Sample preparation for plant metabolomics

Responses of leaf gas exchange and metabolites to drought stress in different organs of sugarcane and its closely related species Erianthus arundinaceus

MAIN CONCLUSION

The high intrinsic water-use efficiency of Erianthus may be due to the low abaxial stomatal density and the accumulation of leaf metabolites such as betaine and gamma-aminobutyric acid. Sugarcane is an important crop that is widely cultivated in tropical and subtropical regions of the world. Because drought is among the main impediments limiting sugarcane production in these regions, breeding of drought-tolerant sugarcane varieties is important for sustainable production. Erianthus arundinaceus, a species closely related to sugarcane, exhibits high intrinsic water-use efficiency (iWUE), the underlying mechanisms for which remain unknown. To improve the genetic base for conferring drought tolerance in sugarcane, in the present study, we performed a comprehensive comparative analysis of leaf gas exchange and metabolites in different organs of sugarcane and Erianthus under wet and dry soil-moisture conditions. Erianthus exhibited lower stomatal conductance under both conditions, which resulted in a higher iWUE than in sugarcane. Organ-specific metabolites showed gradations between continuous parts and organs, suggesting linkages between them. Cluster analysis of organ-specific metabolites revealed the effects of the species and treatments in the leaves. Principal component analysis of leaf metabolites confirmed a rough ordering of the factors affecting their accumulations. Compared to sugarcane leaf, Erianthus leaf accumulated more raffinose, betaine, glutamine, gamma-aminobutyric acid, and S-adenosylmethionine, which function as osmolytes and stress-response compounds, under both the conditions. Our extensive analyses reveal that the high iWUE of Erianthus may be due to the specific accumulation of such metabolites in the leaves, in addition to the low stomatal density on the abaxial side of leaves. The identification of drought-tolerance traits of Erianthus will benefit the generation of sugarcane varieties capable of withstanding drought stress.

Food profiling goes green: Sustainable analysis strategies for food authentication

Omics technologies, such as genomics, proteomics, metabolomics, isotopolomics, and metallomics, are important tools for analytical verification of food authenticity. However, in many cases, their application requires the use of high-resolution technological platforms as well as careful consideration of sample collection, storage, preparation and, in particular, extraction. In this overview, the individual steps and disciplines are explained against the background of the term "Green Chemistry," and the various instrumental procedures for the respective omics disciplines are discussed. Furthermore, new approaches and developments are presented on how such analyses can be made sustainable in the future.

Twenty Years of 1H NMR Plant Metabolomics: A Way Forward toward Assessment of Plant Metabolites for Constitutive and Inducible Defenses to Biotic Stress

Metabolomics has become an important tool in elucidating the complex relationship between a plant genotype and phenotype. For over 20 years, nuclear magnetic resonance (NMR) spectroscopy has been known for its robustness, quantitative capabilities, simplicity, and cost-efficiency. 1H NMR is the method of choice for analyzing a broad range of relatively abundant metabolites, which can be used for both capturing the plant chemical profile at one point in time and understanding the pathways that underpin plant defense. This systematic Review explores how 1H NMR-based plant metabolomics has contributed to understanding the role of various compounds in plant responses to biotic stress, focusing on both primary and secondary metabolites. It clarifies the challenges and advantages of using 1H NMR in plant metabolomics, interprets common trends observed, and suggests guidelines for method development and establishing standard procedures.

Climate-Affected Australian Tropical Montane Cloud Forest Plants: Metabolomic Profiles, Isolated Phytochemicals, and Bioactivities

The Australian Wet Tropics World Heritage Area (WTWHA) in northeast Queensland is home to approximately 18 percent of the nation's total vascular plant species. Over the past century, human activity and industrial development have caused global climate changes, posing a severe and irreversible danger to the entire land-based ecosystem, and the WTWHA is no exception. The current average annual temperature of WTWHA in northeast Queensland is 24 °C. However, in the coming years (by 2030), the average annual temperature increase is estimated to be between 0.5 and 1.4 °C compared to the climate observed between 1986 and 2005. Looking further ahead to 2070, the anticipated temperature rise is projected to be between 1.0 and 3.2 °C, with the exact range depending on future emissions. We identified 84 plant species, endemic to tropical montane cloud forests (TMCF) within the WTWHA, which are already experiencing climate change threats. Some of these plants are used in herbal medicines. This study comprehensively reviewed the metabolomics studies conducted on these 84 plant species until now toward understanding their physiological and metabolomics responses to global climate change. This review also discusses the following: (i) recent developments in plant metabolomics studies that can be applied to study and better understand the interactions of wet tropics plants with climatic stress, (ii) medicinal plants and isolated phytochemicals with structural diversity, and (iii) reported biological activities of crude extracts and isolated compounds.

Metabolomics approach to understand molecular mechanisms involved in fungal pathogen-citrus pathosystems

Citrus is a crucial crop with a significant economic impact globally. However, postharvest decay caused by fungal pathogens poses a considerable threat, leading to substantial financial losses. Penicillium digitatum, Penicillium italicum, Geotrichum citri-aurantii and Phyllosticta citricarpa are the main fungal pathogens, causing green mold, blue mold, sour rot and citrus black spot diseases, respectively. The use of chemical fungicides as a control strategy in citrus raises concerns about food and environmental safety. Therefore, understanding the molecular basis of host-pathogen interactions is essential to find safer alternatives. This review highlights the potential of the metabolomics approach in the search for bioactive compounds involved in the pathogen-citrus interaction, and how the integration of metabolomics and genomics contributes to the understanding of secondary metabolites associated with fungal virulence and the fungal infection mechanisms. Our goal is to provide a pipeline combining metabolomics and genomics that can effectively guide researchers to perform studies aiming to contribute to the understanding of the fundamental chemical and biochemical aspects of pathogen-host interactions, in order to effectively develop new alternatives for fungal diseases in citrus cultivation. We intend to inspire the scientific community to question unexplored biological systems, and to employ diverse analytical approaches and metabolomics techniques to address outstanding questions about the non-studied pathosystems from a chemical biology perspective.

