Search

The cloud forest (CF), a hugely biodiverse ecosystem, is a hotspot of unexplored plants with potential for discovering pharmacologically active compounds. Without sufficient ethnopharmacological information, developing strategies for rationally selecting plants for experimental studies is crucial. With this goal, a CF metabolites library was created, and a ligand-based virtual screening was conducted to identify molecules with potential hypoglycemic activity. From the most promising botanical families, plants were collected, methanolic extracts were prepared, and hypoglycemic activity was evaluated through in vitro enzyme inhibition assays on α-amylase, α-glucosidase, and dipeptidyl peptidase IV (DPP-IV). Metabolomic analyses were performed to identify the dominant metabolites in the species with the best inhibitory activity profile, and their affinity for the molecular targets was evaluated using ensemble molecular docking. This strategy led to the identification of twelve plants (in four botanical families) with hypoglycemic activity. Sida rhombifolia (Malvaceae) stood out for its DPP-IV selective inhibition versus S. glabra. A comparison of chemical profiles led to the annotation of twenty-seven metabolites over-accumulated in S. rhombifolia compared to S. glabra, among which acanthoside D and cis-tiliroside were noteworthy for their potential selective inhibition due to their specific intermolecular interactions with relevant amino acids of DPP-IV. The workflow used in this study presents a novel targeting strategy for identifying novel bioactive natural sources, which can complement the conventional selection criteria used in Natural Product Chemistry. [ABSTRACT FROM AUTHOR]

Drug development from medicinal plants constitutes an important strategy for finding natural anticancer therapies. While several plant secondary metabolites with potential antitumor activities have been identified, well-defined mechanisms of action remained uncovered. In fact, studies of medicinal plants have often focused on the genome, transcriptome, and proteome, dismissing the relevance of the metabolome for discovering effective plant-based drugs. Metabolomics has gained huge interest in cancer research as it facilitates the identification of potential anticancer metabolites and uncovers the metabolomic alterations that occur in cancer cells in response to treatment. This holds great promise for investigating the mode of action of target metabolites. Although metabolomics has made significant contributions to drug discovery, research in this area is still ongoing. In this review, we emphasize the significance of plant metabolomics in anticancer research, which continues to be a potential technique for the development of anticancer drugs in spite of all the challenges encountered. As well, we provide insights into the essential elements required for performing effective metabolomics analyses. [ABSTRACT FROM AUTHOR]

Summary: Polygonum minus (PM) has a rich traditional usage for health benefits, yet its potential as a natural‐based solution for obesity management remains unexplored. This study evaluated the antioxidant properties, inhibition of pancreatic lipase and α‐glucosidase activities, and metabolite profiles of PM aerial extracts harvested at 8, 10, and 12 weeks using 1H NMR‐based metabolomics. PM harvested at 12 weeks exhibited significant antioxidant and enzyme inhibition activities. NMR metabolomics unveiled nine major metabolites correlated to the bioactivities of 12‐week PM. LC–MS/MS profiling enabled the identification of flavonoids and phenolic acids, with the majority having sulfate, gallate, and glycoside moieties. Notably, in vivo experiments demonstrated that rats treated with 200 mg kg−1 and 400 mg kg−1 PM exhibited significantly lower (P < 0.05) total body weight gain (39.03% and 52.59%, respectively) compared to negative control rats (69.95%), with the lower dose group also exhibiting reduced (P < 0.05) fasting blood glucose levels. This study highlights the potential of 12‐week PM as a natural‐based solution in obesity management. [ABSTRACT FROM AUTHOR]

The enhanced efficacy of vinegar‐processed Cyperus rotundus (VCR) in treating primary dysmenorrhea (PD) has been observed. However, the active components and potential mechanisms of synergy are still unclear. The objective of this study was to develop a method that combines bionic technology, plant metabolomics and network pharmacology to discover the active components and potential mechanisms underlying the enhanced therapeutic effects of VCR for PD. Vinegar processing alters the flavor of C. rotundus, leading to changes in its properties. The acidic nature of vinegar enhances the selectivity of the medicine toward the liver, thereby improving its ability to soothe the liver, regulate qi and provide pain relief. Through gas chromatography–mass spectrometry and multivariate statistical analysis, 30 key differential components between raw C. rotundus and VCR have been screened and identified. These differential components primarily exert their therapeutic effects in treating PD by modulating targets such as interleukin‐6, TNF, TP53 and PTGS2, as well as pathways including the estrogen signaling pathway, ovarian steroidogenesis, the TNF signaling pathway and the HIF‐1 signaling pathway. The findings of this study serve as a reference for the application of VCR in compound formulas and clinic practiceal. Furthermore, the methodology employed in this study provides research insights for the processing of other Chinese medicines. [ABSTRACT FROM AUTHOR]

SUMMARY: Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi‐omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years. [ABSTRACT FROM AUTHOR]

The presence and localization of plant metabolites are indicative of physiological processes, e.g., under biotic and abiotic stress conditions. Further, the chemical composition of plant parts is related to their quality as food or for medicinal applications. Mass spectrometry imaging (MSI) has become a popular analytical technique for exploring and visualizing the spatial distribution of plant molecules within a tissue. This review provides a summary of mass spectrometry methods used for mapping and identifying metabolites in plant tissues. We present the benefits and the disadvantages of both vacuum and ambient ionization methods, considering direct and indirect approaches. Finally, we discuss the current limitations in annotating and identifying molecules and perspectives for future investigations. [ABSTRACT FROM AUTHOR]

Indoor production of basil (Ocimum basilicum L.) is influenced by light spectrum, photosynthetic photon flux density (PPFD), and the photoperiod. To investigate the effects of different lighting on growth, chlorophyll content, and secondary metabolism, basil plants were grown from seedlings to fully expanded plants in microcosm devices under different light conditions: (a) white light at 250 and 380 μmol·m−2·s−1 under 16/8 h light/dark and (b) white light at 380 μmol·m−2·s−1 under 16/8 and 24/0 h light/dark. A higher yield was recorded under 380 μmol·m−2·s−1 compared to 250 μmol·m−2·s−1 (fresh and dry biomasses 260.6 ± 11.3 g vs. 144.9 ± 14.6 g and 34.1 ± 2.6 g vs. 13.2 ± 1.4 g, respectively), but not under longer photoperiods. No differences in plant height and chlorophyll content index were recorded, regardless of the PPFD level and photoperiod length. Almost the same volatile organic compounds (VOCs) were detected under the different lighting treatments, belonging to terpenes, aldehydes, alcohols, esters, and ketones. Linalool, eucalyptol, and eugenol were the main VOCs regardless of the lighting conditions. The multivariate data analysis showed a sharp separation of non-volatile metabolites in apical and middle leaves, but this was not related to different PPFD levels. Higher levels of sesquiterpenes and monoterpenes were detected in plants grown under 250 μmol·m−2·s−1 and 380 μmol·m−2·s−1, respectively. A low separation of non-volatile metabolites based on the photoperiod length and VOC overexpression under longer photoperiods were also highlighted. [ABSTRACT FROM AUTHOR]

