Mass Spectrometry-Based Untargeted Plant Metabolomics

Synergy of Analytical Characterization and Biocompatible Extractions for the Enhancement of High-Quality Biorefinery Products from Medicago sativa

This study presents the development of an analytical characterization strategy tailored to end products derived from an alfalfa (Medicago sativa)-based biorefinery with particular emphasis on protein concentrates and phenolic-enriched fractions. Our approach began with a comprehensive full-factorial experimental design aimed at optimizing the extraction process, taking care to design a biocompatible extraction protocol. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) techniques were used to characterize the molecular profile of the extracts. In particular, the extracts showed a significant relative abundance of flavonoids and isoflavonoids in both their aglycone and glycosylated forms, in which antioxidant activity was evaluated. In addition, we elucidated the proteomic profiles of the protein concentrates. This proteomic characterization served as a valuable resource for understanding the differences between these end products, providing insights that can guide informed decisions about their potential applications.

Kiwifruit spatiotemporal multiomics networks uncover key tissue-specific regulatory processes throughout the life cycle

Kiwifruit (Actinidia chinensis), a recently commercialized horticultural crop, is rich in various nutrient compounds. However, the regulatory networks controlling the dynamic changes in key metabolites among different tissues remain largely unknown. Here, high-resolution spatiotemporal datasets obtained by ultraperformance liquid chromatography-tandem mass spectrometry methodology and RNA-seq were employed to investigate the dynamic changes in the metabolic and transcriptional landscape of major kiwifruit tissues across different developmental stages, including from fruit skin, outer pericarp, inner pericarp, and fruit core. Kiwifruit spatiotemporal regulatory networks (KSRN) were constructed by integrating the 1,243 identified metabolites and co-expressed genes into 10 different clusters and 11 modules based on their biological functions. These networks allowed the generation of a global map for the major metabolic and transcriptional changes occurring throughout the life cycle of different kiwifruit tissues and discovery of the underlying regulatory networks. KSRN predictions confirmed previously established regulatory networks, including the spatiotemporal accumulation of anthocyanin and ascorbic acid (AsA). More importantly, the networks led to the functional characterization of three transcription factors: an A. chinensis ethylene response factor 1, which negatively controls sugar accumulation and ethylene production by perceiving the ripening signal, a basic-leucine zipper 60 (AcbZIP60) transcription factor, which is involved in the biosynthesis of AsA as part of the L-galactose pathway, and a transcription factor related to apetala 2.4 (RAP2.4), which directly activates the expression of the kiwi fruit aroma terpene synthase gene AcTPS1b. Our findings provide insights into spatiotemporal changes in kiwifruit metabolism and generate a valuable resource for the study of metabolic regulatory processes in kiwifruit as well as other fruits.

Optimizing ultrasonication-assisted comprehensive extraction of bioactive flavonoids from Pterocarpus santalinus leaves using response surface methodology

The leaves of Pterocarpus santalinus have been identified as a good source of health-beneficial flavonoids through the amalgamation of untargeted metabolomics using UHPLC-ESI-MSn leading to the identification of flavone-glycosides bearing isorhamnetin and quercetin skeletons. To unveil the optimum ultrasonication extraction conditions required for the comprehensive extraction of major flavone-glycosides, isorhamnetin-3-O-β-d-(2-O-α-L-rhamnopyranosyl)glucopyranoside and isorhamnetin-3-O-β-d-glucopyranoside, the response surface methodology based on Box-Behnken design was adopted. The influence of input extraction parameters extraction time (X1): 15-45 min, temperature (X2): 40-60 °C and biomass-solvent ratio (X3): 60-100 on the extractive yield and comprehensive flavonoid content resulted in the optimal conditions as 19.09 min, 48.65 oC, and 72.15, respectively. The investigation provides a sustainable approach for recovering health-beneficial flavone-glycosides for utilization in various industries.

Molecular Networks as Strategy for Dereplication of Steroidal Alkaloids of Herbarium Samples of Solanum jabrense Agra and M. Nee, an Endemic and Unexplored Species

Solanum jabrense is an endemic species from Brazil, distributed in the phytogeographic domains of the Caatinga and Atlantic Forest, in the states of Northeast. Solanum L. species have great economic importance not only because they are used in human food, but also because they present several secondary metabolites, especially glycosylated steroidal alkaloids, giving them medicinal properties. Recently, dry herbarium specimens have been used to identify metabolites of interest preserved even after years of storage, using a simple and fast method of extraction and analysis by liquid chromatography (LC) coupled to mass spectrometry (MS). Dereplication techniques aided by molecular networks (MNs) were used to analyze the chemical composition from samples of S. jabrense herbarium specimens and to identify chemical markers and bioactive molecules with potential medicinal use. From the LC-MS/MS dataset of the crude extracts and a standard (solasodine), an MN was generated that resulted in the dereplication of 19 spirosolane-type alkaminas. Our results suggest that dereplication using fragments of dried Solanum specimens is a quick tool to identify potential conserved metabolites, being useful not only for chemotaxonomy and metabolomic but also for the discovery of new molecules in natural products.

Analysis of the quadruple lsu mutant reveals molecular determinants of the role of LSU proteins in sulfur assimilation in Arabidopsis

Because plants are immobile, they have developed intricate mechanisms to sense and absorb nutrients, adjusting their growth and development accordingly. Sulfur is an essential macroelement, but our understanding of its metabolism and homeostasis is limited. LSU (RESPONSE TO LOW SULFUR) proteins are plant-specific proteins with unknown molecular functions and were first identified during transcriptomic studies on sulfur deficiency in Arabidopsis. These proteins are crucial hubs that integrate environmental signals and are involved in the response to various stressors. Herein, we report the direct involvement of LSU proteins in primary sulfur metabolism. Our findings revealed that the quadruple lsu mutant, q-lsu-KO, which was grown under nonlimiting sulfate conditions, exhibited a molecular response resembling that of sulfur-deficient wild-type plants. This led us to explore the interactions of LSU proteins with sulfate reduction pathway enzymes. We found that all LSU proteins interact with ATPS1 and ATPS3 isoforms of ATP sulfurylase, all three isoforms of adenosine 5´ phosphosulfate reductase (APR), and sulfite reductase (SiR). Additionally, in vitro assays revealed that LSU1 enhances the enzymatic activity of SiR. These results highlight the supportive role of LSU proteins in the sulfate reduction pathway.