Integrative Metabolomics and Proteomics Allow the Global Intracellular Characterization of Bacillus subtilis Cells and Spores

Reliable and comprehensive multi-omics analysis is essential for researchers to understand and explore complex biological systems more completely. Bacillus subtilis (B. subtilis) is a model organism for Gram-positive spore-forming bacteria, and in-depth insight into the physiology and molecular basis of spore formation and germination in this organism requires advanced multilayer molecular data sets generated from the same sample. In this study, we evaluated two monophasic methods for polar and nonpolar compound extraction (acetonitrile/methanol/water; isopropanol/water, and 60% ethanol) and two biphasic methods (chloroform/methanol/water, and methyl tert-butyl ether/methanol/water) on coefficients of variation of analytes, identified metabolite composition, and the quality of proteomics profiles. The 60% EtOH protocol proved to be the easiest in sample processing and was more amenable to automation. Collectively, we annotated 505 and 484 metabolites and identified 1665 and 1562 proteins in B. subtilis vegetative cells and spores, respectively. We also show differences between vegetative cells and spores from a multi-omics perspective and demonstrate that an integrative multi-omics analysis can be implemented from one sample using the 60% EtOH protocol. The results obtained by the 60% EtOH protocol provide comprehensive insight into differences in the metabolic and protein makeup of B. subtilis vegetative cells and spores.

Studying Plant Specialized Metabolites Using Computational Metabolomics Strategies

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

Plant Sample Collection and Shipment for Multi-omic Analyses and Phytosanitary Evaluation

Plant sample preparation for analyses is a fundamental step in high-throughput omics strategies. Especially for plant metabolomics, quenching of hydrolytic enzymes able to affect metabolite concentrations is crucial for the accuracy of results. Given that DNA is usually less labile than metabolites, most sampling and shipment procedures able to preserve the metabolome are also suitable for preventing the degradation of plant DNA or of DNA of pathogens in the plant tissue. In this article, we describe all the steps of sample collection, shipment (including the phytosanitary issues of moving plant samples), and processing for combined genomics and metabolomics from a single sample, as well as the protocols used in our laboratories for downstream approaches for crop plants, allowing collection of multi-omic datasets in large experimental setups. The protocols have been adjusted to apply to both freeze-dried and fresh-frozen material to allow the processing of crop plant samples that will require long-distance transport. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of freeze-dried leaf disks for multiplexed PCR or DArT-Seq genotyping Basic Protocol 2: Medium-throughput preparation of pathogen-free nucleic acids for most genotyping-resequencing applications or pathogen detection Alternate Protocol: Low-throughput extraction of high-quality DNA for resequencing using commercial kits Support Protocol: DNA quality control Basic Protocol 3: Preparation of freeze-dried plant material for metabolomics Basic Protocol 4: Preparation of fresh-frozen plant material for metabolomics Basic Protocol 5: Preparation and shipment of metabolite extracts for metabolomic analyses Basic Protocol 6: Sample shipping and long-term storage.

Influence of arbuscular mycorrhizal fungi density on growth and metabolism of Handroanthus serratifolius (Vahl) S.O. Grose seedlings

Studies on the relationship between Handroanthus serratifolius and arbuscular mycorrhizal fungi (AMF) are limited in the literature. The influence of AMF spore density on plant development is fundamental information to determining the degree of benefits in this relationship. Therefore, the objective of this study was to investigate the effects of different AMF spore densities on thirty-day-old H. serratifolius seedlings, focusing on growth and biochemical parameters using a completely randomized experimental design with three different spore densities and control. The spore densities were classified as low, medium, and high, with 1.54, 3.08, and 12.35 spores g-1 , respectively. Plant growth analysis, mycorrhizal colonization, nitrogen compound concentration, and carbohydrate analysis were performed. The medium spore density treatment showed the greatest increases in biomass, height, leaf area, and root volume. Furthermore, greater absorption of phosphorus and better dynamics in nitrogen metabolism were observed in mycorrhizal plants compared to the control since the ammonium and nitrate compounds were rapidly incorporated into protein and chlorophyll compounds. The carbohydrate analysis revealed the influence of source-sink dynamics on sugar concentration in different plant parts. These findings support the importance of determining the appropriate spore density for assessing the symbiotic relationship between forest species and AMF.

Exploratory optimisation of a LC-HRMS based analytical method for untargeted metabolomic screening of Cannabis Sativa L. through Data Mining

BACKGROUND

Recent increase in public acceptance of cannabis as a natural medical alternative for certain neurological pathologies has led to its approval in different regions of the world. However, due to its previous illegal background, little research has been conducted around its biochemical insights. Therefore, in the current framework, metabolomics may be a suitable approach for deepening the knowledge around this plant species. Nevertheless, experimental methods in metabolomics must be carefully handled, as slight modifications can lead to metabolomic coverage loss. Hence, the main objective of this work was to optimise an analytical method for appropriate untargeted metabolomic screening of cannabis.

RESULTS

We present an empirically optimised experimental procedure through which the broadest metabolomic coverage was obtained, in which extraction solvents for metabolite isolation, chromatographic columns for LC-qOrbitrap analysis and plant-representative biological tissues were compared. By exploratory means, it was determined that the solvent combination composed of CHCl3:H2O:CH3OH (2:1:1, v/v) provided the highest number of features from diverse chemical classes, as it was a two-phase extractant. In addition, a reverse phase 2.6 μm C18 100 Å (150 × 3 mm) chromatographic column was determined as the appropriate choice for adequate separation and further detection of the diverse metabolite classes. Apart from that, overall chromatographic peak quality provided by each column was observed and the need for batch correction methods through quality control (QC) samples was confirmed. At last, leaf and flower tissues resulted to provide complementary metabolic information of the plant, to the detriment of stem tissue, which resulted to be negligible.

SIGNIFICANCE

It was concluded that the optimised experimental procedure could significantly ease the path for future research works related to cannabis metabolomics by LC-HRMS means, as the work was based on previous plant metabolomics literature. Furthermore, it is crucial to highlight that an optimal analytical method can vary depending on the main objective of the research, as changes in the experimental factors can lead to different outcomes, regardless of whether the results are better or worse.

Can plant hormonomics be built on simple analysis? A review

The field of plant hormonomics focuses on the qualitative and quantitative analysis of the hormone complement in plant samples, akin to other omics sciences. Plant hormones, alongside primary and secondary metabolites, govern vital processes throughout a plant's lifecycle. While active hormones have received significant attention, studying all related compounds provides valuable insights into internal processes. Conventional single-class plant hormone analysis employs thorough sample purification, short analysis and triple quadrupole tandem mass spectrometry. Conversely, comprehensive hormonomics analysis necessitates minimal purification, robust and efficient separation and better-performing mass spectrometry instruments. This review summarizes the current status of plant hormone analysis methods, focusing on sample preparation, advances in chromatographic separation and mass spectrometric detection, including a discussion on internal standard selection and the potential of derivatization. Moreover, current approaches for assessing the spatiotemporal distribution are evaluated. The review touches on the legitimacy of the term plant hormonomics by exploring the current status of methods and outlining possible future trends.

