented the highest values of TPC (155 ± 9.1 mg GAE/g E) and TFC (724 ± 22.2 mg RE/g E). The metabolic analysis was similar among the five samples; the highest concentrations of the four chemical markers were found in Cp3 (C. peltata from the "Pantanos" sub-region) for chlorogenic acid (39.8 ± 2.3 mg/g) and isoorientin (51.5 ± 2.9 mg/g), in Cp4 for orientin (49.9 ± 0.6 mg/g), and in Cp2 (C. peltata from the "Chontalpa" sub-region) for the vitexin analog (6.2 ± 0.2 mg/g). The metabolic analysis and the ¹H-NMR fingerprint analysis showed intraspecies differences among the C. peltata samples and interspecies between C. peltata and C. obtusifolia, which were attributed to variations in the metabolite groups as well as in the proportion of sugars such as glucose and xylose.

Comprehensive mechanisms of heavy metal toxicity in plants, detoxification, and remediation

Natural and anthropogenic causes are continually growing sources of metals in the ecosystem; hence, heavy metal (HM) accumulation has become a primary environmental concern. HM contamination poses a serious threat to plants. A major focus of global research has been to develop cost-effective and proficient phytoremediation technologies to rehabilitate HM-contaminated soil. In this regard, there is a need for insights into the mechanisms associated with the accumulation and tolerance of HMs in plants. It has been recently suggested that plant root architecture has a critical role in the processes that determine sensitivity or tolerance to HMs stress. Several plant species, including those from aquatic habitats, are considered good hyperaccumulators for HM cleanup. Several transporters, such as the ABC transporter family, NRAMP, HMA, and metal tolerance proteins, are involved in the metal acquisition mechanisms. Omics tools have shown that HM stress regulates several genes, stress metabolites or small molecules, microRNAs, and phytohormones to promote tolerance to HM stress and for efficient regulation of metabolic pathways for survival. This review presents a mechanistic view of HM uptake, translocation, and detoxification. Sustainable plant-based solutions may provide essential and economical means of mitigating HM toxicity.

Data Science and Plant Metabolomics

The study of plant metabolism is one of the most complex tasks, mainly due to the huge amount and structural diversity of metabolites, as well as the fact that they react to changes in the environment and ultimately influence each other. Metabolic profiling is most often carried out using tools that include mass spectrometry (MS), which is one of the most powerful analytical methods. All this means that even when analyzing a single sample, we can obtain thousands of data. Data science has the potential to revolutionize our understanding of plant metabolism. This review demonstrates that machine learning, network analysis, and statistical modeling are some techniques being used to analyze large quantities of complex data that provide insights into plant development, growth, and how they interact with their environment. These findings could be key to improving crop yields, developing new forms of plant biotechnology, and understanding the relationship between plants and microbes. It is also necessary to consider the constraints that come with data science such as quality and availability of data, model complexity, and the need for deep knowledge of the subject in order to achieve reliable outcomes.

Plant Metabolomics: An Overview of the Role of Primary and Secondary Metabolites against Different Environmental Stress Factors

Several environmental stresses, including biotic and abiotic factors, adversely affect the growth and development of crops, thereby lowering their yield. However, abiotic factors, e.g., drought, salinity, cold, heat, ultraviolet radiations (UVr), reactive oxygen species (ROS), trace metals (TM), and soil pH, are extremely destructive and decrease crop yield worldwide. It is expected that more than 50% of crop production losses are due to abiotic stresses. Moreover, these factors are responsible for physiological and biochemical changes in plants. The response of different plant species to such stresses is a complex phenomenon with individual features for several species. In addition, it has been shown that abiotic factors stimulate multi-gene responses by making modifications in the accumulation of the primary and secondary metabolites. Metabolomics is a promising way to interpret biotic and abiotic stress tolerance in plants. The study of metabolic profiling revealed different types of metabolites, e.g., amino acids, carbohydrates, phenols, polyamines, terpenes, etc, which are accumulated in plants. Among all, primary metabolites, such as amino acids, carbohydrates, lipids polyamines, and glycine betaine, are considered the major contributing factors that work as osmolytes and osmoprotectants for plants from various environmental stress factors. In contrast, plant-derived secondary metabolites, e.g., phenolics, terpenoids, and nitrogen-containing compounds (alkaloids), have no direct role in the growth and development of plants. Nevertheless, such metabolites could play a significant role as a defense by protecting plants from biotic factors such as herbivores, insects, and pathogens. In addition, they can enhance the resistance against abiotic factors. Therefore, metabolomics practices are becoming essential and influential in plants by identifying different phytochemicals that are part of the acclimation responses to various stimuli. Hence, an accurate metabolome analysis is important to understand the basics of stress physiology and biochemistry. This review provides insight into the current information related to the impact of biotic and abiotic factors on variations of various sets of metabolite levels and explores how primary and secondary metabolites help plants in response to these stresses.