Untargeted Metabolite Profiling of Wild and In Vitro Propagated Sabah Jewel Orchid Macodes limii J.J. Wood & A.L. Lamb

Macodes limii J.J. Wood & A.L. Lamb is a terrestrial jewel orchid native to Sabah, recognised for its sparkling golden-yellow venations, uniformly distributed on its leaves. Despite its high ornamental value, the exploration of the plant's medicinal potential remains ambiguous. The current study was conducted to gain a fundamental understanding of the metabolite composition and regulation in M. limii plants from two different growing environments: wild and in vitro cultivation, as well as to analyse their phytochemical contents and antioxidant activity. The metabolite profiling of the M . limii plant extracts through gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis has tentatively identified compounds from various classes including sugars, carbohydrates, sugar alcohols, amino acids, organic acids, phenolic derivatives and lipid and lipid-like compounds. Subsequently, the multivariate statistical analysis confirmed the existence of significant metabolite variations across distinct growth environments. Notably, the leaf extract derived from wild-grown plants displayed the highest levels of total phenolic and flavonoid content, contributing significantly to its higher antioxidant activity as measured by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. The discovery has offered a fundamental understanding of the metabolites in M. limii jewel orchids, indicating that in vitro regenerated plants may represent a viable alternative for further investigating their therapeutic potential, thus helping to alleviate the impact on wild populations.

An Expedited Qualitative Profiling of Free Amino Acids in Plant Tissues Using Liquid Chromatography-Mass Spectrometry (LC-MS) in Conjunction With MS-DIAL

The estimation of relative levels of amino acids is crucial for understanding various biological processes in plants, including photosynthesis, stress tolerance, and the uptake and translocation of nutrients. A wide range of liquid chromatography (LC; HPLC/UHPLC)-based methods is available for measuring the quantity of amino acids in plants. Additionally, the coupling of LC with mass spectrometry (MS) significantly enhanced the robustness of existing chromatographic methods used for amino acid quantification. However, accurate annotation and integration of mass peaks can be challenging for plant biologists with limited experience in analyzing MS data, especially in studies involving large datasets with multiple treatments and/or replicates. Further, there are instances when the experiment demands an overall view of the amino acids profile rather than focusing on absolute quantification. The present protocol provides a detailed LC-MS method for obtaining a qualitative amino acids profile using MS-DIAL, a versatile and user-friendly program for processing MS data. Free amino acids were extracted from the leaves of control and Tomato leaf curl Palampur virus (ToLCPalV)-infected Nicotiana benthamiana plants. Extracted amino acids were derivatized and separated using UHPLC-QTOF, with each amino acid subsequently identified by aligning mass data with a custom text library created in MS-DIAL. Further, MS-DIAL was employed for internal standard-based normalization to obtain a qualitative profile of 15 amino acids in control and virus-infected plants. The outlined method aims to simplify the processing of MS data to quickly assess any modulation in amino acid levels in plants with a higher degree of confidence.

The marriage between stable isotope ecology and plant metabolomics - new perspectives for metabolic flux analysis and the interpretation of ecological archives

Even though they share many thematical overlaps, plant metabolomics and stable isotope ecology have been rather separate fields mainly due to different mass spectrometry demands. New high-resolution bioanalytical mass spectrometers are now not only offering high-throughput metabolite identification but are also suitable for compound- and intramolecular position-specific isotope analysis in the natural isotope abundance range. In plant metabolomics, label-free metabolic pathway and metabolic flux analysis might become possible when applying this new technology. This is because changes in the commitment of substrates to particular metabolic pathways and the activation or deactivation of others alter enzyme-specific isotope effects. This leads to differences in intramolecular and compound-specific isotope compositions. In plant isotope ecology, position-specific isotope analysis in plant archives informed by metabolic pathway analysis could be used to reconstruct and separate environmental impacts on complex metabolic processes. A technology-driven linkage between the two disciplines could allow us to extract information on environment-metabolism interaction from plant archives such as tree rings but also within ecosystems. This would contribute to a holistic understanding of how plants react to environmental drivers, thus also providing helpful information on the trajectories of the vegetation under the conditions to come.

Unraveling the effects of drying techniques on chaya leaves: Metabolomics analysis of nonvolatile and volatile metabolites, umami taste, and antioxidant capacity

Chaya (Cnidoscolus chayamansa) leaves are known for their strong umami taste and widespread use as a dried seasoning. This study aimed to assess the impact of different drying methods [freeze drying (FD), vacuum drying, oven drying at 50 °C and 120 °C (OD120) and pan roasting (PR)] on the metabolome using mass spectrometry, umami intensity, and antioxidant properties of chaya leaves. The predominant volatile compound among all samples, 3-methylbutanal, exhibited the highest relative odor activity value (rOAV), imparting a malt-like odor, while hexanal (green grass-like odor) and 2-methylbutanal (coffee-like odor) are the second highest rOAV in the FD and PR samples, respectively. OD120 and PR samples possessed the highest levels of umami-tasting amino acids and 5'-ribonucleotides as well as the most intense umami taste, whereas FD samples exhibited the highest antioxidant capacity. These findings enhance our understanding of the aroma characteristics, umami taste, and antioxidant potential of processed chaya leaves.

Unveiling the multifaceted antiproliferative efficacy of Cichorium endivia root extract by dual modulation of apoptotic and inflammatory genes, inducing cell cycle arrest, and targeting COX-2

Chicory (Cichorium endivia L. divaricatum) is a renowned medicinal plant traditionally used for various ailments, yet the pharmacological potential of its roots, particularly in terms of antitumor activity, remains elusive. In the present study, we explore, for the first time, the metabolomic profile of ethanolic extract from Cichorium endivia roots (CIR) and further unveil its antiproliferative potential. The untargeted phytochemical analysis UPLC/T-TOF-MS/MS identified 131 metabolites in the CIR extract, covering acids, amino acids, flavonoids, alkaloids, nucleotides, and carbohydrates. The antiproliferative activity of the CIR extract was tested in 14 cancer cell lines, revealing significant cytotoxicity (IC50: 2.85-29.15 μg mL-1) and a high selectivity index. Among the cells examined, the CIR extract recorded the most potent antiproliferative activity and selectivity toward HepG2 and Panc-1 cells, with an IC50 of 2.85 μg mL-1 and 3.86 μg mL-1, respectively, and SI > 10. Insights into the mode of action of the antiproliferative activity revealed that CIR extract induces cell arrest in the S phase while diminishing cell distribution in the G0/G1 and G2/M phases in HepG-2 and Panc-1 cells. Flow cytometric and RT-PCR analysis revealed that the CIR extract significantly triggers apoptosis and modulates the expression of pro-apoptotic and anti-apoptotic genes. Furthermore, the CIR extract exhibited a pronounced anti-inflammatory activity, as evidenced by down-regulating key cytokines in LPS-induced RAW 264.7 cells and selectively inhibiting the COX-2 enzyme. Finally, the CIR extract showed a robust total antioxidant capacity, together with potent free radicals and metal scavenging properties, highlighting its role in alleviating oxidative stress. Taken together, this study highlights the multifaceted therapeutic potential of CIR extract as a natural-based antitumor supplement.

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.