Automatization of metabolite extraction for high-throughput metabolomics: case study on transgenic isoprene-emitting birch

Metabolomics studies are becoming increasingly common for understanding how plant metabolism responds to changes in environmental conditions, genetic manipulations and treatments. Despite the recent advances in metabolomics workflow, the sample preparation process still limits the high-throughput analysis in large-scale studies. Here, we present a highly flexible robotic system that integrates liquid handling, sonication, centrifugation, solvent evaporation and sample transfer processed in 96-well plates to automatize the metabolite extraction from leaf samples. We transferred an established manual extraction protocol performed to a robotic system, and with this, we show the optimization steps required to improve reproducibility and obtain comparable results in terms of extraction efficiency and accuracy. We then tested the robotic system to analyze the metabolomes of wild-type and four transgenic silver birch (Betula pendula Roth) lines under unstressed conditions. Birch trees were engineered to overexpress the poplar (Populus × canescens) isoprene synthase and to emit various amounts of isoprene. By fitting the different isoprene emission capacities of the transgenic trees with their leaf metabolomes, we observed an isoprene-dependent upregulation of some flavonoids and other secondary metabolites as well as carbohydrates, amino acid and lipid metabolites. By contrast, the disaccharide sucrose was found to be strongly negatively correlated to isoprene emission. The presented study illustrates the power of integrating robotics to increase the sample throughput, reduce human errors and labor time, and to ensure a fully controlled, monitored and standardized sample preparation procedure. Due to its modular and flexible structure, the robotic system can be easily adapted to other extraction protocols for the analysis of various tissues or plant species to achieve high-throughput metabolomics in plant research.

Longitudinal Plant Health Monitoring via High-Resolution Mass Spectrometry Screening Workflows: Application to a Fertilizer Mediated Tomato Growth Experiment

Significant efforts have been spent in the modern era towards implementing environmentally friendly procedures like composting to mitigate the negative effects of intensive agricultural practices. In this context, a novel fertilizer was produced via the hydrolysis of an onion-derived compost, and has been previously comprehensively chemically characterized. In order to characterize its efficacy, the product was applied to tomato plants at five time points to monitor plant health and growth. Control samples were also used at each time point to eliminate confounding parameters due to the plant's normal growth process. After harvesting, the plant leaves were extracted using aq. MeOH (70:30, v/v) and analyzed via UPLC-QToF-MS, using a C18 column in both ionization modes (±ESI). The data-independent (DIA/bbCID) acquisition mode was employed, and the data were analyzed by MS-DIAL. Statistical analysis, including multivariate and trend analysis for longitudinal monitoring, were employed to highlight the differentiated features among the controls and treated plants as well as the time-point sequence. Metabolites related to plant growth belonging to several chemical classes were identified, proving the efficacy of the fertilizer product. Furthermore, the efficiency of the analytical and statistical workflows utilized was demonstrated.

Metabolomics and genetics of reproductive bud development in Ficus carica var. sativa (edible fig) and in Ficus carica var. caprificus (caprifig): similarities and differences

In figs, reproductive biology comprises cultivars requiring or not pollination, with female trees (edible fig) and male trees (caprifig) bearing different types of fruits. Metabolomic and genetic studies may clarify bud differentiation mechanisms behind the different fruits. We used a targeted metabolomic analysis and genetic investigation through RNA sequence and candidate gene investigation to perform a deep analysis of buds of two fig cultivars, 'Petrelli' (San Pedro type) and 'Dottato' (Common type), and one caprifig. In this work, proton nuclear magnetic resonance (¹H NMR-based metabolomics) has been used to analyze and compare buds of the caprifig and the two fig cultivars collected at different times of the season. Metabolomic data of buds collected on the caprifig, 'Petrelli', and 'Dottato' were treated individually, building three separate orthogonal partial least squared (OPLS) models, using the "y" variable as the sampling time to allow the identification of the correlations among metabolomic profiles of buds. The sampling times revealed different patterns between caprifig and the two edible fig cultivars. A significant amount of glucose and fructose was found in 'Petrelli', differently from 'Dottato', in the buds in June, suggesting that these sugars not only are used by the ripening brebas of 'Petrelli' but also are directed toward the developing buds on the current year shoot for either a main crop (fruit in the current season) or a breba (fruit in the successive season). Genetic characterization through the RNA-seq of buds and comparison with the literature allowed the identification of 473 downregulated genes, with 22 only in profichi, and 391 upregulated genes, with 21 only in mammoni.

Untargeted Plant Metabolomics: Evaluation of Lyophilization as a Sample Preparation Technique

Lyophilization is a common method used for stabilizing biological samples prior to storage or to concentrate extracts. However, it is possible that this process may alter the metabolic composition or lead to the loss of metabolites. In this study, the performance of lyophilization is investigated in the example of wheat roots. To this end, native and ¹³C-labelled, fresh or already lyophilized root samples, and (diluted) extracts with dilution factors up to 32 and authentic reference standards were investigated. All samples were analyzed using RP-LC-HRMS. Results show that using lyophilization for the stabilization of plant material altered the metabolic sample composition. Overall, 7% of all wheat metabolites detected in non-lyophilized samples were not detected in dried samples anymore, and up to 43% of the remaining metabolites exhibited significantly increased or decreased abundances. With respect to extract concentration, less than 5% of the expected metabolites were completely lost by lyophilization and the recovery rates of the remaining metabolites were slightly reduced with increasing concentration factors to an average of 85% at an enrichment factor of 32. Compound annotation did not indicate specific classes of wheat metabolites to be affected.

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.