Genetic and Metabolite Variability among Commercial Varieties and Advanced Lines of Vicia faba L

Vicia faba L. (faba bean) is one of the most promising pulse crops due to its nutritional value and high nitrogen fixation capacity. The aim of the present study was to compare the genetic diversity and the seed metabolite profiles of five genetic materials of faba bean. Specifically, three newly developed advanced lines (KK18, KK14 and KK10) and two commercial cultivars (POLIKARPI and TANAGRA), were evaluated for this purpose. Genetic diversity among populations was assessed by SCoT molecular markers. Through UPGMA dendrogram, genetic distances between populations were estimated. Untargeted metabolomics analysis of the seeds was performed employing GC/EI/MS. The cultivar POLYKARPI exhibited the highest polymorphism. All varieties showed a higher within-cultivars and advanced lines variability than between. POLYKARPI and KK14 had the lowest genetic distances, while KK18 and TANAGRA presented the highest ones. The advanced line KK18 displayed the best nutritional profile, the highest concentration of desirable metabolites (lactic acid and trehalose), the lowest concentration of anti-nutritional factors (oxalic acid) and the lowest concentration of saturated fatty acids (palmitic and stearic acid). According to the results of the present study, KK18 line is a very promising material for further exploration and utilization in breeding programs.

Metabolomics-centered mining of plant metabolic diversity and function: Past decade and future perspectives

Plants are natural experts in organic synthesis, being able to generate large numbers of specific metabolites with widely varying structures that help them adapt to variable survival challenges. Metabolomics is a research discipline that integrates the capabilities of several types of research including analytical chemistry, statistics, and biochemistry. Its ongoing development provides strategies for gaining a systematic understanding of quantitative changes in the levels of metabolites. Metabolomics is usually performed by targeting either a specific cell, a specific tissue, or the entire organism. Considerable advances in science and technology over the last three decades have propelled us into the era of multi-omics, in which metabolomics, despite at an earlier developmental stage than genomics, transcriptomics, and proteomics, offers the distinct advantage of studying the cellular entities that have the greatest influence on end phenotype. Here, we summarize the state of the art of metabolite detection and identification, and illustrate these techniques with four case study applications: (i) comparing metabolite composition within and between species, (ii) assessing spatio-temporal metabolic changes during plant development, (iii) mining characteristic metabolites of plants in different ecological environments and upon exposure to various stresses, and (iv) assessing the performance of metabolomics as a means of functional gene identification , metabolic pathway elucidation, and metabolomics-assisted breeding through analyzing plant populations with diverse genetic variations. In addition, we highlight the prominent contributions of joint analyses of plant metabolomics and other omics datasets, including those from genomics, transcriptomics, proteomics, epigenomics, phenomics, microbiomes, and ion-omics studies. Finally, we discuss future directions and challenges exploiting metabolomics-centered approaches in understanding plant metabolic diversity.

Tool and techniques study to plant microbiome current understanding and future needs: an overview

Microorganisms are present in the universe and they play role in beneficial and harmful to human life, society, and environments. Plant microbiome is a broad term in which microbes are present in the rhizo, phyllo, or endophytic region and play several beneficial and harmful roles with the plant. To know of these microorganisms, it is essential to be able to isolate purification and identify them quickly under laboratory conditions. So, to improve the microbial study, several tools and techniques such as microscopy, rRNA, or rDNA sequencing, fingerprinting, probing, clone libraries, chips, and metagenomics have been developed. The major benefits of these techniques are the identification of microbial community through direct analysis as well as it can apply in situ. Without tools and techniques, we cannot understand the roles of microbiomes. This review explains the tools and their roles in the understanding of microbiomes and their ecological diversity in environments.

Multi-omics revolution to promote plant breeding efficiency

Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.