Overexpression of SLIM1 transcription factor accelerates vegetative development in Arabidopsis thaliana

The transcription factor Sulfur Limitation 1 (SLIM1) belongs to the plant-specific Ethylene Insenstive3-Like transcription factor family and is known to coordinate gene expression in response to sulfur deficiency. However, the roles of SLIM1 in nutrient-sufficient conditions have not been characterized. Employing constitutive SLIM1 overexpression (35S::SLIM1) and CRISPR/Cas9 mutant plants (slim1-cr), we identified several distinct phenotypes in nutrient-sufficient conditions in Arabidopsis thaliana. Overexpression of SLIM1 results in plants with approximately twofold greater rosette area throughout vegetative development. 35S::SLIM1 plants also bolt earlier and exhibit earlier downregulation of photosynthesis-associated genes and earlier upregulation of senescence-associated genes than Col-0 and slim1-cr plants. This suggests that overexpression of SLIM1 accelerates development in A. thaliana. Genome-wide differential gene expression analysis relative to Col-0 at three time points with slim1-cr and two 35S::SLIM1 lines allowed us to identify 1,731 genes regulated directly or indirectly by SLIM1 in vivo.

Metabolism of the 4-Hydroxyphenylpyruvate Dioxygenase Inhibitor, Mesotrione, in Multiple-Herbicide-Resistant Palmer amaranth (Amaranthus palmeri)

Metabolic resistance to the maize-selective, HPPD-inhibiting herbicide, mesotrione, occurs via Phase I ring hydroxylation in resistant waterhemp and Palmer amaranth; however, mesotrione detoxification pathways post-Phase I are unknown. This research aims to (1) evaluate Palmer amaranth populations for mesotrione resistance via survivorship, foliar injury, and aboveground biomass, (2) determine mesotrione metabolism rates in Palmer amaranth populations during a time course, and (3) identify mesotrione metabolites including and beyond Phase I oxidation. The Palmer amaranth populations, SYNR1 and SYNR2, exhibited higher survival rates (100%), aboveground biomass (c.a. 50%), and lower injury (25-30%) following mesotrione treatment than other populations studied. These two populations also metabolized mesotrione 2-fold faster than sensitive populations, PPI1 and PPI2, and rapidly formed 4-OH-mesotrione. Additionally, SYNR1 and SYNR2 formed 5-OH-mesotrione, which is not produced in high abundance in waterhemp or naturally tolerant maize. Metabolite features derived from 4/5-OH-mesotrione and potential Phase II mesotrione-conjugates were detected and characterized by liquid chromatography-mass spectrometry (LCMS).

The role of metabolomics in informing strategies for improving photosynthesis

Photosynthesis plays a vital role in acclimating to and mitigating climate change, providing food and energy security for a population that is constantly growing, and achieving an economy with zero carbon emissions. A thorough comprehension of the dynamics of photosynthesis, including its molecular regulatory network and limitations, is essential for utilizing it as a tool to boost plant growth, enhance crop yields, and support the production of plant biomass for carbon storage. Photorespiration constrains photosynthetic efficiency and contributes significantly to carbon loss. Therefore, modulating or circumventing photorespiration presents opportunities to enhance photosynthetic efficiency. Over the past eight decades, substantial progress has been made in elucidating the molecular basis of photosynthesis, photorespiration, and the key regulatory mechanisms involved, beginning with the discovery of the canonical Calvin-Benson-Bassham cycle. Advanced chromatographic and mass spectrometric technologies have allowed a comprehensive analysis of the metabolite patterns associated with photosynthesis, contributing to a deeper understanding of its regulation. In this review, we summarize the results of metabolomics studies that shed light on the molecular intricacies of photosynthetic metabolism. We also discuss the methodological requirements essential for effective analysis of photosynthetic metabolism, highlighting the value of this technology in supporting strategies aimed at enhancing photosynthesis.

Identification of Stress-Responsive Metabolites in Plants Using an Untargeted Metabolomics Approach

Stress can affect different groups of plant metabolites and multiple signaling pathways. Untargeted metabolomics enables the collection of whole-spectrum data for the entire metabolite content present in plant tissues at that point in time. We present a thorough approach for large-scale, untargeted metabolomics of plant tissues using reverse-phase liquid chromatography connected to high-resolution mass spectrometry (LC-MS) of dilute methanolic extract. MZmine is a specialized computer software that automates the alignment and baseline modification of all derived mass peaks across all samples, resulting in precise information on the relative abundance of hundreds of metabolites reflected by thousands of mass signals. Further processing with statistic and bioinformatic techniques will provide a comprehensive perspective of the variations and connections among groups of samples.

Plant Tissue Culture and Metabolite Profiling for High-Value Natural Product Synthesis

The engineering of plant cell cultures to produce high-value natural products is suggested to be a safe, low-cost, and environmentally friendly route to produce a wide range of chemicals. Given that the expression of heterologous biosynthetic pathways in plant tissue culture is limited by a lack of detailed protocols, the biosynthesis of high-value metabolites in plant cell culture is constrained compared with that in microbes. However, both Arabidopsis thaliana and Nicotiana benthamiana can be efficiently transformed with multigene constructs to produce high-value natural products in stable plant cell cultures. This chapter provides a detailed protocol as to how to engineer the plant cell culture as bio-factories for metabolite biosynthesis.

Synthetic biology identifies the minimal gene set required for paclitaxel biosynthesis in a plant chassis

The diterpenoid paclitaxel (Taxol) is a chemotherapy medication widely used as a first-line treatment against several types of solid cancers. The supply of paclitaxel from natural sources is limited. However, missing knowledge about the genes involved in several specific metabolic steps of paclitaxel biosynthesis has rendered it difficult to engineer the full pathway. In this study, we used a combination of transcriptomics, cell biology, metabolomics, and pathway reconstitution to identify the complete gene set required for the heterologous production of paclitaxel. We identified the missing steps from the current model of paclitaxel biosynthesis and confirmed the activity of most of the missing enzymes via heterologous expression in Nicotiana benthamiana. Notably, we identified a new C4β-C20 epoxidase that could overcome the first bottleneck of metabolic engineering. We used both previously characterized and newly identified oxomutases/epoxidases, taxane 1β-hydroxylase, taxane 9α-hydroxylase, taxane 9α-dioxygenase, and phenylalanine-CoA ligase, to successfully biosynthesize the key intermediate baccatin III and to convert baccatin III into paclitaxel in N. benthamiana. In combination, these approaches establish a metabolic route to taxoid biosynthesis and provide insights into the unique chemistry that plants use to generate complex bioactive metabolites.

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.