Phytochemical Profile and In Vitro Bioactivities of Plant-Based By-Products in View of a Potential Reuse and Valorization

Wastes and by-products of plant origin are of particular interest to develop a circular economy approach, which attempts to turn them into resources. In this work, thirty-seven neglected plant matrices, including agricultural residues, pest plants, and by-products from the herbal and food industry were extracted and tested for their in vitro anti-tyrosinase, antioxidant, and antibacterial activity against the phytopathogens Pseudomonas syringae pv. syringae ATCC 19310 and Clavibacter michiganensis subsp. nebraskense ATCC 27822. Antioxidant activity ranged from 0.3 to 5 mg of Tr. eq/mL of plant extract, and extract of Castanea sativa pericarp (Csp), Rosa damascena buds (post-distillation) (Rod), and Prunus amygdalus exocarp and mesocarp (Pam) were the most powerful ones. Csp was also capable of inhibiting tyrosinase (IC₅₀ = 16.5 µg/mL), as well as three distillation by-products, namely: Cupressus sempervirens (Css) (IC₅₀ = 95.5 µg/mL), Salvia officinalis (Sco) (IC₅₀ = 87.6 µg/mL), and Helichrysum italicum (Hei) (IC₅₀ = 90.1 µg/mL). Five residues from distillation showed antibacterial activity against C. michiganensis (MICs ranging from 0.125 to 1 mg/mL), namely: Salvia sclarea L. (Sas), Salvia rosmarinus Schleid (Sar), Sco, Hei, and Css. The ¹H NMR fingerprinting of the bioactive matrices was acquired, detecting primary and secondary metabolites (rosmarinic acid, shikimic acid, sclareol, and hydroxycinnamic acids).

Placental Metabolomics of Fetal Growth Restriction

Fetal growth restriction is an obstetrical pathological condition that causes high neonatal mortality and morbidity. The mechanisms of its onset are not completely understood. Metabolites were extracted from 493 placentas from non-complicated pregnancies in Hamilton Country, TN (USA), and analyzed by gas chromatography-mass spectrometry (GC-MS). Newborns were classified according to raw fetal weight (low birth weight (LBW; <2500 g) and non-low birth weight (Non-LBW; >2500 g)), and according to the calculated birth weight centile as it relates to gestational age (small for gestational age (SGA), large for gestational age (LGA), and adequate for gestational age (AGA)). Mothers of LBW infants had a lower pre-pregnancy weight (66.2 ± 17.9 kg vs. 73.4 ± 21.3 kg, p < 0.0001), a lower body mass index (BMI) (25.27 ± 6.58 vs. 27.73 ± 7.83, p < 0.001), and a shorter gestation age (246.4 ± 24.0 days vs. 267.2 ± 19.4 days p < 0.001) compared with non-LBW. Marital status, tobacco use, and fetus sex affected birth weight centile classification according to gestational age. Multivariate statistical comparisons of the extracted metabolomes revealed that asparagine, aspartic acid, deoxyribose, erythritol, glycerophosphocholine, tyrosine, isoleucine, serine, and lactic acid were higher in both SGA and LBW placentas, while taurine, ethanolamine, β-hydroxybutyrate, and glycine were lower in both SGA and LBW. Several metabolic pathways are implicated in fetal growth restriction, including those related to the hypoxia response and amino-acid uptake and metabolism. Inflammatory pathways are also involved, suggesting that fetal growth restriction might share some mechanisms with preeclampsia.

Integration of Non-targeted Proteomics Mass Spectrometry with Machine Learning for Screening Cooked Beef Adulterated Samples

The degradation of ingredients in heat-processed meat products makes their authentication challenging. In this study, protein profiles of raw beef, chicken, duck, pork, and binary simulated adulterated beef samples (chicken-beef, duck-beef, and pork-beef) and their heat-processed samples were obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Heat-stable characteristic proteins were found by screening the overlapping characteristic protein ion peaks of the raw and corresponding heat-processed samples, which were discovered by partial least-squares discriminant analysis. Based on the 36 heat-stable characteristic proteins, qualitative classification for the raw and heat-processed meats was achieved by extreme gradient boosting. Moreover, quantitative analysis via partial least squares regression was applied to determine the adulteration ratio of the simulated adulterated beef samples. The validity of the approach was confirmed by a blind test with the mean accuracy of 97.4%. The limit of detection and limit of quantification of this method were determined to be 5 and 8%, respectively, showing its practical aspect for the beef authentication.

Seaweed metabolomics: A review on its nutrients, bioactive compounds and changes in climate change

Seaweed, an important food resource in several Asian countries, contains various metabolites, including sugars, organic acids, and amino acids; however, their content is affected by prevailing environmental conditions. This review discusses seaweed metabolomics, especially the distribution of primary and functional secondary metabolites (e.g., carotenoids, polyphenols) in seaweed. Additionally, the effects of global warming on seaweed metabolite profile changes are discussed. For example, high temperatures can increase amino acid levels in seaweeds. Overall, understanding the effects of global warming on seaweed metabolite profiles can be useful for evaluating the nutritional composition of seaweeds as food. This review provides an overview of recent applications of metabolomics in seaweed research as well as a perspective on the nutrient content and cultivation of seaweeds under climate change scenarios.

Metabolomics: Going Deeper, Going Broader, Going Further

Metabolomics is a continuously dynamic field of research that is driven by demanding research questions and technological advances alike. In this review we highlight selected recent and ongoing developments in the area of mass spectrometry-based metabolomics. The field of view that can be seen through the metabolomics lens can be broadened by adoption of separation techniques such as hydrophilic interaction chromatography and ion mobility mass spectrometry (going broader). For a given biospecimen, deeper metabolomic analysis can be achieved by resolving smaller entities such as rare cell populations or even single cells using nano-LC and spatially resolved metabolomics or by extracting more useful information through improved metabolite identification in untargeted metabolomic experiments (going deeper). Integration of metabolomics with other (omics) data allows researchers to further advance in the understanding of the complex metabolic and regulatory networks in cells and model organisms (going further). Taken together, diverse fields of research from mechanistic studies to clinics to biotechnology applications profit from these technological developments.

Comparative metabolomics reveal intraspecies variability in bioactive compounds of different cultivars of pomegranate fruit (Punica granatum L.) and their waste by-products

BACKGROUND

The different parts of pomegranate fruit are considered a powerful mixture of bioactive compounds yet the peels and pulps of the fruits are usually discarded and considered as industrial waste. In this work, ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry (UPLC-QqQ-MS) was utilized for metabolomics analysis of different parts (peel, pulp, seed and juice) of pomegranate fruit cultivars to verify possible variations among the fruits and their waste products as potential sources of functional constituents.