Integrated Metabolomics and Network Pharmacology to Decipher the Latent Mechanisms of Protopanaxatriol against Acetic Acid-Induced Gastric Ulcer

Gastric ulcer (GU) is a peptic disease with high morbidity and mortality rates affecting approximately 4% of the population throughout the world. Current therapies for GU are limited by the high relapse incidence and side effects. Therefore, novel effective antiulcer drugs are urgently needed. Ginsenosides have shown good anti-GU effects, and the major intestinal bacterial metabolite of ginsenosides, protopanaxatriol (PPT), is believed to be the active component. In this study, we evaluated the anti-GU effect of PPT in rats in an acetic acid-induced GU model. High (H-PPT) and medium (M-PPT) doses of PPT (20.0 and 10.0 mg/mg/day) significantly reduced the ulcer area and the ET-1, IL-6, EGF, SOD, MDA and TNF-α levels in serum were regulated by PPT in a dose-dependent manner. We also investigated the mechanisms of anti-GU activity of PPT based on metabolomics coupled with network pharmacology strategy. The result was that 16 biomarkers, 3 targets and 3 metabolomic pathways were identified as playing a vital role in the treatment of GU with PPT and were further validated by molecular docking. In this study, we have demonstrated that the integrated analysis of metabolomics and network pharmacology is an effective strategy for deciphering the complicated mechanisms of natural compounds.

Metabolomics-Driven Mining of Metabolite Resources: Applications and Prospects for Improving Vegetable Crops

Vegetable crops possess a prominent nutri-metabolite pool that not only contributes to the crop performance in the fields, but also offers nutritional security for humans. In the pursuit of identifying, quantifying and functionally characterizing the cellular metabolome pool, biomolecule separation technologies, data acquisition platforms, chemical libraries, bioinformatics tools, databases and visualization techniques have come to play significant role. High-throughput metabolomics unravels structurally diverse nutrition-rich metabolites and their entangled interactions in vegetable plants. It has helped to link identified phytometabolites with unique phenotypic traits, nutri-functional characters, defense mechanisms and crop productivity. In this study, we explore mining diverse metabolites, localizing cellular metabolic pathways, classifying functional biomolecules and establishing linkages between metabolic fluxes and genomic regulations, using comprehensive metabolomics deciphers of the plant’s performance in the environment. We discuss exemplary reports covering the implications of metabolomics, addressing metabolic changes in vegetable plants during crop domestication, stage-dependent growth, fruit development, nutri-metabolic capabilities, climatic impacts, plant-microbe-pest interactions and anthropogenic activities. Efforts leading to identify biomarker metabolites, candidate proteins and the genes responsible for plant health, defense mechanisms and nutri-rich crop produce are documented. With the insights on metabolite-QTL (mQTL) driven genetic architecture, molecular breeding in vegetable crops can be revolutionized for developing better nutritional capabilities, improved tolerance against diseases/pests and enhanced climate resilience in plants.

Mass Spectrometry-Based Nontargeted and Targeted Analytical Approaches in Fingerprinting and Metabolomics of Food and Agricultural Research

Mass spectrometry (MS)-based techniques have been extensively applied in food and agricultural research. This review aims to address the advances and applications of MS-based analytical strategies in nontargeted and targeted analysis and summarizes the recent publications of MS-based techniques, including flow injection MS fingerprinting, chromatography-tandem MS metabolomics, direct analysis using ambient mass spectrometry, as well as development in MS data deconvolution software packages and databases for metabolomic studies. Various nontargeted and targeted approaches are employed in marker compounds identification, material adulteration detection, and the analysis of specific classes of secondary metabolites. In the newly emerged applications, the recent advances in computer tools for the fast deconvolution of MS data in targeted secondary metabolite analysis are highlighted.