Unlocking Potentially Therapeutic Phytochemicals in Capadulla (Doliocarpus dentatus) from Guyana Using Untargeted Mass Spectrometry-Based Metabolomics

Doliocarpus dentatus is thought to have a wide variety of therapeutic phytochemicals that allegedly improve libido and cure impotence. Although a few biomarkers have been identified with potential antinociceptive and cytotoxic properties, an untargeted mass spectrometry-based metabolomics approach has never been undertaken to identify therapeutic biofingerprints for conditions, such as erectile dysfunction, in men. This study executes a preliminary phytochemical screening of the woody vine of two ecotypes of D. dentatus with renowned differences in therapeutic potential for erectile dysfunction. Liquid chromatography-mass spectrometry-based metabolomics was used to screen for flavonoids, terpenoids, and other chemical classes found to contrast between red and white ecotypes. Among the metabolite chemodiversity found in the ecotype screens, using a combination of GNPS, MS-DIAL, and SIRIUS, approximately 847 compounds were annotated at levels 2 to 4, with the majority of compounds falling under lipid and lipid-like molecules, benzenoids and phenylpropanoids, and polyketides, indicative of the contributions of the flavonoid, shikimic acid, and terpenoid biosynthesis pathways. Despite the extensive annotation, we report on 138 tentative compound identifications of potentially therapeutic compounds, with 55 selected compounds at a level-2 annotation, and 22 statistically significant therapeutic biomarkers, the majority of which were polyphenols. Epicatechin methyl gallate, catechin gallate, and proanthocyanidin A2 had the greatest significant differences and were also relatively abundant among the red and white ecotypes. These putatively identified compounds reportedly act as antioxidants, neutralizing damaging free radicals, and lowering cell oxidative stress, thus aiding in potentially preventing cellular damage and promoting overall well-being, especially for treating erectile dysfunction (ED).

Diverse forage improves lipid metabolism and antioxidant capacity in goats, as revealed by metabolomics

It is well established that promoting the balance of nutrients and plant secondary metabolites (PSM) by feeding diverse forage physiologically improves ruminant production. However, the underlying mechanism remains unclear. To investigate the physiological mechanism related to the improvement of physiological stress tolerance, ruminants were fed diverse forage. Oxidative stress markers were quantified, and serum metabolomics was performed. Six crossbred Shiba wethers (32.8 ± 9.2 kg BW) were arranged in a replicated 3 × 3 Latin square design. The treatments were feeding only Sudan grass hay (100% SDN); feeding a mixture of Sudan grass and alfalfa hay (70:30, SDN-ALF); and feeding a mixture of Sudan grass, timothy grass, and alfalfa hay (35:35:30; SDN-TMT-ALF). Each diet group was fed its specific diet for 21 days with a 14-day adaptation period. Feed intake and digestibility, blood biochemistry, total antioxidant capacity (TAC), and superoxide dismutase (SOD) were analysed. In addition, blood serum metabolites were assessed by liquid chromatography-tandem mass spectrometry. The DM intake and DM, organic matter, and CP digestibility were higher (P < 0.05) in the SDN-TMT-ALF group than in the SDN group. The TAC was higher (P < 0.01) in the SDN-TMT-ALF and SDN-ALF groups (809.51 and 813.7 µM, respectively) than the SDN group (720.69 µM), while the SOD level was unchanged (P = 0.06) among the treatments. Total serum cholesterol and NH3 levels were higher (P < 0.05) in the SDN-TMT-ALF group (89.17 mg/dL and 242.42 µg/dL, respectively) than in the SDN group (71.00 mg/dL and 89.17 µg/dL). Additionally, the levels of nine metabolites in serum differed among the treatments (P < 0.05). Linoleic acid (LA) and cortisone, which are related to LA metabolism and the steroid biosynthesis pathway, were upregulated by the SDN-ALF and SDN-TMT-ALF diets compared to the SDN diet, suggesting the contribution of ALF to altering the metabolites. The levels of hippuric acid, which is a metabolite of phenolic compounds, were higher (P < 0.001) in the animals fed SDN, which contained higher phenolic and luteolin concentrations than the other diets. Pathway analysis suggested that the higher cortisone levels were derived from cholesterol due to upregulated glycolysis metabolism, which was positively related to increased ingestion, digestibility, and serum LA levels in animals given mixed forage. In conclusion, physiological stress tolerance in the animals was regulated by upregulation of LA and steroid hormone metabolism, which was associated with an increase in TAC rather than the ability of the animal to regulate its PSM intake.

Mass spectrometry-based approaches to assess the botanical authenticity of dietary supplements

Dietary supplements are legally considered foods despite frequently including medicinal plants as ingredients. Currently, the consumption of herbal dietary supplements, also known as plant food supplements (PFS), is increasing worldwide and some raw botanicals, highly demanded due to their popularity, extensive use, and/or well-established pharmacological effects, have been attaining high prices in the international markets. Therefore, botanical adulteration for profit increase can occur along the whole PFS industry chain, from raw botanicals to plant extracts, until final PFS. Besides the substitution of high-value species, unintentional mislabeling can happen in morphologically similar species. Both cases represent a health risk for consumers, prompting the development of numerous works to access botanical adulterations in PFS. Among different approaches proposed for this purpose, mass spectrometry (MS)-based techniques have often been reported as the most promising, particularly when hyphenated with chromatographic techniques. Thus, this review aims at describing an overview of the developments in this field, focusing on the applications of MS-based techniques to targeted and untargeted analysis to detect botanical adulterations in plant materials, extracts, and PFS.

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.

Decreased metabolic diversity in common beans associated with domestication revealed by untargeted metabolomics, information theory, and molecular networking

The process of crop domestication leads to a dramatic reduction in the gene expression associated with metabolic diversity. Genes involved in specialized metabolism appear to be particularly affected. Although there is ample evidence of these effects at the genetic level, a reduction in diversity at the metabolite level has been taken for granted despite having never been adequately accessed and quantified. Here we leveraged the high coverage of ultra high performance liquid chromatography-high-resolution mass spectrometry based metabolomics to investigate the metabolic diversity in the common bean (Phaseolus vulgaris). Information theory highlights a shift towards lower metabolic diversity and specialization when comparing wild and domesticated bean accessions. Moreover, molecular networking approaches facilitated a broader metabolite annotation than achieved to date, and its integration with gene expression data uncovers a metabolic shift from specialized metabolism towards central metabolism upon domestication of this crop.

Mass spectrometry-based metabolomic analysis as a tool for quality control of natural complex products

Metabolomics is an area of intriguing and growing interest. Since the late 1990s, when the first Omic applications appeared to study metabolite's pool ("metabolome"), to understand new aspects of the global regulation of cellular metabolism in biology, there have been many evolutions. Currently, there are many applications in different fields such as clinical, medical, agricultural, and food. In our opinion, it is clear that developments in metabolomics analysis have also been driven by advances in mass spectrometry (MS) technology. As natural complex products (NCPs) are increasingly used around the world as medicines, food supplements, and substance-based medical devices, their analysis using metabolomic approaches will help to bring more and more rigor to scientific studies and industrial production monitoring. This review is intended to emphasize the importance of metabolomics as a powerful tool for studying NCPs, by which significant advantages can be obtained in terms of elucidation of their composition, biological effects, and quality control. The different approaches of metabolomic analysis, the main and basic techniques of multivariate statistical analysis are also briefly illustrated, to allow an overview of the workflow associated with the metabolomic studies of NCPs. Therefore, various articles and reviews are illustrated and commented as examples of the application of MS-based metabolomics to NCPs.