Copyright of Mycosystema is the property of Mycosystema Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Cassia absus member of fabaceae family is commonly used medicinal plant in India as it is useful in many ailments and diseases from centuries. Despite the great advancements in pharmaceutical medicine in recent decades, medicinal plants still plays an important role in human kind and health. The last decades have witnessed a surfeit of research geared towards validating the various biological activities of plants/products. Aims: The organic solvent based phenolic extraction, affecting the human health and environment in many ways, so an alternative of this old fashion with eco-friendly extraction is need of hour. The present study was aimed for HPLC-MS based metabolomics & chemometrics studies of Cassia absus seeds, extracted with deep eutectic solvents (DESs) based green extraction (CAA, CAB, CAC, CAD) of Cassia absus and the comparison with the organic methanol extract. Methods: The green extraction done by various deep eutectic solvents and extracts were checked for their chemometrics studies and HPLC-MS based phenolic metabolomics. These extracts were checked for their antioxidant activities through a battery of In-vitro assay viz. DPPH, deoxyribose, chelating, reducing, and lipid peroxidation. All these extracts were also tested for their antimicrobial and tyrosinase inhibitory activities. Results: It is pertinent to mention here that all green extracts showed enrichment of phenolic compounds and more biological activities as compared to methanol extract in all these biological assays. The phenolic fingerprinting analyzed using Metaboanalyst 5.0 showed dysregulation of major phenolic compounds in different set of extracts. The heatmap and PCA plots showing a clear inter and intraclass variation/separation of phytochemicals.

Nuclear magnetic resonance (NMR) spectroscopy is a sensitive technique used to analyse the structure elucidation, dynamics, reaction state, and chemical environment of molecules. Abelmoschus esculentus and Lagenaria siceraria are edible plants used traditionally to treat jaundice, diabetes, weight loss, ulcer, hypertension, heart failure, skin diseases and reduced cholesterol. Therefore, based on the medicinal uses the study was designed to analyze fingerprinting of metabolites of the seeds of the selected plants. The dry seeds were powdered and the metabolites were extracted by socking method with a mixture of methanol/chloroform. The extracted metabolites from seeds were subjected to proton NMR using the noesygpprld pulse sequence. A total 18 peaks were obtained from each spectrum. Among the peaks, three peaks with the highest intensities were analyzed by utilizing NMR. The peak metabolites were determined with the correlation with the correct peak using in built Biological Magnetic Resonance Data Bank (BMRB). The results showed that the obtained data varied from known plant metabolites due to the contamination and interaction between the metabolites. In addition, variants in the metabolites from sample to sample may have been the result of errors or limitations in the study. The data generated from this experiment will be used to help to conduct the advanced research in the near future on the selected edible plant species which will be valuable for many different areas of the scientific community. Plant metabolomics has the potential benefit in the medical field, agricultural industry, and many other areas of our economy.

Background Metabolomics is the simultaneous determination of all metabolites in a system. Despite significant advances in the field, compound identification remains a challenge. Prior knowledge of the compound classes of interest can improve metabolite identification. Hormones are a small signaling molecules, which function in coordination to direct all aspects of development, function and reproduction in living systems and which also pose challenges as environmental contaminants. Hormones are inherently present at low levels in tissues, stored in many forms and mobilized rapidly in response to a stimulus making them difficult to measure, identify and quantify. Methods An in-depth literature review was performed for known hormones, their precursors, metabolites and conjugates in plants to generate the database and an RShiny App developed to enable web-based searches against the database. An accompanying liquid chromatography – mass spectrometry (LC-MS) protocol was developed with retention time prediction in Retip. A meta-analysis of 14 plant metabolomics studies was used for validation. Results We developed HormonomicsDB, a tool which can be used to query an untargeted mass spectrometry (MS) dataset against a database of more than 200 known hormones, their precursors and metabolites. The protocol encompasses sample preparation, analysis, data processing and hormone annotation and is designed to minimize degradation of labile hormones. The plant system is used a model to illustrate the workflow and data acquisition and interpretation. Analytical conditions were standardized to a 30 min analysis time using a common solvent system to allow for easy transfer by a researcher with basic knowledge of MS. Incorporation of synthetic biotransformations enables prediction of novel metabolites. Conclusions HormonomicsDB is suitable for use on any LC-MS based system with compatible column and buffer system, enables the characterization of the known hormonome across a diversity of samples, and hypothesis generation to reveal knew insights into hormone signaling networks.

Background and objective: The herb Rheum tanguticum (RT), a member of the Polygonaceae family, is listed in the Chinese Pharmacopoeia and has been widely used to treat cardiovascular and gastrointestinal disease. The research aimed to identify the different substances from two kinds of RT extraction methods and the in vivo biotransformation of RT components. Methods: In this study, by using ultrahigh‐performance liquid chromatography coupled with quadrupole‐time‐of‐flight tandem mass spectrometry (UHPLC‐Q‐TOF‐MS/MS), we have investigated the metabolomic variation and the in vivo metabolism of RT. A post‐acquisition data processing software, PeakView, was applied to an accurate qualitative analysis of the chemical components in RT. Results: Through plant metabolomics analysis, 24 related, differentially expressed metabolites of RT water extract and alcohol extract were obtained. Combined with novel identification strategies and systematic in vivo metabolism analysis, a total of 101 compounds were discovered or tentatively identified in rat serum (including 15 prototype compounds and 86 metabolites). Conclusion: In this study, a combination of extraction methods, liquid chromatography–mass spectrometry (LC–MS) technology, and in vivo animal metabolism studies have been established for the screening, identification, and research of chemical active components of natural medicines. LC–MS analysis combined with plant metabolomics was used to study the differential metabolites between different extraction methods of RT. Based on UHPLC‐Q‐TOF‐MS/MS technology, the composition and metabolism of rat plasma before and after RT administration were analysed in vivo, and 15 prototype components and 86 metabolites were detected. A combination of extraction methods, chromatography‐mass spectrometry (LC‐MS/MS) technology, and in vivo animal metabolism studies have been established for the screening, identification, and research of chemical active components of natural medicines. LC‐MS analysis combined with plant metabolomics was used to study the differential metabolites between different extraction methods of RT. Based on UHPLC‐Q‐TOF‐MS/MS technology, the composition and metabolism of rat plasma before and after RT administration were analyzed in vivo, and 15 prototype components and 86 metabolites were detected. [ABSTRACT FROM AUTHOR]