Differential sensitivity of metabolic pathways in sugar beet roots to combined salt, heat, and light stress

Plants in nature commonly encounter combined stress scenarios. The response to combined stressors is often unpredictable from the response to single stresses. To address stress interference in roots, we applied salinity, heat, and high light to hydroponically grown sugar beet. Two main patterns of metabolomic acclimation were apparent. High salt of 300 mM NaCl considerably lowered metabolite amounts, for example, those of most amino acids, γ-amino butyric acid (GABA), and glucose. Very few metabolites revealed the opposite trend with increased contents at high salts, mostly organic acids such as citric acid and isocitric acid, but also tryptophan, tyrosine, and the compatible solute proline. High temperature (31°C vs. 21°C) also frequently lowered root metabolite pools. The individual effects of salinity and heat were superimposed under combined stress. Under high light and high salt conditions, there was a significant decline in root chloride, mannitol, ribulose 5-P, cysteine, and l-aspartate contents. The results reveal the complex interaction pattern of environmental parameters and urge researchers to elaborate in much more detail and width on combinatorial stress effects to bridge work under controlled growth conditions to growth in nature, and also to better understand acclimation to the consequences of climate change.

Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype–phenotype (genotype–LIPIDOTYPE–phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP).

Effects of exogenous selenium application on nutritional quality and metabolomic characteristics of mung bean (Vigna radiata L.)

Selenium (Se) biofortification is an important strategy for reducing hidden hunger by increasing the nutritional quality of crops. However, there is limited metabolomic information on the nutritional quality of Se-enriched mung beans. In this study, physiological assays and LC-MS/MS based widely targeted metabolomics approach was employed to reveal the Se biofortification potential of mung bean by evaluating the effect of Se on mung bean nutraceutical compounds and their qualitative parameters. Physiological data showed that foliar application of 30 g ha^-1 Se at key growth stages significantly increased the content of Se, protein, fat, total phenols, and total flavonoids content in two mung bean varieties. Widely targeted metabolomics identified 1,080 metabolites, among which L-Alanyl-L-leucine, 9,10-Dihydroxy-12,13-epoxyoctadecanoic acid, and 1-caffeoylquinic acid could serve as biomarkers for identifying highly nutritious mung bean varieties. Pathway enrichment analysis revealed that the metabolic pathways of different metabolites were different in the Se-enriched mung bean. Specifically, P1 was mainly enriched in the linoleic acid metabolic pathway, while P2 was mainly enriched in the phosphonate and phosphinate metabolic pathways. Overall, these results revealed the specific Se enrichment mechanism of different mung bean varieties. This study provides new insights into the comprehensive improvement of the nutritional quality of mung beans.

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.

Improving Drought Stress Tolerance in Ramie (Boehmeria nivea L.) Using Molecular Techniques

Ramie is one of the most significant fiber crops and contributes to good quality fiber. Drought stress (DS) is one of the most devastating abiotic factors which is accountable for a substantial loss in crop growth and production and disturbing sustainable crop production. DS impairs growth, plant water relation, and nutrient uptake. Ramie has evolved a series of defense responses to cope with DS. There are numerous genes regulating the drought tolerance (DT) mechanism in ramie. The morphological and physiological mechanism of DT is well-studied; however, modified methods would be more effective. The use of novel genome editing tools like clustered regularly interspaced short palindromic repeats (CRISPR) is being used to edit the recessive genes in crops to modify their function. The transgenic approaches are used to develop several drought-tolerant varieties in ramie, and further identification of tolerant genes is needed for an effective breeding plan. Quantitative trait loci (QTLs) mapping, transcription factors (TFs) and speed breeding are highly studied techniques, and these would lead to the development of drought-resilient ramie cultivars. The use of hormones in enhancing crop growth and development under water scarcity circumstances is critical; however, using different concentrations and testing genotypes in changing environments would be helpful to sort the tolerant genotypes. Since plants use various ways to counter DS, investigating mechanisms of DT in plants will lead to improved DT in ramie. This critical review summarized the recent advancements on DT in ramie using novel molecular techniques. This information would help ramie breeders to conduct research studies and develop drought tolerant ramie cultivars.

Heat Stress During Gametogenesis Irreversibly Damages Female Reproductive Organ in Rice