Methyl jasmonate elicitation effect on the metabolic profile of cambial meristematic cells culture derived from sweet basil (Ocimum basilicum L.) in relation to antioxidant activity: Untargeted metabolomics study in a time-based approach

The undifferentiated cambial meristematic cell (CMC) has been recognized as a value-added production platform for plant natural products in comparison to the dedifferentiated plant cell line (DDC). In a time-based approach at 0, 24, 48, and 72 h, the present study aimed at investigating the phytochemical metabolome of methyl jasmonate (MeJA)-elicited CMC cultures derived from sweet basil (Ocimum basilicum L.), including primary and secondary metabolites analyzed using GC/TOF-MS post-silylation and RP-UPLC-C₁₈-FT-MS/MS, respectively, as well as the analysis of aroma composition using headspace SPME-GC-MS. The results revealed a stress response in primary metabolism manifested by an increase in amino and organic acids reaching their maximum levels after 48 (1.3-fold) and 72 (1.7-fold) h, respectively. In addition, phenolic acids (e.g., sagerinic acid, rosmarinic acid, and 3-O-methylrosmarinic acid) followed by flavonoid aglycones (e.g., salvigenin and 5,6,4'-trihydroxy-7,3'-dimethoxyflavone) were the most abundant with prominent increases at 48 (1.2-fold) and 72 (2.1-fold) h, respectively. The aroma was intensified by the elicitation along the time, especially after 48 and 72 h. Furthermore, multivariate data analyses, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) confirmed elicitation effect, especially post 48 and 72 h. The study further assessed the effect of MeJA elicitation on the antioxidant and polyphenolic content. The cultures at 48 h demonstrated a significant (p < 0.05) antioxidant activity concurrently with correlation with total polyphenolic content using Pearson's correlation. Our study provides new insights to the elicitation impact on primary and secondary metabolism, in addition to aroma profile, to orchestrate the stress response and in relation to antioxidant effect.

A metabolomic platform to identify and quantify polyphenols in coffee and related species using liquid chromatography mass spectrometry

INTRODUCTION

Products of plant secondary metabolism, such as phenolic compounds, flavonoids, alkaloids, and hormones, play an important role in plant growth, development, stress resistance. The plant family Rubiaceae is extremely diverse and abundant in Central America and contains several economically important genera, e.g. Coffea and other medicinal plants. These are known for the production of bioactive polyphenols (e.g. caffeine and quinine), which have had major impacts on human society. The overall goal of this study was to develop a high-throughput workflow to identify and quantify plant polyphenols.

METHODS

First, a method was optimized to extract over 40 families of phytochemicals. Then, a high-throughput metabolomic platform has been developed to identify and quantify 184 polyphenols in 15 min.

RESULTS

The current metabolomics study of secondary metabolites was conducted on leaves from one commercial coffee variety and two wild species that also belong to the Rubiaceae family. Global profiling was performed using liquid chromatography high-resolution time-of-flight mass spectrometry. Features whose abundance was significantly different between coffee species were discriminated using statistical analysis and annotated using spectral databases. The identified features were validated by commercially available standards using our newly developed liquid chromatography tandem mass spectrometry method.

DISCUSSION

Caffeine, trigonelline and theobromine were highly abundant in coffee leaves, as expected. Interestingly, wild Rubiaceae leaves had a higher diversity of phytochemicals in comparison to commercial coffee: defense-related molecules, such as phenylpropanoids (e.g., cinnamic acid), the terpenoid gibberellic acid, and the monolignol sinapaldehyde were found more abundantly in wild Rubiaceae leaves.

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.

NMR-Based Chromatography Readouts: Indispensable Tools to “Translate” Analytical Features into Molecular Structures

Gaining structural information is a must to allow the unequivocal structural characterization of analytes from natural sources. In liquid state, NMR spectroscopy is almost the only possible alternative to HPLC-MS and hyphenating the effluent of an analyte separation device to the probe head of an NMR spectrometer has therefore been pursued for more than three decades. The purpose of this review article was to demonstrate that, while it is possible to use mass spectrometry and similar methods to differentiate, group, and often assign the differentiating variables to entities that can be recognized as single molecules, the structural characterization of these putative biomarkers usually requires the use of NMR spectroscopy.

Metabolite profiling of Arabidopsis mutants of lower glycolysis

We have previously shown that in Arabidopsis the three enzymes of lower glycolysis namely phosphoglycerate mutase (PGAM), enolase and pyruvate kinase form a complex which plays an important role in tethering the mitochondria to the chloroplast. Given that the metabolism of these mutants, the complemented of pgam mutant and overexpression lines of PGAM were unclear, here, we present gas chromatography mass spectrometry-based metabolomics data of them alongside their plant growth phenotypes. Compared with wild type, both sugar and amino acid concentration are significantly altered in phosphoglycerate mutase, enolase and pyruvate kinase. Conversely, overexpression of PGAM could decrease the content of 3PGA, sugar and several amino acids and increase the content of alanine and pyruvate. In addition, the pgam mutant could not be fully complemented by either a nuclear target pgam, a side-directed-mutate of pgam or a the E.coli PGAM in term of plant phenotype or metabolite profiles, suggesting the low glycolysis complete formation is required to support normal metabolism and growth.

Exact mass GC-MS analysis: Protocol, database, advantages and application to plant metabolic profiling

Plant metabolomics has been used widely in plant physiology, in particular to analyse metabolic responses to environmental parameters. Derivatization (via trimethylsilylation and methoximation) followed by GC-MS metabolic profiling is a major technique to quantify low molecular weight, common metabolites of primary carbon, sulphur and nitrogen metabolism. There are now excellent opportunities for new generation analyses, using high resolution, exact mass GC-MS spectrometers that are progressively becoming relatively cheap. However, exact mass GC-MS analyses for routine metabolic profiling are not common, since there is no dedicated available database. Also, exact mass GC-MS is usually dedicated to structural resolution of targeted secondary metabolites. Here, we present a curated database for exact mass metabolic profiling (made of 336 analytes, 1064 characteristic exact mass fragments) focused on molecules of primary metabolism. We show advantages of exact mass analyses, in particular to resolve isotopic patterns, localise S-containing metabolites, and avoid identification errors when analytes have common nominal mass peaks in their spectrum. We provide a practical example using leaves of different Arabidopsis ecotypes and show how exact mass GC-MS analysis can be applied to plant samples and identify metabolic profiles.