RESULTS

Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) coefficient-plot showed enrichment of phenolic compounds such as punicalagin and ellagic acid derivatives in pulp samples while seeds class was enriched in phlorizin, catechin and quercetin, juice class showed abundance of naringenin and pelargonidin-3-pentoside while peels were enriched in anthocyanins and flavonoids including cyanidin diglycoside, quercetin and luteolin glycosides. Although the juice samples of almost all tested cultivars showed remarkable cytotoxic activity, the pulp samples, particularly the Manfalouti cultivar, exhibited the most potent [half maximal inhibitory concentration (IC₅₀ ) = 2.367 ± 0.14 μg/mL in MCF-7, IC₅₀  = 3.854 ± 0.23 μg/mL in Hep-G2 cell lines]. OPLS models were constructed for determination of cytotoxicity-associated metabolites among where the coefficients plots revealed tannins; granatin A, ellagic acid derivatives, punicalagin α and β, in addition to anthocyanins and phenolic compounds; cyanidin diglycoside, quercetin, phlorizin, 3-O-caffeoylquinic acid, naringenin and liquiritin were more pertinent with cytotoxicity of the different parts of pomegranate fruit.

CONCLUSION

The results obtained allow for the full utilization of the resources of pomegranate fruit and its industrial waste as sources of bioactive compounds. © 2022 Society of Chemical Industry.

Single, but not dual, attack by a biotrophic pathogen and a sap-sucking insect affects the oak leaf metabolome

Plants interact with a multitude of microorganisms and insects, both below- and above ground, which might influence plant metabolism. Despite this, we lack knowledge of the impact of natural soil communities and multiple aboveground attackers on the metabolic responses of plants, and whether plant metabolic responses to single attack can predict responses to dual attack. We used untargeted metabolic fingerprinting (gas chromatography-mass spectrometry, GC-MS) on leaves of the pedunculate oak, Quercus robur, to assess the metabolic response to different soil microbiomes and aboveground single and dual attack by oak powdery mildew (Erysiphe alphitoides) and the common oak aphid (Tuberculatus annulatus). Distinct soil microbiomes were not associated with differences in the metabolic profile of oak seedling leaves. Single attacks by aphids or mildew had pronounced but different effects on the oak leaf metabolome, but we detected no difference between the metabolomes of healthy seedlings and seedlings attacked by both aphids and powdery mildew. Our findings show that aboveground attackers can have species-specific and non-additive effects on the leaf metabolome of oak. The lack of a metabolic signature detected by GC-MS upon dual attack might suggest the existence of a potential negative feedback, and highlights the importance of considering the impacts of multiple attackers to gain mechanistic insights into the ecology and evolution of species interactions and the structure of plant-associated communities, as well as for the development of sustainable strategies to control agricultural pests and diseases and plant breeding.

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

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.

Towards a broader view of the metabolome: untargeted profiling of soluble and bound polyphenols in plants

Phenylalanine (Phe) is a central precursor for numerous secondary plant metabolites with a multitude of biological functions. Recent studies on the fungal disease Fusarium head blight in wheat showed numerous Phe-derived defence metabolites to be induced in the presence of the pathogen. These studies also suggest a partial incorporation of Phe-derived secondary metabolites into the cell wall. To broaden the view of the metabolome to bound Phe derivatives, an existing approach using ¹³C-labelled Phe as tracer was extended. The developed workflow consists of three successive extractions with an acidified acetonitrile-methanol-water mixture to remove the soluble plant metabolites, followed by cell wall hydrolysis with 4M aqueous NaOH, acidification with aqueous HCl, and liquid-liquid extraction of the hydrolysate with ethyl acetate. The untargeted screening of Phe-derived metabolites revealed 156 soluble compounds and 90 compounds in the hydrolysed samples including known cell wall constituents like ferulic acid, coumaric acid, and tricin. Forty-nine metabolites were found exclusively in the hydrolysate. The average cumulative extraction yield of the soluble metabolites was 99.6%, with a range of 91.8 to 100%. Repeatability coefficients of variation of the protocol ranged from 10.5 to 25.9%, with a median of 16.3%. To demonstrate the suitability of the proposed method for a typical metabolomics application, mock-treated and Fusarium graminearum-treated wheat samples were compared. The study revealed differences between the hydrolysates of the two sample types, confirming the differential incorporation of Phe-derived metabolites into the cell wall under infection conditions.

Comparison of Widely Targeted Metabolomics and Untargeted Metabolomics of Wild Ophiocordyceps Sinensis

The authors of this paper conducted a comparative metabolomic analysis of Ophiocordyceps sinensis (OS), providing the metabolic profiles of the stroma (OSBSz) and sclerotia (OSBSh) of OS by widely targeted metabolomics and untargeted metabolomics. The results showed that 778 and 1449 metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. The metabolites in OSBSz and OSBSh are significantly differentiated; 71 and 96 differentially expressed metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. This suggests that these 71 metabolites (riboflavine, tripdiolide, bromocriptine, lumichrome, tetrahymanol, citrostadienol, etc.) and 96 metabolites (sancycline, vignatic acid B, pirbuterol, rubrophen, epalrestat, etc.) are potential biomarkers. 4-Hydroxybenzaldehyde, arginine, and lumichrome were common differentially expressed metabolites. Using the widely targeted metabolomics approach, the key pathways identified that are involved in creating the differentiation between OSBSz and OSBSh may be nicotinate and nicotinamide metabolism, thiamine metabolism, riboflavin metabolism, glycine, serine, and threonine metabolism, and arginine biosynthesis. The differentially expressed metabolites identified using the untargeted metabolomics approach were mainly involved in arginine biosynthesis, terpenoid backbone biosynthesis, porphyrin and chlorophyll metabolism, and cysteine and methionine metabolism. The purpose of this research was to provide support for the assessment of the differences between the stroma and sclerotia, to furnish a material basis for the evaluation of the physical effects of OS, and to provide a reference for the selection of detection methods for the metabolomics of OS.

High-throughput plant phenotyping: a role for metabolomics?

High-throughput (HTP) plant phenotyping approaches are developing rapidly and are already helping to bridge the genotype-phenotype gap. However, technologies should be developed beyond current physico-spectral evaluations to extend our analytical capacities to the subcellular level. Metabolites define and determine many key physiological and agronomic features in plants and an ability to integrate a metabolomics approach within current HTP phenotyping platforms has huge potential for added value. While key challenges remain on several fronts, novel technological innovations are upcoming yet under-exploited in a phenotyping context. In this review, we present an overview of the state of the art and how current limitations might be overcome to enable full integration of metabolomics approaches into a generic phenotyping pipeline in the near future.