Heat stress during gametogenesis leads to spikelet sterility. To ascertain the role of female reproductive organ (pistil), two rice genotypes N22 and IR64 with contrasting heat stress responses were exposed to control (30 °C) and heat stress (38 °C and 40 °C) during megasporogenesis. Anatomical observations of ovule revealed greater disappearance of megaspore mother cell and nuclei at early stages, and during later stages mature embryo sac without female germ unit, improper positioning of nuclei, and shrunken embryo sac was observed in the sensitive IR64. Under heat stress, a decrease in sugar and starch, increase in H₂O₂ and malondialdehyde with lower antioxidant enzyme activities were recorded in pistils of both N22 and IR64. Lower accumulation of TCA cycle metabolites and amino acids were noticed in IR64 pistils under heat stress at gametogenesis, whereas N22 exhibited favorable metabolite profiles. At heading, however, N22 pistils had higher carbohydrate accumulation and better ROS homeostasis, suggesting higher recovery after heat stress exposure. In summary, the results indicate that heat stress during megasporogenesis leads to irreversible anatomical and physiological changes in pistil and alters metabolic signatures leading to increased spikelet sterility in rice. Mechanisms identified for enhanced heat tolerance in pistil can help in developing rice varieties that are better adapted to future hotter climate.

Advances in Plant Metabolomics and Its Applications in Stress and Single-Cell Biology

In the past two decades, the post-genomic era envisaged high-throughput technologies, resulting in more species with available genome sequences. In-depth multi-omics approaches have evolved to integrate cellular processes at various levels into a systems biology knowledge base. Metabolomics plays a crucial role in molecular networking to bridge the gaps between genotypes and phenotypes. However, the greater complexity of metabolites with diverse chemical and physical properties has limited the advances in plant metabolomics. For several years, applications of liquid/gas chromatography (LC/GC)-mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been constantly developed. Recently, ion mobility spectrometry (IMS)-MS has shown utility in resolving isomeric and isobaric metabolites. Both MS and NMR combined metabolomics significantly increased the identification and quantification of metabolites in an untargeted and targeted manner. Thus, hyphenated metabolomics tools will narrow the gap between the number of metabolite features and the identified metabolites. Metabolites change in response to environmental conditions, including biotic and abiotic stress factors. The spatial distribution of metabolites across different organs, tissues, cells and cellular compartments is a trending research area in metabolomics. Herein, we review recent technological advancements in metabolomics and their applications in understanding plant stress biology and different levels of spatial organization. In addition, we discuss the opportunities and challenges in multiple stress interactions, multi-omics, and single-cell metabolomics.

Advances in Metabolomics-Driven Diagnostic Breeding and Crop Improvement

Climate change continues to threaten global crop output by reducing annual productivity. As a result, global food security is now considered as one of the most important challenges facing humanity. To address this challenge, modern crop breeding approaches are required to create plants that can cope with increased abiotic/biotic stress. Metabolomics is rapidly gaining traction in plant breeding by predicting the metabolic marker for plant performance under a stressful environment and has emerged as a powerful tool for guiding crop improvement. The advent of more sensitive, automated, and high-throughput analytical tools combined with advanced bioinformatics and other omics techniques has laid the foundation to broadly characterize the genetic traits for crop improvement. Progress in metabolomics allows scientists to rapidly map specific metabolites to the genes that encode their metabolic pathways and offer plant scientists an excellent opportunity to fully explore and rationally harness the wealth of metabolites that plants biosynthesize. Here, we outline the current application of advanced metabolomics tools integrated with other OMICS techniques that can be used to: dissect the details of plant genotype–metabolite–phenotype interactions facilitating metabolomics-assisted plant breeding for probing the stress-responsive metabolic markers, explore the hidden metabolic networks associated with abiotic/biotic stress resistance, facilitate screening and selection of climate-smart crops at the metabolite level, and enable accurate risk-assessment and characterization of gene edited/transgenic plants to assist the regulatory process. The basic concept behind metabolic editing is to identify specific genes that govern the crucial metabolic pathways followed by the editing of one or more genes associated with those pathways. Thus, metabolomics provides a superb platform for not only rapid assessment and commercialization of future genome-edited crops, but also for accelerated metabolomics-assisted plant breeding. Furthermore, metabolomics can be a useful tool to expedite the crop research if integrated with speed breeding in future.

