UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

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.

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.

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.

Pseudobulbus Cremastrae seu Pleiones (PCsP), a traditional Chinese medicine known as ‶Shan-Ci-Gu″, possesses properties for clearing heat, counteracting toxicity, dissipating phlegm, and resolving masses. As a TCM with multiple bases, the dried pseudobulbs of Pleione bulbocodioides (PB), Pleione yunnanensis (PY) and Cremastra appendiculata (CA) are considered to be the official sources of PCsP. Additionally, several unofficial substitutes are also available in the market. To enhance the quality control of PCsP, an integrated strategy based on Q-marker was proposed. Initially, a study of integrating plant metabolomics, target isolation, structure identification, and activity testing afforded five Q-markers, including three new compounds. Furthermore, a quality evaluation method using a single standard to determine multi-components (SSDMC) based on Q-marker was established, which could effectively distinguish PB from CA and the counterfeit herbs. Finally, the transitivity of Q-markers was explored through a representative Chinese compound prescription containing PCsP. The results indicated that the identified Q-markers together with the established analysis methods could be effectively applied for quality control of PCsP and its preparations.

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.

The dried root of Bupleurum marginatum var. stenophyllum (H. Wolff) R.H. Shan & Y. Li (BM), which has been used as a Bupleuri radix in Guizhou Province and is listed in the 2003 edition of the Guizhou Quality Standard for Traditional Chinese Medicines and Ethnic Materia Medica, is effective at dispersing the liver and relieving depression and often used in the form of raw or vinegar-processed product (VBM). However, the potential depression-relieving components of BM are unclear. The aim of this study was to determine the potential antidepressant constituents of BM and investigate the effect of vinegar processing on these components. The antidepressant effect and mechanism of BM and VBM were investigated in depressed mice and BV2 cells, respectively. The pharmacodynamic constituents were screened through serum pharmacochemistry, which combined the results of metabolomics analysis of BM and VBM, high-performance liquid chromatography (HPLC) content determination, and verification of the antidepressant effect and mechanism of differential components of SSb2 to clarify the connotation of vinegar processing. Our results demonstrated that BM can exert a significant antidepressant effect by inhibiting microglia polarization and that this effect was enhanced after vinegar processing. Thirty-eight components were identified in the BM, 13 of which were blood-absorbable, mainly saponins, and defined as potential antidepressant components of the BM. The contents of 17 components-6 of which were absorbed into the blood-changed considerably after processing. It was finally determined that vinegar processing can enhance the antidepressant effect of BM by increasing the contents of SSb1 and SSb2. SSb2 exerts this effect via the samemechanism as BM. In conclusion, in this study we clarified the antidepressant effects and potential active components of BM and examined the mechanism of vinegar processing. These findings lay a foundation for the future research on the antidepressant effects of BM as well as for the complete development and application of BM\'s ethnomedicinal resources.

Medicinal plant metabolomics has emerged as a goldmine for the natural product chemists. It provides a pool of bioactive phytoconstituents leading to accelerated novel discoveries and the elucidation of a variety of biosynthetic pathways. Further, it also acts as an innovative tool for herbal medicine\'s scientific validation and quality assurance. This review highlights different strategies and analytical techniques employed in the practice of metabolomics. Further, it also discusses several other applications and advantages of metabolomics in the area of natural product chemistry. Additional examples of integrating metabolomics with multivariate data analysis techniques for some Indian medicinal plants are also reviewed. Recent technical advances in mass spectrometry-based hyphenated techniques, nuclear magnetic resonance-based techniques, and comprehensive hyphenated technologies for phytometabolite profiling studies have also been reviewed. Mass Spectral Imaging (MSI) has been presented as a highly promising method for high precision in situ spatiotemporal monitoring of phytometabolites. We conclude by introducing GNPS (Global Natural Products Social Molecular Networking) as an emerging platform to make social networks of related molecules, to explore data and to annotate more metabolites, and expand the networks to novel \"predictive\" metabolites that can be validated.

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