Research Progress and Trends in Metabolomics of Fruit Trees

Metabolomics is an indispensable part of modern systems biotechnology, applied in the diseases' diagnosis, pharmacological mechanism, and quality monitoring of crops, vegetables, fruits, etc. Metabolomics of fruit trees has developed rapidly in recent years, and many important research results have been achieved in combination with transcriptomics, genomics, proteomics, quantitative trait locus (QTL), and genome-wide association study (GWAS). These research results mainly focus on the mechanism of fruit quality formation, metabolite markers of special quality or physiological period, the mechanism of fruit tree's response to biotic/abiotic stress and environment, and the genetics mechanism of fruit trait. According to different experimental purposes, different metabolomic strategies could be selected, such as targeted metabolomics, non-targeted metabolomics, pseudo-targeted metabolomics, and widely targeted metabolomics. This article presents metabolomics strategies, key techniques in metabolomics, main applications in fruit trees, and prospects for the future. With the improvement of instruments, analysis platforms, and metabolite databases and decrease in the cost of the experiment, metabolomics will prompt the fruit tree research to achieve more breakthrough results.

Plant metabolomics: a new strategy and tool for quality evaluation of Chinese medicinal materials

The present quality control method of Chinese medicinal materials (CMM) has obvious deficiency, which cannot be compatible with the multi-target and multi-component characteristics and production process of CMM. Plant metabolomics with a huge impetus to comprehensively characterize the metabolites and clarify the complexity and integrity of CMM, has been widely used in the research of CMM. This article comprehensively reviewed the application of plant metabolomics in the quality control of CMM. It introduced the concept, technique, and application examples, discussed the prospects, limitations, improvements of plant metabolomics. MS and NMR, as important techniques for plant metabolomics, are mainly highlighted in the case references. The purpose of this article is to clarify the advantage of plants metabolomics for promoting the optimization of the CMM quality control system and proposing a system approach to realize the overall quality control of CMM based on plant metabolomics combined with multidisciplinary method.

Amplified Drought and Seasonal Cycle Modulate Quercus pubescens Leaf Metabolome

The intensification of summer drought expected with climate change can induce metabolism modifications in plants to face such constraints. In this experiment, we used both a targeted approach focused on flavonoids, as well as an untargeted approach, to study a broader fraction of the leaf metabolome of Quercus pubescens exposed to amplified drought. A forest site equipped with a rainfall exclusion device allowed reduction of natural rainfall by ~30% over the tree canopy. Leaves of natural drought (ND) and amplified drought (AD) plots were collected over three seasonal cycles (spring, summer, and autumn) in 2013 (the second year of rain exclusion), 2014, and 2015. As expected, Q. pubescens metabolome followed a seasonal course. In the summer of 2015, the leaf metabolome presented a shifted and early autumnal pattern because of harsher conditions during this year. Despite low metabolic modification at the global scale, our results demonstrated that 75% of Quercus metabolites were upregulated in springs when trees were exposed to AD, whereas 60 to 73% of metabolites (93% in summer 2015), such as kaempferols and quercetins, were downregulated in summers/autumns. Juglanin, a kaempferol pentoside, as well as rhododendrin derivatives, were upregulated throughout the year, suggesting an antioxidant ability of these metabolites. Those changes in terms of phenology and leaf chemistry could, in the end, affect the ecosystem functioning.

Metabolite profile of African horned cucumber (Cucumis metuliferus E. May. Ex Naudin) fruit grown under differing environmental conditions

Plant metabolites are known as biological compounds that are essential to the growth and development of a plant and have a direct impact on yield and biochemical constituents of plants. For this study, the objective was to conduct primary metabolomics analysis using liquid chromatography mass spectrometry. African horned cucumber fruits were harvested from plants grown under pots experiment (greenhouse, shade net and open field), soil types (loamy soil and sandy loam) and three water stress levels (no water stress-100%-3L, moderate water stress-75%-2L, and severe water stress-35%-1L) during 2017/18 and 2018/19 seasons. Results showed that the treatment of no water stress combined with sandy loam under shade net environment, significantly increased asparagine content from 10 × 10⁶ to 80 × 10⁶ peak intensity. The treatment of no water stress, in combination with sandy loam soil under open field environment increased 4-hydroxyproline from 10 × 10⁶ to 90 × 10⁶ peak intensity compared to other treatments. It can be deduced that the treatment combination of (no water stress and moderate water stress) and all soil types, under greenhouse environment increased most metabolites content of the fruit when compared to other treatments. Therefore, it subsequently has potential to affect fruit quality such as taste and other biochemical constituents.

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".

Enantioselective metabolomics by liquid chromatography-mass spectrometry

Metabolomics strives to capture the entirety of the metabolites in a biological system by comprehensive analysis, often by liquid chromatography hyphenated to mass spectrometry. A particular challenge thereby is the differentiation of structural isomers. Common achiral targeted and untargeted assays do not distinguish between enantiomers. This may lead to information loss. An increasing number of publications demonstrate that the enantiomeric ratio of certain metabolites can be meaningful biomarkers of certain diseases emphasizing the importance of introducing enantioselective analytical procedures in metabolomics. In this work, the state-of-the-art in the field of LC-MS based metabolomics is summarized with focus on developments in the recent decade. Methodologies, tagging strategies, workflows and general concepts are outlined. Selected biological applications in which enantioselective metabolomics has documented its usefulness are briefly discussed. In general, targeted enantioselective metabolomics assays are often based on a direct approach using chiral stationary phases (CSP) with polysaccharide derivatives, macrocyclic antibiotics, chiral crown ethers, chiral ion exchangers, donor-acceptor phases as chiral selectors. Rarely, these targeted assays focus on more than 20 analytes and usually are restricted to a certain metabolite class. In a variety of cases, pre-column derivatization of metabolites has been performed, especially for amino acids, to improve separation and detection sensitivity. Triple quadrupole instruments are the detection methods of first choice in targeted assays. Here, issues like matrix effect, absence of blank matrix impair accuracy of results. In selected applications, multiple heart cutting 2D-LC (RP followed by chiral separation) has been pursued to overcome this problem and alleviate bias due to interferences. Non-targeted assays, on the other hand, are based on indirect approach involving tagging with a chiral derivatizing agent (CDA). Besides classical CDAs numerous innovative reagents and workflows have been proposed and are discussed. Thereby, a critical issue for the accuracy is often neglected, viz. the validation of the enantiomeric impurity in the CDA. The majority of applications focus on amino acids, hydroxy acids, oxidized fatty acids and oxylipins. Some potential clinical applications are highlighted.