Nuclear magnetic resonance (NMR) spectroscopy is a sensitive technique used to analyse the structure, dynamics, reaction state, and chemical environment of molecules. Abelmoschus esculentus and Lagenaria siceraria are edible plants used traditionally to treat jaundice, diabetes, weight loss, ulcer, hypertension, heart failure, skin diseases and reduced cholesterol. Therefore, based on the medicinal uses the study was designed to analyze fingerprinting of metabolites of the seeds of the selected plants. The dry seeds were powdered and the metabolites were extracted by socking method with a mixture of methanol/chloroform. The extracted metabolites from seeds were subjected to proton NMR using the noesygpprld pulse sequence. A total 18 peaks were obtained from each spectrum. Among the peaks, three peaks with the highest intensities were analyzed by utilizing NMR. The peak metabolites were determined with the correlation with the correct peak using in built Biological Magnetic Resonance Data Bank (BMRB). The results showed that the obtained data varied from known plant metabolites due to the contamination and interaction between the metabolites. In addition, variants in the metabolites from sample to sample may have been the result of errors or limitations in the study. The data generated from this experiment will be used to help to conduct the advanced research in the near future on the selected edible plant species which will be valuable for many different areas of the scientific community. Plant metabolomics has the potential benefit in the medical field, agricultural industry, and many other areas of our economy. [ABSTRACT FROM AUTHOR]

Floating wheat is a classical herbal with potential efficacy in the treatment of hyperhidrosis. Aiming at revealing the main components and potential mechanisms of floating wheat, a comprehensive and unique phytopharmacology profile study was carried out. First, common wheat was used as a control to look for chemical markers of floating wheat. In the screening analysis, a total of 180 shared compounds were characterized in common wheat and floating wheat, respectively. The results showed that floating wheat and common wheat contain similar types of compounds. In addition, in non-targeted metabolomic analysis, when taking the contents of the constituents into account, it was found that there indeed existed quite a difference between floating wheat and common wheat and 17 potential biomarkers for floating wheat. Meanwhile, a total of seven components targeted for hyperhidrosis were screened out based on network pharmacology. Seven key differential components were screened, among which kaempferol, asiatic acid, sclareol, enoxolone, and secoisolariciresinol had higher degree values than the others. The analysis of interacting genes revealed three key genes, namely, MAP2K1, ESR1, and ESR2. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses showed that various signaling pathways were involved. Prolactin signaling, thyroid cancer, endocrine resistance, gonadotropin secretion, and estrogen signaling pathways were the main pathways of the intervention of floating wheat in excessive sweating, which was associated with the estrogenic response, hormone receptor binding, androgen metabolism, apoptosis, cancer, and many other biological processes. Molecular docking showed that the screened key components could form good bindings with the target proteins through intermolecular forces. This study reveals the active ingredients and potential molecular mechanism of floating wheat in the treatment of hyperhidrosis and provides a reference for subsequent basic research. [ABSTRACT FROM AUTHOR]

Background Metabolomics is the simultaneous determination of all metabolites in a system. Despite significant advances in the field, compound identification remains a challenge. Prior knowledge of the compound classes of interest can improve metabolite identification. Hormones are a small signaling molecules, which function in coordination to direct all aspects of development, function and reproduction in living systems and which also pose challenges as environmental contaminants. Hormones are inherently present at low levels in tissues, stored in many forms and mobilized rapidly in response to a stimulus making them difficult to measure, identify and quantify. Methods An in-depth literature review was performed for known hormones, their precursors, metabolites and conjugates in plants to generate the database and an RShiny App developed to enable web-based searches against the database. An accompanying liquid chromatography – mass spectrometry (LC-MS) protocol was developed with retention time prediction in Retip. A meta-analysis of 14 plant metabolomics studies was used for validation. Results We developed HormonomicsDB, a tool which can be used to query an untargeted mass spectrometry (MS) dataset against a database of more than 200 known hormones, their precursors and metabolites. The protocol encompasses sample preparation, analysis, data processing and hormone annotation and is designed to minimize degradation of labile hormones. The plant system is used a model to illustrate the workflow and data acquisition and interpretation. Analytical conditions were standardized to a 30 min analysis time using a common solvent system to allow for easy transfer by a researcher with basic knowledge of MS. Incorporation of synthetic biotransformations enables prediction of novel metabolites. Conclusions HormonomicsDB is suitable for use on any LC-MS based system with compatible column and buffer system, enables the characterization of the known hormonome across a diversity of samples, and hypothesis generation to reveal knew insights into hormone signaling networks.

Plant metabolomics is a rapidly advancing field of plant sciences and systems biology. It involves comprehensive analyses of small molecules (metabolites) in plant tissues and cells. These metabolites include a wide range of compounds, such as sugars, amino acids, organic acids, secondary metabolites (e.g., alkaloids and flavonoids), lipids, and more. Metabolomics allows an understanding of the functional roles of specific metabolites in plants’ physiology, development, and responses to biotic and abiotic stresses. It can lead to the identification of metabolites linked with specific traits or functions. Plant metabolic networks and pathways can be better understood with the help of metabolomics. Researchers can determine how plants react to environmental cues or genetic modifications by examining how metabolite profiles change under various crop stages. Metabolomics plays a major role in crop improvement and biotechnology. Integrating metabolomics data with other omics data (genomics, transcriptomics, and proteomics) provides a more comprehensive perspective of plant biology. This systems biology approach enables researchers to understand the complex interactions within organisms.

Abstract Plant metabolomics is an important research area in plant science. Chemometrics is a useful tool for plant metabolomic data analysis and processing. Among them, high-order chemometrics represented by tensor modeling provides a new and promising technical method for the analysis of complex multi-way plant metabolomics data. This paper systematically reviews different tensor methods widely applied to the analysis of complex plant metabolomic data. The advantages and disadvantages as well as the latest methodological advances of tensor models are reviewed and summarized. At the same time, application of different tensor methods in solving plant science problems are also reviewed and discussed. The reviewed applications of tensor methods in plant metabolomics cover a wide range of important plant science topics including plant gene mutation and phenotype, plant disease and resistance, plant pharmacology and nutrition analysis, and plant products ingredient characterization and quality evaluation. It is evident from the review that tensor methods significantly promote the automated and intelligent process of plant metabolomics analysis and profoundly affect the paradigm of plant science research. To the best of our knowledge, this is the first review to systematically summarize the tensor analysis methods in plant metabolomic data analysis.