Increase Crop Resilience to Heat Stress Using Omic Strategies

Varieties of various crops with high resilience are urgently needed to feed the increased population in climate change conditions. Human activities and climate change have led to frequent and strong weather fluctuation, which cause various abiotic stresses to crops. The understanding of crops' responses to abiotic stresses in different aspects including genes, RNAs, proteins, metabolites, and phenotypes can facilitate crop breeding. Using multi-omics methods, mainly genomics, transcriptomics, proteomics, metabolomics, and phenomics, to study crops' responses to abiotic stresses will generate a better, deeper, and more comprehensive understanding. More importantly, multi-omics can provide multiple layers of information on biological data to understand plant biology, which will open windows for new opportunities to improve crop resilience and tolerance. However, the opportunities and challenges coexist. Interpretation of the multidimensional data from multi-omics and translation of the data into biological meaningful context remained a challenge. More reasonable experimental designs starting from sowing seed, cultivating the plant, and collecting and extracting samples were necessary for a multi-omics study as the first step. The normalization, transformation, and scaling of single-omics data should consider the integration of multi-omics. This review reports the current study of crops at abiotic stresses in particular heat stress using omics, which will help to accelerate crop improvement to better tolerate and adapt to climate change.

Differential Metabolic Responses of Lettuce Grown in Soil, Substrate and Hydroponic Cultivation Systems under NH4+/NO3- Application

Nitrogen (N) is an essential element for plant growth and development. The application of a balanced and optimal amount of N is required for sustainable plant yield. For this, different N sources and forms are used, that including ammonium (NH4+) and nitrate (NO3-). These are the main sources for N uptake by plants where NH4+/NO3- ratios have a significant effect on the biomass, quality and metabolites composition of lettuce grown in soil, substrate and hydroponic cultivation systems. A limited supply of N resulted in the reduction in the biomass, quality and overall yield of lettuce. Additionally, different types of metabolites were produced with varying concentrations of N sources and can be used as metabolic markers to improve the N use efficiency. To investigate the differential metabolic activity, we planted lettuce with different NH4+/NO3- ratios (100:0, 75:25, 50:50, 25:75 and 0:100%) and a control (no additional N applied) in soil, substrate and hydroponic cultivation systems. The results revealed that the 25% NH4+/75% NO3- ratio increased the relative chlorophyll contents as well as the biomass of lettuce in all cultivation systems. However, lettuce grown in the hydroponic cultivation system showed the best results. The concentration of essential amino acids including alanine, valine, leucine, lysine, proline and serine increased in soil and hydroponically grown lettuce treated with the 25% NH4+/75% NO3- ratio. The taste and quality-related compounds in lettuce showed maximum relative abundance with the 25% NH4+/75% NO3- ratio, except ascorbate (grown in soil) and lactupicrin (grown in substrate), which showed maximum relative abundance in the 50% NH4+/50% NO3- ratio and control treatments, respectively. Moreover, 1-O-caffeoylglucose, 1,3-dicaffeoylquinic acid, aesculetin and quercetin-3-galactoside were increased by the application of the 100% NH4+/0% NO3- ratio in soil-grown lettuce. The 25% NH4+/75% NO3- ratio was more suitable in the hydroponic cultivation system to obtain increased lettuce biomass. The metabolic profiling of lettuce showed different behaviors when applying different NH4+/NO3- ratios. Therefore, the majority of the parameters were largely influenced by the 25% NH4+/75% NO3- ratio, which resulted in the hyper-accumulation of health-promoting compounds in lettuce. In conclusion, the optimal N applications improve the quality of lettuce grown in soil, substrate and hydroponic cultivation systems which ultimately boost the nutritional value of lettuce.

Metabolite profiling and protein quantification to a large library of 96 horsegram (Macrotyloma uniflorum) germplasm

The present study was framed for the assessment of metabolic diversity of 96 diverse horsegram lines derived from 700 germplasm accessions of Pan India. The nutritional component of horsegram germplasm was studied using nuclear magnetic resonance spectroscopy (¹H NMR) and micro-Kjeldal method. Differential range of protein content was found 13–40% in the selected panel. The related wild species Macrotyloma sar-gharwalensis contained highest protein content (40%), and the lowest protein content (13%) was found in IC-120837 and TCR-1439. Seed based ¹H NMR spectroscopy of horsegram discovered 45 different metabolites (17 amino acids, 7 flavonoids, 10 organic acids/phenolic acids/sugar alcohols/steroids, 7 carbohydrades/sugars, and 4 vitamins). The number of total metabolites quantified among diverse horsegram panel ranged from 25–44. The lowest metabolites number was 26 in PLKU-38, while, IC-280031 and IC-139356 lines showed the presence of highest number of metabolites (44). Lines IC-280031 and IC-139356 were found most nutritive amongst selected panel of horsegram germplasm by containing maximum number of quantifiable metabolites during ¹H NMR spectroscopy study. Further, the NMR based data of 96 germplasms was subjected for statistical analysis (PCA, Matrix plot, stacked charts) that revealed the similarities and variations among the whole germplasm. The methionine, sucrose, maltose, riboflavin and myricetin were observed as differential chemo-markers that help to differentiate the horsegram lines of selected panel. This information will further aid in the selection of nutritionally efficient cultivars for proteomics and genomics studies and these lines can be used as nutraceutical food for the prevention of various health ailments including kidney stone.