Metabolomics in Exercise and Sports: A Systematic Review

BACKGROUND

Metabolomics is a field of omics science that involves the comprehensive measurement of small metabolites in biological samples. It is increasingly being used to study exercise physiology and exercise-associated metabolism. However, the field of exercise metabolomics has not been extensively reviewed or assessed.

OBJECTIVE

This review on exercise metabolomics has three aims: (1) to provide an introduction to the general workflow and the different metabolomics technologies used to conduct exercise metabolomics studies; (2) to provide a systematic overview of published exercise metabolomics studies and their findings; and (3) to discuss future perspectives in the field of exercise metabolomics.

METHODS

We searched electronic databases including Google Scholar, Science Direct, PubMed, Scopus, Web of Science, and the SpringerLink academic journal database between January 1st 2000 and September 30th 2020.

RESULTS

Based on our detailed analysis of the field, exercise metabolomics studies fall into five major categories: (1) exercise nutrition metabolism; (2) exercise metabolism; (3) sport metabolism; (4) clinical exercise metabolism; and (5) metabolome comparisons. Exercise metabolism is the most popular category. The most common biological samples used in exercise metabolomics studies are blood and urine. Only a small minority of exercise metabolomics studies employ targeted or quantitative techniques, while most studies used untargeted metabolomics techniques. In addition, mass spectrometry was the most commonly used platform in exercise metabolomics studies, identified in approximately 54% of all published studies. Our data indicate that biomarkers or biomarker panels were identified in 34% of published exercise metabolomics studies.

CONCLUSION

Overall, there is an increasing trend towards better designed, more clinical, mass spectrometry-based metabolomics studies involving larger numbers of participants/patients and larger numbers of metabolites being identified.

Current State of Metabolomics Research in Meat Quality Analysis and Authentication

In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.

Study on changes in pigment composition during the blooming period of safflower based on plant metabolomics and semi-quantitative analysis

Red and yellow pigments are the major ingredients of safflower, often used to color food and cosmetics. Carthamin was the main component of red pigment and hydroxysafflor yellow A and anhydrosafflower yellow B were representative components of yellow pigment. Plant metabolomics and semi-quantitative analysis were used to analyze the changes of pigment composition during the blooming period, especially these characteristic components. Carthamin, hydroxysafflor yellow A, anhydrosafflower yellow B, and other components were screened out as differential metabolites based on plant metabolomics. Then semi-quantitative analysis was used to quantify these three representative components of pigments. Experimental results showed that the content of pigments has dynamic changes along with flowering, in the early blooming period, yellow pigment accumulated much and red pigment was low in content. In the middle period, the accumulation rate of the yellow pigment slowed down and content was stabilized. In the next step, the content of yellow pigments gradually decreased, and the content of red pigments gradually increased. Later, the level of yellow pigment decreased significantly, and the accumulation rate of red pigment increased significantly. Last, the appearance color of safflower was red, with yellow parts barely visible, and accumulation of red pigment was the highest and of the yellow pigment was the lowest in content.

The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science

The environment, from microbial ecosystems to recycled resources, fluctuates dynamically due to many physical, chemical and biological factors, the profile of which reflects changes in overall state, such as environmental illness caused by a collapse of homeostasis. To evaluate and predict environmental health in terms of systemic homeostasis and resource balance, a comprehensive understanding of these factors requires an approach based on the "exposome paradigm", namely the totality of exposure to all substances. Furthermore, in considering sustainable development to meet global population growth, it is important to gain an understanding of both the circulation of biological resources and waste recycling in human society. From this perspective, natural environment, agriculture, aquaculture, wastewater treatment in industry, biomass degradation and biodegradable materials design are at the forefront of current research. In this respect, nuclear magnetic resonance (NMR) offers tremendous advantages in the analysis of samples of molecular complexity, such as crude bio-extracts, intact cells and tissues, fibres, foods, feeds, fertilizers and environmental samples. Here we outline examples to promote an understanding of recent applications of solution-state, solid-state, time-domain NMR and magnetic resonance imaging (MRI) to the complex evaluation of organisms, materials and the environment. We also describe useful databases and informatics tools, as well as machine learning techniques for NMR analysis, demonstrating that NMR data science can be used to evaluate the exposome in both the natural environment and human society towards a sustainable future.

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

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

Research on Biomarkers of Different Growth Periods and Different Drying Processes of Citrus wilsonii Tanaka Based on Plant Metabolomics

Fruit of Citrus wilsonii Tanaka called as "Xiang yuan" in Chinese, which means fragrant and round. It was widely used in the pharmaceutical and food industries. This fruit has well-known health benefits such as antioxidant, radical scavenging, and anti-inflammatory. Naringin, deacetylnomilin, citric acid, limonin, and nomilin were the characteristic components of Citrus wilsonii Tanaka. Although the fruit of Citrus wilsonii Tanaka possessed many applications, there was a lack of research on the growth period and drying process. In this study, plant metabolomics was used to analyze the biomarkers of the growth period, and appearance indicators and metabolites abundance were combined for the analysis of change regularities of the growth period. The representative differential metabolites of naringin, citric acid, and limonin were screened out, and the abundance of these components was relatively highest in the middle of the growth period. Therefore, the fruit of Citrus wilsonii Tanaka should be harvested before it turned yellow completely, which could effectively ensure the content of potential active ingredients. In the comparison of different drying methods, citric acid and naringin were considered to be representative differential components, but limonoids were relatively stable and not easily affected by drying methods. Naringin was an index component that could not only be reflected the maturity but also related to different drying methods. Considering its physical and chemical properties and its position, naringin had the potential to be a biomarker of Citrus wilsonii Tanaka.

Soybean Metabolomics Based in Mass Spectrometry: Decoding the Plant's Signaling and Defense Responses under Biotic Stress

Metabolomics is an omics technology that is extremely valuable to analyze all small-molecule metabolites in organisms. Recent advances in analytical instrumentation, such as mass spectrometry combined with data processing tools, chemometrics, and spectral data libraries, allow plant metabolomics studies to play a fundamental role in the agriculture field and food security. Few studies are found in the literature using the metabolomics approach in soybean plants on biotic stress. In this review, we provide a new perspective highlighting the potential of metabolomics-based mass spectrometry for soybean in response to biotic stress. Furthermore, we highlight the response and adaptation mechanisms of soybean on biotic stress about primary and secondary metabolism. Consequently, we provide subsidies for further studies of the resistance and improvement of the crop.