Genome assembly and chemogenomic profiling of National Flower of Singapore Papilionanthe Miss Joaquim 'Agnes' reveals metabolic pathways regulating floral traits

Singapore's National Flower, Papilionanthe (Ple.) Miss Joaquim 'Agnes' (PMJ) is highly prized as a horticultural flower from the Orchidaceae family. A combination of short-read sequencing, single-molecule long-read sequencing and chromatin contact mapping was used to assemble the PMJ genome, spanning 2.5 Gb and 19 pseudo-chromosomal scaffolds. Genomic resources and chemical profiling provided insights towards identifying, understanding and elucidating various classes of secondary metabolite compounds synthesized by the flower. For example, presence of the anthocyanin pigments detected by chemical profiling coincides with the expression of ANTHOCYANIN SYNTHASE (ANS), an enzyme responsible for the synthesis of the former. Similarly, the presence of vandaterosides (a unique class of glycosylated organic acids with the potential to slow skin aging) discovered using chemical profiling revealed the involvement of glycosyltransferase family enzymes candidates in vandateroside biosynthesis. Interestingly, despite the unnoticeable scent of the flower, genes involved in the biosynthesis of volatile compounds and chemical profiling revealed the combination of oxygenated hydrocarbons, including traces of linalool, beta-ionone and vanillin, forming the scent profile of PMJ. In summary, by combining genomics and biochemistry, the findings expands the known biodiversity repertoire of the Orchidaceae family and insights into the genome and secondary metabolite processes of PMJ.

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.

I, Deniega FM, Delica K, Fernandez K, Lebrilla CB, Manalo MN, Heralde III FM, Completo GCJ, Nacario RC. Biological Assay-Guided Fractionation and Mass Spectrometry-Based Metabolite Profiling of Annona muricata L. Cytotoxic Compounds against Lung Cancer A549 Cell Line

Annona muricata L. (Guyabano) leaves are reported to exhibit anticancer activity against cancer cells. In this study, the ethyl acetate extract from guyabano leaves was purified through column chromatography, and the cytotoxic effects of the semi-purified fractions were evaluated against A549 lung cancer cells using in vitro MTS cytotoxicity and scratch/wound healing assays. Fractions F15-16C and F15-16D exhibited the highest anticancer activity in the MTS assay, with % cytotoxicity values of 99.6% and 99.4%, respectively. The bioactivity of the fractions was also consistent with the results of the scratch/wound healing assay. Moreover, untargeted metabolomics was employed on the semi-purified fractions to determine the putative compounds responsible for the bioactivity. The active fractions were processed using LC-MS/MS analysis with the integration of the following metabolomic tools: MS-DIAL (for data processing), MetaboAnalyst (for data analysis), GNPS (for metabolite annotation), and Cytoscape (for network visualization). Results revealed that the putative compounds with a significant difference between active and inactive fractions in PCA and OPLS-DA models were pheophorbide A and diphenylcyclopropenone.

Metabolomic analysis of sheath blight disease of rice (Oryza sativa L.) induced by Rhizoctonia solani phytotoxin

AIM

To understand the mechanism of necrosis incited by a host-selective phytotoxin designated as Rhizoctonia solani toxin (RST) identified to be a potential pathogenic factor of Rhizoctonia solani AG1 IA, causing sheath blight (ShB) of rice.

METHODS AND RESULTS

The metabolomic changes induced by the phytotoxic metabolite in a ShB susceptible rice cultivar were elucidated by Gas Chromatography-Mass Spectrometry (GC-MS) analysis and compared with that of the pathogen to identify rice metabolites targeted by the phytotoxin. The profiles of about 29 metabolites with various physiological roles in rice plants have been identified worldwide. Unsupervised and supervised multivariate chemometrics (Principal Component Analysis, PCA and Partial Least Squares-Discriminant Analysis, PLS-DA) and cluster (Heat maps) analyses were used to compare the metabolites obtained from chemical profiles of the treatments with sterile distilled water (SDW) control. The results indicated that the rice plant expressed more metabolites in response to the pathogen than the phytotoxin and was lowest in SDW control. The key metabolites expressed in rice in response to the treatments were investigated by the Variable Importance in Projection (VIP) analysis using P< 0.05 VIP >15. The analysis identified 7 and 11 upregulating metabolites in the phytotoxin and the pathogen treatments, respectively, compared to the untreated control. Among the phytotoxin-treated and the pathogen inoculated samples, the phytotoxin treated sample recorded upregulation of 6 metabolites, whereas 9 metabolites were upregulated in the pathogen inoculated samples. These upregulating metabolites are speculated for the necrotic symptoms characteristic to both the phytotoxin and pathogen. In this analysis, hexadecanoic acid and dotriacontane were highly expressed metabolites specific to the phytotoxin and pathogen-treated samples, respectively. Besides upregulation, the metabolites also have a VIP score of >1.5 and hence fulfilled the criteria of classifying them as reliable potential biomarkers. In the pathway analysis, hexadecanoic acid and dotriacontane were identified to be involved in several important biosynthetic pathways of rice, such as the biosynthesis of saturated fatty acid and unsaturated fatty acids cutin, suberin, and wax.

CONCLUSIONS

The study concludes that though certain metabolites induced by the phytotoxin in the susceptible variety during necrosis shares with that of the pathogen, the identification of metabolites specific to the phytotoxin in comparison to the pathogenic and SDW controls indicated that the phytotoxin modulates the host metabolism differently and hence can be a potential pathogenicity factor of the ShB fungus.

SIGNIFICANCE AND IMPACT OF THE STUDY

Due to lack of knowledge on the pathway genes of RST and in the absence of an ShB resistant variety, understanding differentially expressed metabolic changes induced in the susceptible variety by the phytotoxin in comparison to that of the pathogenic and uninoculated controls enables us to identify the key metabolite changes during the ShB infection. Such metabolomic changes can further be used to infer gene functions for exploitation in ShB control.

Carbon pathways during transitory starch degradation in Arabidopsis differentially affect the starch granule number and morphology in the dpe2/phs1 mutant background

The Arabidopsis knockout mutant lacking both the cytosolic disproportionating enzyme 2 (DPE2) and the plastidial phosphorylase (PHS1) had a dwarf-growth phenotype, a reduced and uneven distribution of starch within the plant rosettes, and a lower starch granule number per chloroplast under standard growth conditions. In contrast, a triple mutant impaired in starch degradation by its additional lack of the glucan, water dikinase (GWD) showed improved plant growth, a starch-excess phenotype, and a homogeneous starch distribution. Furthermore, the number of starch granules per chloroplast was increased and was similar to the wild type. We concluded that ongoing starch degradation is mainly responsible for the observed phenotype of dpe2/phs1. Next, we generated two further triple mutants lacking either the phosphoglucan, water dikinase (PWD), or the disproportionating enzyme 1 (DPE1) in the background of the double mutant. Analysis of the starch metabolism revealed that even minor ongoing starch degradation observed in dpe2/phs1/pwd maintained the double mutant phenotype. In contrast, an additional blockage in the glucose pathway of starch breakdown, as in dpe2/phs1/dpe1, resulted in a nearly starch-free phenotype and massive chloroplast degradation. The characterized mutants were discussed in the context of starch granule formation.