Vitamin D Deficiency in Women with Breast Cancer: A Correlation with Osteoporosis? A Machine Learning Approach with Multiple Factor Analysis

Breast cancer (BC) is the most frequent malignant tumor in women in Europe and North America, and the use of aromatase inhibitors (AIs) is recommended in women affected by estrogen receptor-positive BCs. AIs, by inhibiting the enzyme that converts androgens into estrogen, cause a decrement in bone mineral density (BMD), with a consequent increased risk of fragility fractures. This study aimed to evaluate the role of vitamin D3 deficiency in women with breast cancer and its correlation with osteoporosis and BMD modifications. This observational cross-sectional study collected the following data regarding bone health: osteoporosis and osteopenia diagnosis, lumbar spine (LS) and femoral neck bone mineral density (BMD), serum levels of 25-hydroxyvitamin D3 (25(OH)D3), calcium and parathyroid hormone. The study included 54 women with BC, mean age 67.3 ± 8.16 years. Given a significantly low correlation with the LS BMD value (r2 = 0.30, p = 0.025), we assessed the role of vitamin D3 via multiple factor analysis and found that BMD and vitamin D3 contributed to the arrangement of clusters, reported as vectors, providing similar trajectories of influence to the construction of the machine learning model. Thus, in a cohort of women with BC undergoing Ais, we identified a very low prevalence (5.6%) of patients with adequate bone health and a normal vitamin D3 status. According to our cluster model, we may conclude that the assessment and management of bone health and vitamin D3 status are crucial in BC survivors.

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.

Molecular Insights into Freezing Stress in Peach Based on Multi-Omics and Biotechnology: An Overview

In nature or field conditions, plants are frequently exposed to diverse environmental stressors. Among abiotic stresses, the low temperature of freezing conditions is a critical factor that influences plants, including horticultural crops, decreasing their growth, development, and eventually quality and productivity. Fortunately, plants have developed a mechanism to improve the tolerance to freezing during exposure to a range of low temperatures. In this present review, current findings on freezing stress physiology and genetics in peach (Prunus persica) were refined with an emphasis on adaptive mechanisms for cold acclimation, deacclimation, and reacclimation. In addition, advancements using multi-omics and genetic engineering approaches unravel the molecular physiological mechanisms, including hormonal regulations and their general perceptions of freezing tolerance in peach were comprehensively described. This review might pave the way for future research to the horticulturalists and research scientists to overcome the challenges of freezing temperature and improvement of crop management in these conditions.

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.

Recent applications of metabolomics in plant breeding

Metabolites play a central role in maintaining organismal life and in defining crop phenotypes, such as nutritional value, fragrance, color, and stress resistance. Among the 'omes' in biology, the metabolome is the closest to the phenotype. Consequently, metabolomics has been applied to crop improvement as method for monitoring changes in chemical compositions, clarifying the mechanisms underlying cellular functions, discovering markers and diagnostics, and phenotyping for mQTL, mGWAS, and metabolite-genome predictions. In this review, 359 reports of the most recent applications of metabolomics to plant breeding-related studies were examined. In addition to the major crops, more than 160 other crops including rare medicinal plants were considered. One bottleneck associated with using metabolomics is the wide array of instruments that are used to obtain data and the ambiguity associated with metabolite identification and quantification. To further the application of metabolomics to plant breeding, the features and perspectives of the technology are discussed.