Drug development from medicinal plants constitutes an important strategy for finding natural anticancer therapies. While several plant secondary metabolites with potential antitumor activities have been identified, well-defined mechanisms of action remained uncovered. In fact, studies of medicinal plants have often focused on the genome, transcriptome, and proteome, dismissing the relevance of the metabolome for discovering effective plant-based drugs. Metabolomics has gained huge interest in cancer research as it facilitates the identification of potential anticancer metabolites and uncovers the metabolomic alterations that occur in cancer cells in response to treatment. This holds great promise for investigating the mode of action of target metabolites. Although metabolomics has made significant contributions to drug discovery, research in this area is still ongoing. In this review, we emphasize the significance of plant metabolomics in anticancer research, which continues to be a potential technique for the development of anticancer drugs in spite of all the challenges encountered. As well, we provide insights into the essential elements required for performing effective metabolomics analyses.

The presence and localization of plant metabolites are indicative of physiological processes, e.g., under biotic and abiotic stress conditions. Further, the chemical composition of plant parts is related to their quality as food or for medicinal applications. Mass spectrometry imaging (MSI) has become a popular analytical technique for exploring and visualizing the spatial distribution of plant molecules within a tissue. This review provides a summary of mass spectrometry methods used for mapping and identifying metabolites in plant tissues. We present the benefits and the disadvantages of both vacuum and ambient ionization methods, considering direct and indirect approaches. Finally, we discuss the current limitations in annotating and identifying molecules and perspectives for future investigations.

Indoor production of basil (Ocimum basilicum L.) is influenced by light spectrum, photosynthetic photon flux density (PPFD), and the photoperiod. To investigate the effects of different lighting on growth, chlorophyll content, and secondary metabolism, basil plants were grown from seedlings to fully expanded plants in microcosm devices under different light conditions: (a) white light at 250 and 380 μmol·m−2·s−1 under 16/8 h light/dark and (b) white light at 380 μmol·m−2·s−1 under 16/8 and 24/0 h light/dark. A higher yield was recorded under 380 μmol·m−2·s−1 compared to 250 μmol·m−2·s−1 (fresh and dry biomasses 260.6 ± 11.3 g vs. 144.9 ± 14.6 g and 34.1 ± 2.6 g vs. 13.2 ± 1.4 g, respectively), but not under longer photoperiods. No differences in plant height and chlorophyll content index were recorded, regardless of the PPFD level and photoperiod length. Almost the same volatile organic compounds (VOCs) were detected under the different lighting treatments, belonging to terpenes, aldehydes, alcohols, esters, and ketones. Linalool, eucalyptol, and eugenol were the main VOCs regardless of the lighting conditions. The multivariate data analysis showed a sharp separation of non-volatile metabolites in apical and middle leaves, but this was not related to different PPFD levels. Higher levels of sesquiterpenes and monoterpenes were detected in plants grown under 250 μmol·m−2·s−1 and 380 μmol·m−2·s−1, respectively. A low separation of non-volatile metabolites based on the photoperiod length and VOC overexpression under longer photoperiods were also highlighted.

Verticillium wilt of olive (VWO) is one of the most widespread and devastating olive diseases in the world. Harnessing host resistance to the causative agent is considered one of the most important measures within an integrated control strategy of the disease. Aiming to understand the mechanisms underlying olive resistance to VWO, the metabolic profiles of olive leaves, stems and roots from 10 different cultivars with varying levels of susceptibility to this disease were investigated by liquid chromatography coupled to mass spectrometry (LC-MS). The distribution of 56 metabolites among the three olive tissues was quantitatively assessed and the possible relationship between the tissues' metabolic profiles and resistance to VWO was evaluated by applying unsupervised and supervised multivariate analysis. Principal component analysis (PCA) was used to explore the data, and separate clustering of highly resistant and extremely susceptible cultivars was observed. Moreover, partial least squares discriminant analysis (PLS-DA) models were built to differentiate samples of highly resistant, intermediate susceptible/resistant, and extremely susceptible cultivars. Root models showed the lowest classification capability, but metabolites from leaf and stem were able to satisfactorily discriminate samples according to the level of susceptibility. Some typical compositional patterns of highly resistant and extremely susceptible cultivars were described, and some potential resistance/susceptibility metabolic markers were pointed out. [ABSTRACT FROM AUTHOR]

Plant metabolomics is an important research area in plant science. Chemometrics is a useful tool for plant metabolomic data analysis and processing. Among them, high-order chemometrics represented by tensor modeling provides a new and promising technical method for the analysis of complex multi-way plant metabolomics data. This paper systematically reviews different tensor methods widely applied to the analysis of complex plant metabolomic data. The advantages and disadvantages as well as the latest methodological advances of tensor models are reviewed and summarized. At the same time, application of different tensor methods in solving plant science problems are also reviewed and discussed. The reviewed applications of tensor methods in plant metabolomics cover a wide range of important plant science topics including plant gene mutation and phenotype, plant disease and resistance, plant pharmacology and nutrition analysis, and plant products ingredient characterization and quality evaluation. It is evident from the review that tensor methods significantly promote the automated and intelligent process of plant metabolomics analysis and profoundly affect the paradigm of plant science research. To the best of our knowledge, this is the first review to systematically summarize the tensor analysis methods in plant metabolomic data analysis. [ABSTRACT FROM AUTHOR]

Mass spectrometry has been an essential technique for the investigation of the metabolic pathways of living organisms since its appearance at the beginning of the 20th century. Due to its capability to resolve isotopically labeled species, it can be applied together with stable isotope tracers to reveal the transformation of particular biologically relevant molecules. However, low-resolution techniques, which were used for decades, had limited capabilities for untargeted metabolomics, especially when a large number of compounds are labelled simultaneously. Such untargeted studies may provide new information about metabolism and can be performed with high-resolution mass spectrometry. Here, we demonstrate the capabilities of high-resolution mass spectrometry to obtain insights on the metabolism of a model plant, Lepidium sativum, germinated in D2O and H218O-enriched media. In particular, we demonstrated that in vivo labeling with heavy water helps to identify if a compound is being synthesized at a particular stage of germination or if it originates from seed content, and tandem mass spectrometry allows us to highlight the substructures with incorporated isotope labels. Additionally, we found in vivo labeling useful to distinguish between isomeric compounds with identical fragmentation patterns due to the differences in their formation rates that can be compared by the extent of heavy atom incorporation. [ABSTRACT FROM AUTHOR]