Regulatory Modules of Metabolites and Protein Phosphorylation in Arabidopsis Genotypes With Altered Sucrose Allocation

Multi-omics data sets are increasingly being used for the interpretation of cellular processes in response to environmental cues. Especially, the posttranslational modification of proteins by phosphorylation is an important regulatory process affecting protein activity and/or localization, which, in turn, can have effects on metabolic processes and metabolite levels. Despite this importance, relationships between protein phosphorylation status and metabolite abundance remain largely underexplored. Here, we used a phosphoproteomics-metabolomics data set collected at the end of day and night in shoots and roots of Arabidopsis to propose regulatory relationships between protein phosphorylation and accumulation or allocation of metabolites. For this purpose, we introduced a novel, robust co-expression measure suited to the structure of our data sets, and we used this measure to construct metabolite-phosphopeptide networks. These networks were compared between wild type and plants with perturbations in key processes of sugar metabolism, namely, sucrose export (sweet11/12 mutant) and starch synthesis (pgm mutant). The phosphopeptide-metabolite network turned out to be highly sensitive to perturbations in sugar metabolism. Specifically, KING1, the regulatory subunit of SnRK1, was identified as a primary candidate connecting protein phosphorylation status with metabolism. We additionally identified strong changes in the fatty acid network of the sweet11/12 mutant, potentially resulting from a combination of fatty acid signaling and metabolic overflow reactions in response to high internal sucrose concentrations. Our results further suggest novel protein-metabolite relationships as candidates for future targeted research.

Chloroplast translational regulation uncovers nonessential photosynthesis genes as key players in plant cold acclimation

Plants evolved efficient multifaceted acclimation strategies to cope with low temperatures. Chloroplasts respond to temperature stimuli and participate in temperature sensing and acclimation. However, very little is known about the involvement of chloroplast genes and their expression in plant chilling tolerance. Here we systematically investigated cold acclimation in tobacco seedlings over 2 days of exposure to low temperatures by examining responses in chloroplast genome copy number, transcript accumulation and translation, photosynthesis, cell physiology, and metabolism. Our time-resolved genome-wide investigation of chloroplast gene expression revealed substantial cold-induced translational regulation at both the initiation and elongation levels, in the virtual absence of changes at the transcript level. These cold-triggered dynamics in chloroplast translation are widely distinct from previously described high light-induced effects. Analysis of the gene set responding significantly to the cold stimulus suggested nonessential plastid-encoded subunits of photosynthetic protein complexes as novel players in plant cold acclimation. Functional characterization of one of these cold-responsive chloroplast genes by reverse genetics demonstrated that the encoded protein, the small cytochrome b6f complex subunit PetL, crucially contributes to photosynthetic cold acclimation. Together, our results uncover an important, previously underappreciated role of chloroplast translational regulation in plant cold acclimation.

Molecular networking and collision cross section prediction for structural isomer and unknown compound identification in plant metabolomics: a case study applied to Zhanthoxylum heitzii extracts

Mass spectrometry-based plant metabolomics allow large-scale analysis of a wide range of compounds and the discovery of potential new active metabolites with minimal sample preparation. Despite recent tools for molecular networking, many metabolites remain unknown. Our objective is to show the complementarity of collision cross section (CCS) measurements and calculations for metabolite annotation in a real case study. Thus, a systematic and high-throughput investigation of root, bark, branch, and leaf of the Gabonese plant Zhanthoxylum heitzii was performed through ultra-high performance liquid chromatography high-resolution tandem mass spectrometry (UHPLC-QTOF/MS). A feature-based molecular network (FBMN) was employed to study the distribution of metabolites in the organs of the plants and discover potential new components. In total, 143 metabolites belonging to the family of alkaloids, lignans, polyphenols, fatty acids, and amino acids were detected and a semi-quantitative analysis in the different organs was performed. A large proportion of medical plant phytochemicals is often characterized by isomerism and, in the absence of reference compounds, an additional dimension of gas phase separation can result in improvements to both quantitation and compound annotation. The inclusion of ion mobility in the ultra-high performance liquid chromatography mass spectrometry workflow (UHPLC-IMS-MS) has been used to collect experimental CCS values in nitrogen and helium (CCS_N2 and CCS_He) of Zhanthoxylum heitzii features. Due to a lack of reference data, the investigation of predicted collision cross section has enabled comparison with the experimental values, helping in dereplication and isomer identification. Moreover, in combination with mass spectra interpretation, the comparison of experimental and theoretical CCS values allowed annotation of unknown features. The study represents a practical example of the potential of modern mass spectrometry strategies in the identification of medicinal plant phytochemical components.

Adverse Effects of Arsenic Uptake in Rice Metabolome and Lipidome Revealed by Untargeted Liquid Chromatography Coupled to Mass Spectrometry (LC-MS) and Regions of Interest Multivariate Curve Resolution

Rice crops are especially vulnerable to arsenic exposure compared to other cereal crops because flooding growing conditions facilitates its uptake. Besides, there are still many unknown questions about arsenic’s mode of action in rice. Here, we apply two untargeted approaches using liquid chromatography coupled to mass spectrometry (LC-MS) to unravel the effects on rice lipidome and metabolome in the early stages of growth. The exposure is evaluated through two different treatments, watering with arsenic-contaminated water and soil containing arsenic. The combination of regions of interest (ROI) and multivariate curve resolution (MCR) strategies in the ROIMCR data analyses workflow is proposed and complemented with other multivariate analyses such as partial least square discriminant analysis (PLS-DA) for the identification of potential markers of arsenic exposure and toxicity effects. The results of this study showed that rice metabolome (and lipidome) in root tissues seemed to be more affected by the watering and soil treatment. In contrast, aerial tissues alterations were accentuated by the arsenic dose, rather than with the watering and soil treatment itself. Up to a hundred lipids and 40 metabolites were significantly altered due to arsenic exposure. Major metabolic alterations were found in glycerophospholipids, glycerolipids, and amino acid-related pathways.

Rice metabolic regulatory network spanning the entire life cycle

As one of the most important crops in the world, rice (Oryza sativa) is a model plant for metabolome research. Although many studies have focused on the analysis of specific tissues, the changes in metabolite abundance across the entire life cycle have not yet been determined. In this study, combining both targeted and nontargeted metabolite profiling methods, a total of 825 annotated metabolites were quantified in rice samples from different tissues covering the entire life cycle. The contents of metabolites in different tissues of rice were significantly different, with various metabolites accumulating in the plumule and radicle during seed germination. Combining these data with transcriptome data obtained from the same time period, we constructed the Rice Metabolic Regulation Network. The metabolites and co-expressed genes were further divided into 12 clusters according to their accumulation patterns, with members within each cluster displaying a uniform and clear pattern of abundance across development. Using this dataset, we established a comprehensive metabolic profile of the rice life cycle and used two independent strategies to identify novel transcription factors-namely the use of known regulatory genes as bait to screen for new networks underlying lignin metabolism and the unbiased identification of new glycerophospholipid metabolism regulators on the basis of tissue specificity. This study thus demonstrates how guilt-by-association analysis of metabolome and transcriptome data spanning the entire life cycle in cereal crops provides novel resources and tools to aid in understanding the mechanisms underlying important agronomic traits.