Comparative metabolomics study of Tartary (Fagopyrum tataricum (L.) Gaertn) and common (Fagopyrum esculentum Moench) buckwheat seeds

Tartary buckwheat has higher health-promoting value than common buckwheat. However, the related metabolites information except flavonoids is largely deficient. Here, we compared the seed metabolomes of the two species using a UHPLC-QqQ-MS-based metabolomics approach. In total, 722 metabolites were obtained, of which 84 and 78 were identified as the key active ingredients of Traditional Chinese Medicines and the active pharmaceutical ingredients for six major diseases-resistance, respectively. Comparative analysis showed there were obviously difference in metabolic profiles between the two buckwheat species, and further found 61 flavonoids and 94 non-flavonoids metabolites displayed significantly higher contents (≥2 fold) in Tartary buckwheat than in common buckwheat. Our results suggest that Tartary and common buckwheat seeds are rich in metabolites beneficial to human health, and non-flavonoids metabolites also contributed to Tartary buckwheat's higher health-promoting value than common buckwheat. This study provides valuable information for the development of new functional foods of Tartary buckwheat.

Metabolomics: a systems biology approach for enhancing heat stress tolerance in plants

Comprehensive metabolomic investigations provide a large set of stress-related metabolites and metabolic pathways, advancing crops under heat stress conditions. Metabolomics-assisted breeding, including mQTL and mGWAS boosted our understanding of improving numerous quantitative traits under heat stress. During the past decade, metabolomics has emerged as a fascinating scientific field that includes documentation, evaluation of metabolites, and chemical methods for cell monitoring programs in numerous plant species. A comprehensive metabolome profiling allowed the investigator to handle the comprehensive data groups of metabolites and the equivalent metabolic pathways in an extraordinary manner. Metabolomics, together with transcriptomics, plays an influential role in discovering connections between stress and genes/metabolite, phenotyping, and biomarkers documentation. Further, it helps to decode several metabolic systems connected with heat stress (HS) tolerance in plants. Heat stress is a critical environmental factor that is globally affecting the growth and productivity of plants. Thus, there is an urgent need to exploit modern breeding and biotechnological tools like metabolomics to develop cultivars with improved HS tolerance. Several studies have reported that amino acids, carbohydrates, nitrogen metabolisms, etc. and metabolites involved in the biosynthesis and catalyzing actions play a game-changing role in HS response and help plants to cope with the HS. The use of metabolomics-assisted breeding (MAB) allows a well-organized transmission of higher yield and HS tolerance at the metabolome level with specific properties. Progressive metabolomics systematic techniques have accelerated metabolic profiling. Nonetheless, continuous developments in bioinformatics, statistical tools, and databases are allowing us to produce ever-progressing, comprehensive insights into the biochemical configuration of plants and by what means this is inclined by genetic and environmental cues. Currently, assimilating metabolomics with post-genomic platforms has allowed a significant division of genetic-phenotypic connotation in several plant species. This review highlights the potential of a state-of-the-art plant metabolomics approach for the improvement of crops under HS. The development of plants with specific properties using integrated omics (metabolomics and transcriptomics) and MAB can provide new directions for future research to enhance HS tolerance in plants to achieve a goal of "zero hunger".

LC-MS metabolomics analysis of Stevia rebaudiana Bertoni leaves cultivated in Malaysia in relation to different developmental stages

INTRODUCTION

Stevia is known for its sweet taste, attributed to the presence of steviol glycosides. Although reports on the dynamic changes of steviol glycosides during development of stevia are available, the data are mainly focused on stevioside and rebaudioside A. Information concerning the comprehensive metabolite profile of stevia in relation to different developmental stages is still lacking.

OBJECTIVE

This study investigated the metabolite changes along the developmental stages of a local stevia cultivar.

METHODOLOGY

Stevia leaves were harvested at 4 different developmental stages (early vegetative, late vegetative, budding, and flowering). Samples were then subjected to LC-MS metabolomics analysis to determine the metabolite variations.

RESULTS

A total of 55 metabolites, comprising phenolic acids, flavonoids, and terpenoids were identified by MS/MS analysis of the stevia leaf extracts, revealing a metabolite profile which was comparatively similar with those of cultivars grown in other countries. PLS-DA differentiated the early vegetative stage stevia leaf samples from those of the later stages by higher content of phenolic acids. The leaf metabolomes of the later 3 stages (late vegetative, budding, and flowering) were collectively richer in flavonoids. Meanwhile, the content of steviol glycosides is highest during the late vegetative and budding stages.

CONCLUSION

The present study provided, for the first time, a general overview of the metabolite variations with regard to the different developmental stages of stevia. The information may facilitate decision making of suitable harvesting times for higher yields of steviol glycosides or a more balanced metabolite profile in terms of pharmacologically useful metabolites.