Background: Semen Aesculi, a traditional Chinese herbal medicine, has a long history of use for treating chest and abdominal pain with distension. In addition, the horse chestnut (Aesculus hippocastanum L.) is another species of Aesculus in Europe and has notable clinical significance in alleviating chronic venous insufficiency, hemorrhoids, and postoperative edema. Thus, highlighting the comparative study of Semen Aesculi and horse chestnut may broaden clinical applications. Objectives: To conduct a comprehensive comparative analysis on the chemical profiling of these two varieties and determine whether they have equivalent clinical efficacy by integrating plant metabolomics and multivariate statistical methods. Methods: Initially, a comprehensive characterisation was performed using ultra‐performance liquid chromatography quadrupole time‐of‐flight tandem mass spectrometry (UPLC‐QTOF‐MS/MS) platform, and in total 44 active ingredients were identified. Then, untargeted metabolomics combined with principal component analysis (PCA) and partial least squares‐discriminant analysis (PLS‐DA) was applied for the discrimination of a German species and three official Chinese species. Next, 24 marker compounds responsible for the discrimination of different species were screened out and used to predict the species of unknown samples by genetic algorithm‐optimised support vector machine (GA‐SVM) with a high prediction accuracy. Finally, a heatmap visualisation was employed for clarifying the distribution of the identified active ingredients. Results: The three species of Chinese Semen Aesculi showed distinct separation from each other, while European horse chestnut and Aesculus chinensis Bunge were similar in chemical composition. Conclusions: This work provided experimental evidence for further expanding the clinical application of Chinese Semen Aesculi and promoted the species identification and quality control of Semen Aesculi. Semen Aesculi has long been used as a Chinese herbal medicine. However, another species named horse chestnut, is more popular in Europe. To determine whether these two varieties are equivalent in clinical efficacy, a comparative analysis based on metabolomics and chemometrics were built for profiling. The result showed that the Chinese species showed distinct separation, while horse chestnut and Aesculus chinensis Bunge were resemblant in composition. This work provided evidence for further expanding the clinical application of Chinese Semen Aesculi. [ABSTRACT FROM AUTHOR]

Lactuca indica L. cv. Mengzao (LIM), acknowledged as a pivotal “One Root of Medicine and Food”, boasts dual applications in both culinary and medicinal domains. This research delves into the influence of various harvest periods (vegetative, budding, blossom, and fruiting) on distinct medicinal parts (roots, stems, leaves, flowers, and seeds) of LIM, employing plant metabolomics to assess its chemical constituents. A total of 66 chemical constituents were identified in LIM, with 11 chemical components emerging as potential markers for distinguish medicinal parts. Notably, nutritional organs exhibited elevated levels of cichoric acid, rutin and chlorogenic acid. Specifically, leaves during the budding stage displayed the highest chicoric acid content at 11.70 mg·g−1. Conversely, reproductive organs showed heightened concentrations of cichoric acid, rutin and chlorogenic acid, with seeds exhibiting the peak cichoric acid content at 4.53 mg g−1. This study enriches our understanding of LIM by offering novel insights into quality assessment and the comprehensive utilization of its diverse parts.

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

Introduction: Standardizing the planting process is an effective way to control the quality stability of herbal resources, which are susceptible to external environmental factors (e.g., moisture, soil, etc.). However, how to scientifically and comprehensively assess the effects of standardized planting on plant quality and quickly test unknown samples has not been addressed. Objective: The aim of this study was to determine and compare the metabolite levels of herbs before and after standardized planting, to quickly distinguish their sources, and to evaluate their quality, using the typical herb Astragali Radix (AR) as an example. Methods: In this study, an efficient strategy using liquid chromatography–mass spectrometry (LC‐MS) based on plant metabolomics combined with extreme learning machine (ELM) has been developed to efficiently distinguish and predict AR after standardized planting. Moreover, a comprehensive multi‐index scoring method has been developed for the comprehensive evaluation of the quality of AR. Results: The results confirmed that AR after standardized planting was significantly differentiated, with a relatively stable content of 43 differential metabolites, mainly including flavonoids. An ELM model was established based on LC‐MS data, and the accuracy in predicting unknown samples could reach more than 90%. As expected, higher total scores were obtained for AR after standardized planting, indicating much better quality. Conclusion: A dual system for evaluating the impact of standardized planting on the quality of plant resources has been established, which will significantly contribute to innovation in the quality evaluation of medicinal herbs and support the selection of optimal planting conditions. In this paper, the AR before and after standardized planting were successfully differentiated at the chemical level by plant metabolomics analysis, and the 43 differential metabolites screened were preliminary identified. The quality of AR was also scored with multiple indexes, and it was found that the quality of AR after standardized planting was better. Meanwhile, using the raw data from LC‐MS as input, the ELM model was found to be more than 90% accurate in predicting different AR. [ABSTRACT FROM AUTHOR]

Viscum coloratum (Kom.) Nakai is a well-known medicinal plant. However, the optimal harvest time for V. coloratum is unknown. Few studies were performed to analyze compound variation during storage and to improve post-harvest quality control. Our study aimed to comprehensively evaluate the quality of V. coloratum in different growth stages, and determine the dynamic variation of metabolites. Ultra-performance liquid chromatography tandem mass spectrometry was used to quantify 29 compounds in V. coloratum harvested in six growth periods, and the associated biosynthetic pathways were explored. The accumulation of different types of compounds were analyzed based on their synthesis pathways. Grey relational analysis was used to evaluate the quality of V. coloratum across different months. The compound variation during storage was analyzed by a high-temperature high-humidity accelerated test. The results showed that the quality of V. coloratum was the hightest in March, followed by November, and became the lowest in July. During storage, compounds in downstream steps of the biosynthesis pathway were first degraded to produce the upstream compounds and some low-molecular-weight organic acids, leading to an increase followed by a decrease in the content of some compounds, and resulted in a large gap during the degradation time course among different compounds. Due to the rapid rate and large degree of degradation, five compounds were tentatively designated as "early warning components" for quality control. This report provides reference for better understanding the biosynthesis and degradation of metabolites in V. coloratum and lays a theoretical foundation for rational application of V. coloratum and better quality control of V. coloratum during storage. [ABSTRACT FROM AUTHOR]

Indoor farming of basil (Ocimum basilicum L.) under artificial lighting to support year-round produce demand is an area of increasing interest. Literature data indicate that diverse light regimes differently affect downstream metabolic pathways which influence basil growth, development and metabolism. In this study, basil was grown from seedlings to fully developed plants in a microcosm, an innovative device aimed at growing plants indoor as in natural conditions. Specifically, the effects of white (W) and blue-red (BR) light under a photosynthetic photon flux density of 255 μmol m−2 s−1 on plant growth, photochemistry, soluble nutrient concentration and secondary metabolism were investigated. Plants grew taller (41.8 ± 5.0 vs. 28.4 ± 2.5 cm) and produced greater biomass (150.3 ± 24.2/14.7 ± 2.0 g vs. 116.2 ± 28.3/12.3 ± 2.5 g fresh/dry biomass) under W light compared to BR light. The two lighting conditions differently influenced the soluble nutrient concentration and the translocation rate. No photosynthetic stress was observed under the two lighting regimes, but leaves grown under W light displayed higher levels of maximum quantum yield of PSII and electron transport rate. Sharp differences in metabolic patterns under the two lighting regimes were detected with higher concentrations of phenolic compounds under the BR light. [ABSTRACT FROM AUTHOR]