Metabolism-mediated mechanisms underpin the differential stomatal speediness regulation among ferns and angiosperms

Recent results suggest that metabolism-mediated stomatal closure mechanisms are important to regulate differentially the stomatal speediness between ferns and angiosperms. However, evidence directly linking mesophyll metabolism and the slower stomatal conductance (g_s ) in ferns is missing. Here, we investigated the effect of exogenous application of abscisic acid (ABA), sucrose and mannitol on stomatal kinetics and carried out a metabolic fingerprinting analysis of ferns and angiosperms leaves harvested throughout a diel course. Fern stomata did not respond to ABA in the time period analysed. No differences in the relative decrease in g_s was observed between ferns and the angiosperm following provision of sucrose or mannitol. However, ferns have slower g_s responses to these compounds than angiosperms. Metabolomics analysis highlights that ferns have a higher accumulation of secondary rather than primary metabolites throughout the diel course, with the opposite being observed in angiosperms. Our results indicate that metabolism-mediated stomatal closure mechanisms underpin the differential stomatal speediness regulation among ferns and angiosperms, in which the slower stomatal closure in ferns is associated with the lack of ABA-responsiveness, to a reduced capacity to respond to mesophyll-derived sucrose and to a higher carbon allocation toward secondary metabolism, which likely modulates both photosynthesis-g_s and growth-stress tolerance trade-offs.

Preparation and Curation of Omics Data for Genome-Wide Association Studies

With the development of large-scale molecular phenotyping platforms, genome-wide association studies have greatly developed, being no longer limited to the analysis of classical agronomic traits, such as yield or flowering time, but also embracing the dissection of the genetic basis of molecular traits. Data generated by omics platforms, however, pose some technical and statistical challenges to the classical methodology and assumptions of an association study. Although genotyping data are subject to strict filtering procedures, and several advanced statistical approaches are now available to adjust for population structure, less attention has been instead devoted to the preparation of omics data prior to GWAS. In the present chapter, we briefly present the methods to acquire profiling data from transcripts, proteins, and small molecules, and discuss the tools and possibilities to clean, normalize, and remove the unwanted variation from large datasets of molecular phenotypic traits prior to their use in GWAS.

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.

A novel multidimensional strategy to evaluate Belamcanda chinensis (L) DC and Iris tectorum Maxim based on plant metabolomics, digital reference standard analyzer and biological activities evaluation

BACKGROUND

Belamcanda chinensis (L.) DC. (BC) belongs to the family of Iridaceae and is widely cultivated and used in many Chinese patent medicine and Chinese medicinal formulae. However, due to the high similarities in appearance such as color and shape to Iris tectorum Maxim (ITM), another plant from the same family, BC is often confused or even misused with ITM.

METHODS

Therefore, in order to distinguish the chemical constituents, qualities and biological activities of BC and ITM, multiple technologies including plant metabolomics, digital reference standard (DRS) analyzer and biological activities assay were employed to provide a sufficient basis for their practical applications.

RESULTS

In plant metabolomics, the PCA and OPLS-DA score plot indicated the obvious differences in chemical profiling between BC and ITM and 6 compounds were successfully identified to contribute to the differences. In DRS study, the fingerprints of 10 and 8 compounds in BC and ITM were developed based on DRS analyzer, respectively, involving relative retention time (RRT) method and linear calibration using two reference substances (LCTRS) technique. The DRS analyzer also accurately identified 10 and 8 compounds from BC and ITM, respectively, by using only two reference standards. In biological activities assay, BC had a better anticancer effect than ITM due to the high abundance of irigenin, while ITM showed stronger hepatoprotective activity than BC because of the high abundance of tectoridin.

CONCLUSIONS

Therefore, due to the significant differences of B. chinensis and I. dichotoma in chemical composition and biological activities, the current studies strongly proved that these two medicinal plants could not be mixed in industrial production and clinical medication.

Metabolomic Studies for the Evaluation of Toxicity Induced by Environmental Toxicants on Model Organisms

Environmental pollution causes significant toxicity to ecosystems. Thus, acquiring a deeper understanding of the concentration of environmental pollutants in ecosystems and, clarifying their potential toxicities is of great significance. Environmental metabolomics is a powerful technique in investigating the effects of pollutants on living organisms in the environment. In this review, we cover the different aspects of the environmental metabolomics approach, which allows the acquisition of reliable data. A step-by-step procedure from sample preparation to data interpretation is also discussed. Additionally, other factors, including model organisms and various types of emerging environmental toxicants are discussed. Moreover, we cover the considerations for successful environmental metabolomics as well as the identification of toxic effects based on data interpretation in combination with phenotype assays. Finally, the effects induced by various types of environmental toxicants in model organisms based on the application of environmental metabolomics are also discussed.

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.

Effect of Drying Methods on Volatile Compounds of Burdock (Arctium lappa L.) Root Tea as Revealed by Gas Chromatography Mass Spectrometry-Based Metabolomics

Burdock (Arctium lappa L.) is one of the nutritional foods widely planted in many countries. Dried burdock root (BR) is available as a herbal tincture and tea in many Asian countries with good flavor and taste. In this study, the volatile components in dried BR were identified and the effects of different drying methods on the volatile components were investigated by HS-GC-MS method. A total of 49 compounds were identified. Different drying methods including hot-air drying (HD, at 50, 60, 70, and 80 °C), vacuum drying (VD, at 50, 60, 70, and 80 °C), sunlight drying (SD), natural drying (ND), and vacuum freeze drying (VFD) were evaluated by HS-GC-MS-based metabolomics method. Results showed that different drying methods produced different effects on the volatile compounds. It was observed that 2,3-pentanedione, 1-(1H-pyrrol-2-yl)-ethanone, furfural, and heptanal were detected at higher concentrations in HD 80 and VD 70. The traditional HD and SD methods produced more flavor substances than VFD. The BR treated by the VFD method could maintain the shape of the fresh BR pieces while HD50 and VD80 methods could maintain the color of fresh BR pieces. These findings could help better understand the flavor of the corresponding processed BR and provide a guide for the drying and processing of BR tea.

Integrating multi-omics data for crop improvement

Our agricultural systems are now in urgent need to secure food for a growing world population. To meet this challenge, we need a better characterization of plant genetic and phenotypic diversity. The combination of genomics, transcriptomics and metabolomics enables a deeper understanding of the mechanisms underlying the complex architecture of many phenotypic traits of agricultural relevance. We review the recent advances in plant genomics to see how these can be integrated with broad molecular profiling approaches to improve our understanding of plant phenotypic variation and inform crop breeding strategies.