Metabolomic Approaches to Studying the Response to Drought Stress in Corn (Zea mays) Cobs

Metabolomics is a technique that allows for the evaluation of the entire extractable chemical profile of a plant, for example, using high-resolution mass spectrometry (HRMS) and can be used to evaluate plant stress responses, such as those due to drought. Metabolomic analysis is dependent upon the efficiency of the extraction protocol. Currently, there are two common extraction procedures widely used in metabolomic experiments, those that extract from plant tissue processed in liquid nitrogen or extraction from lyophilised plant tissues. Here, we evaluated the two using non-targeted metabolomics to show that lyophilisation can stabilise the maize (Zea mays) extractable metabolome, increasing throughput and efficiency of extraction as compared to the more traditional processing in liquid nitrogen. Then, we applied the lyophilisation approach to explore the effect of drought upon the maize metabolome in a non-targeted HRMS metabolomics approach. Metabolomics revealed differences in the mature maize metabolome having undergone three drought conditions imposed at two critical development stages (three-leaf stage and grain-fill stage); moreover, this difference was observed across two tissue types (kernel and inner cob/pith). It was shown that under ideal conditions, the biochemical make-up of the tissue types is different. However, under stress conditions, the stress response dominates the metabolic profile. Drought-related metabolites known from other plant systems have been identified and metabolomics has revealed potential novel drought-stress indicators in our maize system.

Metabolomics as a marketing tool for geographical indication products: a literature review

Geographical indication (GI) is used to identify a product's origin when its characteristics or quality are a result of geographical origin, which includes agricultural products and foodstuff. Metabolomics is an “omics” technique that can support product authentication by providing a chemical fingerprint of a biological system, such as plant and plant-derived products. The main purpose of this article is to verify possible contributions of metabolomic studies to the marketing field, mainly for certified regions, through an integrative review of the literature and maps produced by VOSviewer software. The results indicate that studies based on metabolomics approaches can relate specific food attributes to the region’s terroir and know-how. The evidence of this connection, marketing of GIs and metabolomics methods, is viewed as potential tool for marketing purposes (e.g., to assist communication of positive aspects and quality), and legal protection. In addition, our results provide a taxonomic categorization that can guide future marketing research involving metabolomics. Moreover, the results are also useful to government agencies to improve GIs registration systems and promotion strategies.

Metabolomic Response of Tomatoes (Solanum lycopersicum L.) against Bacterial Wilt (Ralstonia solanacearum) Using 1H-NMR Spectroscopy

Ralstonia solanacearum is the pathogen responsible for wilting, yield losses, and death in tomato plants. The use of resistant cultivars has been proven as the most appropriate solution to controlling this pathogen. Therefore, further study of host-plant resistance mechanisms in tomatoes is urgently needed. ¹H-NMR (nuclear magnetic resonance) spectroscopy combined with multivariate data analysis has been used to identify the biochemical compounds that play a crucial role in the defense mechanisms of tomato against bacterial wilt. Eleven metabolites consisting of amino acids, sugars and organic acids were identified and presented at different concentrations in each cultivar. Leucine and valine were determined as distinguishable metabolites of resistant and susceptible cultivars. Permata and Hawaii 7996 as resistant cultivars had a significant decrease of valine after inoculation about 1.5-2 times compared to the susceptible cultivar (GM2). Meanwhile, the resistant cultivars had a higher level of leucine, about 1.3-1.5 times compared to the susceptible ones. Synthesis of leucine and valine are linked as a member of the pyruvate family. Therefore, the decrease in valine may be related to the higher need for leucine to form the leucine-rich receptor, which plays a role in the plant's immune system against the bacterial wilt.

NMR Profiling of Ononis diffusa Identifies Cytotoxic Compounds against Cetuximab-Resistant Colon Cancer Cell Lines

In the search of new natural products to be explored as possible anticancer drugs, two plant species, namely Ononis diffusa and Ononis variegata, were screened against colorectal cancer cell lines. The cytotoxic activity of the crude extracts was tested on a panel of colon cancer cell models including cetuximab-sensitive (Caco-2, GEO, SW48), intrinsic (HT-29 and HCT-116), and acquired (GEO-CR, SW48-CR) cetuximab-resistant cell lines. Ononis diffusa showed remarkable cytotoxic activity, especially on the cetuximab-resistant cell lines. The active extract composition was determined by NMR analysis. Given its complexity, a partial purification was then carried out. The fractions obtained were again tested for their biological activity and their metabolite content was determined by 1D and 2D NMR analysis. The study led to the identification of a fraction enriched in oxylipins that showed a 92% growth inhibition of the HT-29 cell line at a concentration of 50 µg/mL.

The Effects of Sampling and Storage Conditions on the Metabolite Profile of the Marine Sponge Geodia barretti

Geodia barretti is a deep-sea marine sponge common in the north Atlantic and waters outside of Norway and Sweden. The sampling and subsequent treatment as well as storage of sponges for metabolomics analyses can be performed in different ways, the most commonly used being freezing (directly upon collection or later) or by storage in solvent, commonly ethanol, followed by freeze-drying. In this study we therefore investigated different sampling protocols and their effects on the detected metabolite profiles in liquid chromatography-mass spectrometry (LC-MS) using an untargeted metabolomics approach. Sponges (G. barretti) were collected outside the Swedish west coast and pieces from three sponge specimens were either flash frozen in liquid nitrogen, frozen later after the collection cruise, stored in ethanol or stored in methanol. The storage solvents as well as the actual sponge pieces were analyzed, all samples were analyzed with hydrophilic interaction liquid chromatography as well as reversed phase liquid chromatography with high resolution mass spectrometry using full-scan in positive and negative ionization mode. The data were evaluated using multivariate data analysis. The highest metabolite intensities were found in the frozen samples (flash frozen and frozen after sampling cruise) as well as in the storage solvents (methanol and ethanol). Metabolites extracted from the sponge pieces that had been stored in solvent were found in very low intensity, since the majority of metabolites were extracted to the solvents to a high degree. The exception being larger peptides and some lipids. The lowest variation between replicates were found in the flash frozen samples. In conclusion, the preferred method for sampling of sponges for metabolomics was found to be immediate freezing in liquid nitrogen. However, freezing the sponge samples after some time proved to be a reliable method as well, albeit with higher variation between the replicates. The study highlights the importance of saving ethanol extracts after preservation of specimens for biology studies; these valuable extracts could be further used in studies of natural products, chemosystematics or metabolomics.