Floating wheat is a classical herbal with potential efficacy in the treatment of hyperhidrosis. Aiming at revealing the main components and potential mechanisms of floating wheat, a comprehensive and unique phytopharmacology profile study was carried out. First, common wheat was used as a control to look for chemical markers of floating wheat. In the screening analysis, a total of 180 shared compounds were characterized in common wheat and floating wheat, respectively. The results showed that floating wheat and common wheat contain similar types of compounds. In addition, in non-targeted metabolomic analysis, when taking the contents of the constituents into account, it was found that there indeed existed quite a difference between floating wheat and common wheat and 17 potential biomarkers for floating wheat. Meanwhile, a total of seven components targeted for hyperhidrosis were screened out based on network pharmacology. Seven key differential components were screened, among which kaempferol, asiatic acid, sclareol, enoxolone, and secoisolariciresinol had higher degree values than the others. The analysis of interacting genes revealed three key genes, namely, MAP2K1, ESR1, and ESR2. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses showed that various signaling pathways were involved. Prolactin signaling, thyroid cancer, endocrine resistance, gonadotropin secretion, and estrogen signaling pathways were the main pathways of the intervention of floating wheat in excessive sweating, which was associated with the estrogenic response, hormone receptor binding, androgen metabolism, apoptosis, cancer, and many other biological processes. Molecular docking showed that the screened key components could form good bindings with the target proteins through intermolecular forces. This study reveals the active ingredients and potential molecular mechanism of floating wheat in the treatment of hyperhidrosis and provides a reference for subsequent basic research.

Terminalia catappa L. (Combretaceae) is a medicinal plant that is part of the Brazilian biodiversity; this plant is popularly used for the treatment of a wide range of diseases. To better understand the chemical composition of T. catappa in different seasons, we conducted a thorough study using LC-MS and NMR data analysis techniques. The study helped obtain a chemical profile of the plant ethanolic extracts in different seasons of the year (spring, summer, autumn, and winter). The dereplication of LC-HRMS data allowed the annotation of 90 compounds in the extracts of T. catappa (hydrolyzable tannins, ellagic acid derivatives, and glycosylated flavonoids). Triterpenes and C-glycosyl flavones were the compounds that significantly contributed to differences observed between T. catappa plant samples harvested in autumn/winter and spring, respectively. The variations observed in the compound composition of the plant leaves may be related to processes induced by environmental stress and leaf development. Data fusion applied in the metabolomic profiling study allowed us to identify metabolites with greater confidence, and provided a better understanding regarding the production of specialized metabolites in T. catappa leaves under different environmental conditions, which may be useful to establish appropriate quality criteria for the standardization of this medicinal plant. [ABSTRACT FROM AUTHOR]

Cichorium glandulosum Boiss. et Huet (CG) and Cichorium intybus L. (CI) are widely used as the main raw material of functional food with hepatoprotective and hypoglycemic effects. Due to the lack of comparison on the chemical ingredients and efficacy, they were often used imprecisely and interchangeably. It is necessary to distinguish between them. With the plant metabolomics based on high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS) and multivariate chemometric techniques, the chemical ingredients were characterized and 59 compounds between CG and CI were classified. As for antioxidative and hypoglycemic activities in vitro, CI extraction exhibited better antioxidant activity than CG, while CG extraction showed stronger hypoglycemic activity. Furthermore, a bivariate correlation between the chemical composition and efficacy of the extract was also analyzed, and three differentially strong correlation components between CI and CG were prepared, and the antioxidative and hypoglycemic efficacies were compared in vivo and different active phenotypes were obtained. Finally, we revealed chemical and biological differences between CG and CI, providing a basis for achieving better quality control and developing more effective functional foods. [ABSTRACT FROM AUTHOR]

Viscum coloratum (Kom.) Nakai is a well-known medicinal hemiparasite widely distributed in Asia. The synthesis and accumulation of its metabolites are affected by both environmental factors and the host plants, while the latter of which is usually overlooked. The purpose of this study was to comprehensively evaluate the effects of host and habitat on the metabolites in V. coloratum through multiple chemical and biological approaches. The metabolite profile of V. coloratum harvested from three different host plants in two habitats were determined by multiple chemical methods including high-performance liquid chromatography-ultraviolet (HPLC-UV), gas chromatography-flame ionization detector (GC-FID) and ultra-performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-QTOF/MS). The differences in antioxidant efficacy of V. coloratum were determined based on multiple in vitro models. The multivariate statistical analysis and data fusion strategy were applied to analyze the differences in metabolite profile and antioxidant activity of V. coloratum. Results indicated that the metabolite profile obtained by various chemical approaches was simultaneously affected by host and environment factors, and the environment plays a key role. Meanwhile, three main differential metabolites between two environment groups were identified. The results of antioxidant assay indicated that the environment has greater effects on the biological activity of V. coloratum than the host. Therefore, we conclude that the integration of various chemical and biological approaches combined with multivariate statistical and data fusion analysis, which can determine the influences of host plant and habitat on the metabolites, is a powerful strategy to control the quality of semi-parasitic herbal medicine.

Abstract 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.

Verticillium wilt of olive (VWO) is one of the most widespread and devastating olive diseases in the world. Harnessing host resistance to the causative agent is considered one of the most important measures within an integrated control strategy of the disease. Aiming to understand the mechanisms underlying olive resistance to VWO, the metabolic profiles of olive leaves, stems and roots from 10 different cultivars with varying levels of susceptibility to this disease were investigated by liquid chromatography coupled to mass spectrometry (LC-MS). The distribution of 56 metabolites among the three olive tissues was quantitatively assessed and the possible relationship between the tissues’ metabolic profiles and resistance to VWO was evaluated by applying unsupervised and supervised multivariate analysis. Principal component analysis (PCA) was used to explore the data, and separate clustering of highly resistant and extremely susceptible cultivars was observed. Moreover, partial least squares discriminant analysis (PLS-DA) models were built to differentiate samples of highly resistant, intermediate susceptible/resistant, and extremely susceptible cultivars. Root models showed the lowest classification capability, but metabolites from leaf and stem were able to satisfactorily discriminate samples according to the level of susceptibility. Some typical compositional patterns of highly resistant and extremely susceptible cultivars were described, and some potential resistance/susceptibility metabolic markers were pointed out.

The application of high performance thin layer chromatography (HPTLC)-based non-targeted metabolomics as a holistic approach to compare fingerprints of metabolite changes during Artemisia annua development is described. Images of HPTLC chromatograms obtained after derivatization with anisaldehyde-sulphuric acid reagent were used as a dataset for multivariate analysis. Principal component analysis and orthogonal partial least squares discriminant analysis confirmed the differentiation of samples belonging to vegetative phase, flowering stage, and seed formation stage of the plant development. The obtained results showed that the HPTLC-based metabolomics approach can be a very reliable technique for the investigation of metabolic changes during plant development, complementary to gas chromatography–mass spectrometry and nuclear magnetic resonance-based metabolomics.

Abstract Background The stems of Kadsura interior A. C. Smith are used as traditional Chinese medicine (TCM) Kadsurae Caulis, with the traditional efficacy of tonifying and invigorating the blood, therefore being favored to treat blood deficiency (BD) widely. However, the stems of K. interior and its closely related species are morphologically similar and they may readily be misused as Kadsurae Caulis, thus likely to exert negative effects on clinical efficacy and clinical medication safety. Methods Firstly, blood tonic efficacies of the stems of K. interior (KIS) and its closely related species were compared using BD mouse model induced by 1-acetyl-2-phenylhydrazine (APH) and cyclophosphamide (CTX). Secondly, the chemical constituents from the stems of K. interior and its closely related species were evaluated and compared using a plant metabolomics approach. Plant metabolomics in this study aims at discovering differential metabolites and comprehensively assessing the chemical constituents by combining state-of-the-art high-resolution UPLC-Q/TOF–MS/MS technique and multivariate data analysis. Finally, based on the pharmacological data and the chemical constituents in UPLC-Q/TOF–MS fingerprints, the potential blood tonic active markers were screened by the spectrum-effect relationship analysis and quantified by UPLC-UV-DAD. Results The ethanol extract of the stems of K. interior significantly increased the levels of hematocrit (HCT), hemoglobin (HGB), and red blood cells (RBC) in BD mice. In addition, it significantly increased the serum levels of interleukin 3 (IL-3), granulocyte–macrophage colony-stimulating factor (GM-CSF), and macrophage-stimulating factor (M-CSF) in BD mice (P

Plant metabolomics studies haves revealed new bioactive compounds. However, like other omics disciplines, the generated data are not fully exploited, mainly because the commonly performed analyses focus on elucidating the presence/absence of distinctive metabolites (and/or their precursors) and not on providing a holistic view of metabolomic changes and their participation in organismal adaptation to biotic and abiotic stress conditions. Therefore, spectral libraries generated from Cecropia obtusifolia cell suspension cultures in a previous study were considered as a case study and were reanalyzed herein. These libraries were obtained from a time-course experiment under nitrate starvation conditions using both electrospray ionization modes. The applied methodology included the use of ecological analytical tools in a systematic four-step process, including a population analysis of metabolite α diversity, richness, and evenness (i); a chemometrics analysis to identify discriminant groups (ii); differential metabolic marker identification (iii); and enrichment analyses and annotation of active metabolic pathways enriched by differential metabolites (iv). Our species α diversity results referring to the diversity of metabolites represented by mass-to-charge ratio (m/z) values detected at a specific retention time (rt) (an uncommon way to analyze untargeted metabolomic data) suggest that the metabolome is dynamic and is modulated by abiotic stress. A total of 147 and 371 m/z_rt pairs was identified as differential markers responsive to nitrate starvation in ESI− and ESI+ modes, respectively. Subsequent enrichment analysis showed a high degree of completeness of biosynthetic pathways such as those of brassinosteroids, flavonoids, and phenylpropanoids. [ABSTRACT FROM AUTHOR]

The application of high performance thin layer chromatography (HPTLC)-based non-targeted metabolomics as a holistic approach to compare fingerprints of metabolite changes during Artemisia annua development is described. Images of HPTLC chromatograms obtained after derivatization with anisaldehyde-sulphuric acid reagent were used as a dataset for multivariate analysis. Principal component analysis and orthogonal partial least squares discriminant analysis confirmed the differentiation of samples belonging to vegetative phase, flowering stage, and seed formation stage of the plant development. The obtained results showed that the HPTLC-based metabolomics approach can be a very reliable technique for the investigation of metabolic changes during plant development, complementary to gas chromatography-mass spectrometry and nuclear magnetic resonance-based metabolomics. [ABSTRACT FROM AUTHOR]

Physalins, active ingredients from the Physalis alkekengi L. var. franchetii (P. alkekengi) plant, have shown anti-inflammatory, antioxidant and anticancer activities. Whereas the bioactivity of physalins have been confirmed, their biosynthetic pathways, and those of quite a few derivatives, remain unknown. In this paper, biosynthesis and structure modification-related genes of physalins were mined through transcriptomic and metabolomic profiling. Firstly, we rapidly and conveniently analyzed physalins by UPLC-Q-TOFMS/MS utilizing mass accuracy, diagnostic fragment ions, and common neutral losses. In all, 58 different physalin metabolites were isolated from P. alkekengi calyxes and berries. In an analysis of the physalin biosynthesis pathway, we determined that withanolides and withaphysalins may represent a crucial intermediate between lanosterol and physalins. and those steps were decanted according to previous reports. Our results provide valuable information on the physalin metabolites and the candidate enzymes involved in the physalins biosynthesis pathways of P. alkekengi. In addition, we further analyzed differential metabolites collected from calyxes in the Jilin (Daodi of P. alkekengi) and others. Among them, 20 physalin metabolites may represent herb quality biomarkers for Daodi P. alkekengi, providing an essential role in directing the quality control index of P. alkekengi. [ABSTRACT FROM AUTHOR]

Various root‐colonizing bacterial species can promote plant growth and trigger systemic resistance against aboveground leaf pathogens and herbivore insects. To date, the underlying metabolic signatures of these rhizobacteria‐induced plant phenotypes are poorly understood. To identify core metabolic pathways that are targeted by growth‐promoting rhizobacteria, we used combinations of three plant species and three rhizobacterial species and interrogated plant shoot chemistry by untargeted metabolomics. A substantial part (50%–64%) of the metabolites detected in plant shoot tissue was differentially affected by the rhizobacteria. Among others, the phenylpropanoid pathway was targeted by the rhizobacteria in each of the three plant species. Differential regulation of the various branches of the phenylpropanoid pathways showed an association with either plant growth promotion or growth reduction. Overall, suppression of flavonoid biosynthesis was associated with growth promotion, while growth reduction showed elevated levels of flavonoids. Subsequent assays with 12 Arabidopsis flavonoid biosynthetic mutants revealed that the proanthocyanidin branch plays an essential role in rhizobacteria‐mediated growth promotion. Our study also showed that a number of pharmaceutically and nutritionally relevant metabolites in the plant shoot were significantly increased by rhizobacterial treatment, providing new avenues to use rhizobacteria to tilt plant metabolism towards the biosynthesis of valuable natural plant products. Summary Statement: Rhizobacteria‐mediated growth promotion is associated with different branches of the flavonoid pathway. [ABSTRACT FROM AUTHOR]

Mume Fructus is a well-known herbal medicine and food with a long history of processing and application. Different processing methods impact the intrinsic quality of Mume Fructus. Thus, it is of great significance to investigate the changes in chemical components during processing (i.e., raw compared to the pulp and charcoal forms). In this study, plant metabolomics methods based on mass spectrometry detection were established to analyze the chemical ingredients of Mume Fructus comprehensively. Chemometric strategies were combined to analyze the profile differences of Mume Fructus after different processing methods. The established strategy identified 98 volatile and 89 non-volatile compounds of Mume Fructus by gas chromatography-mass spectrometry (GC-MS) and ultra-high performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS/MS), respectively. Moreover, the orthogonal partial least squares discriminant analysis (OPLS-DA) indicated that raw Mume Fructus and the Mume Fructus pulp and charcoal were distributed in three regions. Subsequently, 19 volatile and 16 non-volatile components were selected as potential chemical component markers with variable importance in the projection using (VIP) >1 as the criterion, and the accuracy was verified by a Back Propagation Neural Network (BP-NN). To further understand the difference in the content of Mume Fructus before and after processing, 16 non-volatile chemical component markers were quantitatively determined by ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS). The results revealed that, compared with raw Mume Fructus, the total content of 16 components in the pulp of Mume Fructus increased while it decreased in the charcoal. Therefore, this study used GC-MS, UHPLC-Q-TOF-MS/MS and UHPLC-MS/MS modern technology to analyze the differences in chemical components before and after the processing of Mume Fructus and provided a material basis for further research on the quality evaluation and efficacy of Mume Fructus. [ABSTRACT FROM AUTHOR]

Background: Metabolomics is the simultaneous determination of all metabolites in a system. Despite significant advances in the field, compound identification remains a challenge. Prior knowledge of the compound classes of interest can improve metabolite identification. Hormones are a small signaling molecules, which function in coordination to direct all aspects of development, function and reproduction in living systems and which also pose challenges as environmental contaminants. Hormones are inherently present at low levels in tissues, stored in many forms and mobilized rapidly in response to a stimulus making them difficult to measure, identify and quantify. Methods: An in-depth literature review was performed for known hormones, their precursors, metabolites and conjugates in plants to generate the database and an RShiny App developed to enable web-based searches against the database. An accompanying liquid chromatography – mass spectrometry (LC-MS) protocol was developed with retention time prediction in Retip. A meta-analysis of 14 plant metabolomics studies was used for validation. Results: We developed HormonomicsDB, a tool which can be used to query an untargeted mass spectrometry (MS) dataset against a database of more than 200 known hormones, their precursors and metabolites. The protocol encompasses sample preparation, analysis, data processing and hormone annotation and is designed to minimize degradation of labile hormones. The plant system is used a model to illustrate the workflow and data acquisition and interpretation. Analytical conditions were standardized to a 30 min analysis time using a common solvent system to allow for easy transfer by a researcher with basic knowledge of MS. Incorporation of synthetic biotransformations enables prediction of novel metabolites. Conclusions: HormonomicsDB is suitable for use on any LC-MS based system with compatible column and buffer system, enables the characterization of the known hormonome across a diversity of samples, and hypothesis generation to reveal knew insights into hormone signaling networks.

Microalgae are active producers of various compounds, including toxic substances. However, their metabolism is very diverse and insufficiently known. We demonstrate an approach that includes growing a new strain of cyanobacterium Leptolyngbya sp. (IPPAS B-1204) on an isotopically labeled medium (D 2 O) and evaluating the metabolomic composition of these microorganisms after deuterium uptake. Despite the low resolution of the GC-MS method, the interpretation of the obtained spectra allowed us to find out not only the amount of the embedded isotope label but also to assume the position in the structure where the label is embedded. We present the results of reliably detecting more than 30 compounds with isotope labels belonging to various classes of biological compounds produced by this cyanobacterium, revealing the metabolic pathways of entry of this label. We also demonstrate that the synthesis of unsaturated fatty acids is suppressed under the growth on D 2 O medium. In addition, we found an isotopic effect in the chromatographic separation of isotopically labeled compounds in gas chromatography. These data can be used in the future both for the identification of compounds and the analysis of the biosynthesis pathways of secondary biologically active compounds and in the analysis of the production of isotopically labeled standards of compounds., Competing Interests: Declaration of Competing Interest The authors of the manuscript entitled “Metabolomic characterization of a new strain of microalgae by GC-MS method with the introduction of a deuterium label” by Anna Vishnevskaya, Anton Bashilov, Sergey Osipenko, Albert Kireev, Maria Sinetova, Eugene Nikolaev and Yury Kostyukevich declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Tire wear particles (TWPs), generated from tire abrasion, contribute significantly to environmental contamination. The toxicity of TWPs to organisms has raised significant concerns, yet their effects on terrestrial plants remain unclear. Here, we investigated the long-term impact of pristine and naturally aged TWPs on water spinach ( Ipomoea aquatica ) and its rhizospheric soil. The results indicated that natural aging reduced the toxicity of TWPs, as evidenced by decreased levels of polycyclic aromatic hydrocarbons (PAHs) in soil and TWPs themselves. Consequently, aged TWPs were found to enhance the plant growth and chlorophyll content, whereas pristine TWPs increased the plant stress. Furthermore, aged TWPs improved soil organic matter (SOM) and total organic carbon (TOC), thereby boosting the microbial enzymes involved in nitrogen cycling. Metabolomic analysis revealed that aged TWPs upregulated key pathways related to carbon and nitrogen metabolism, enhancing plant growth and stress responses. Additionally, rhizosphere bacterial diversity was higher under aged TWPs, favoring nutrient-cycling taxa such as Acidobacteriota and Nitrospirota . Pristine TWPs may lead to overproliferation of certain dominant species, thereby reducing microbial diversity in soil, which could ultimately compromise the soil health. These findings contribute to a deeper understanding of the mechanisms underlying TWP toxicity in plants and highlight the necessity for further research on the impact of aged TWPs across various plant species over different exposure durations for comprehensive risk assessment.

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