Spatial metabolomics using imaging mass spectrometry to identify the localization of asparaptine A in Asparagus officinalis

Current status of MSI research in Japan to measure the localization of natural products in plants

To understand biological functions in organisms, it is important to investigate what is happening in different locations in cells and tissues. The conventional approach is to extract compounds from whole tissue, and then to measure their concentrations or other characteristics using equipment tailored to the different molecules. Recent advances in mass spectrometry have made it possible to measure trace amounts of compounds. Mass spectrometry imaging (MSI), which uses positional information and mass spectrometry data to show where and how much of each compound is present in tissues, has been in the spotlight. Improvements in MSI over the past few decades have enabled its use for visualizing the localization of small molecules including drugs, lipids, and many other compounds in a range of organisms. MSI has also been used to clarify the localization of natural products in plant tissues. This review summarizes the recent research related to MSI technology in Japan.

Advances in mass spectrometry for metabolomics: Strategies, challenges, and innovations in disease biomarker discovery

Mass spectrometry (MS) plays a crucial role in metabolomics, especially in the discovery of disease biomarkers. This review outlines strategies for identifying metabolites, emphasizing precise and detailed use of MS techniques. It explores various methods for quantification, discusses challenges encountered, and examines recent breakthroughs in biomarker discovery. In the field of diagnostics, MS has revolutionized approaches by enabling a deeper understanding of tissue-specific metabolic changes associated with disease. The reliability of results is ensured through robust experimental design and stringent system suitability criteria. In the past, data quality, standardization, and reproducibility were often overlooked despite their significant impact on MS-based metabolomics. Progress in this field heavily depends on continuous training and education. The review also highlights the emergence of innovative MS technologies and methodologies. MS has the potential to transform our understanding of metabolic landscapes, which is crucial for disease biomarker discovery. This article serves as an invaluable resource for researchers in metabolomics, presenting fresh perspectives and advancements that propels the field forward.

The Roles of Functional Amino Acids in Plant Growth and Development

Plants incorporate acquired carbon and nitrogen into amino acid metabolism, whereby the building blocks of proteins and the precursors of various metabolites are produced. This fundamental demand requires tight amino acid metabolism to sustain physiological homeostasis. There is increasing evidence that amino acid metabolism undergoes plastic alteration to orchestrate specific growth and developmental events. Consequently, there has been a gradual exploration of the interface at which amino acid metabolism and plant morphogenesis are mutually affected. This research progress offers an opportunity to explore amino acid metabolism, with the goal to understand how it can be modulated to serve special cellular needs and regulate specific growth and developmental pathways. Continuous improvements in the sensitivity and coverage of metabolomics technology, along with the development of chemoinformatics, have allowed the investigation of these research questions. In this review, we summarize the roles of threonine, serine, arginine and γ-aminobutyric acid as representative examples of amino acids relevant to specific developmental processes in plants ('functional amino acids'). Our objective is to expand perspectives regarding amino acid metabolism beyond the conventional view that it is merely life-supporting machinery.

Single-cell and spatial multi-omics in the plant sciences: Technical advances, applications, and perspectives

Plants contain a large number of cell types and exhibit complex regulatory mechanisms. Studies at the single-cell level have gradually become more common in plant science. Single-cell transcriptomics, spatial transcriptomics, and spatial metabolomics techniques have been combined to analyze plant development. These techniques have been used to study the transcriptomes and metabolomes of plant tissues at the single-cell level, enabling the systematic investigation of gene expression and metabolism in specific tissues and cell types during defined developmental stages. In this review, we present an overview of significant breakthroughs in spatial multi-omics in plants, and we discuss how these approaches may soon play essential roles in plant research.

A mass spectrometry imaging approach on spatiotemporal distribution of multiple alkaloids in Gelsemium elegans

Gelsemium elegans contains multiple alkaloids with pharmacological effects, thus researchers focus on the identification and application of alkaloids extracted from G. elegans. Regretfully, the spatiotemporal distribution of alkaloids in G. elegans is still unclear. In this study, the desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was applied to simultaneously analyze the distribution of pharmacologically important alkaloids in different organ/tissue sections of G. elegans at different growth stages. Finally, 23 alkaloids were visualized in roots, stems and leaves at seedling stage and 19 alkaloids were observed at mature stage. In mature G. elegans, 16 alkaloids were distributed in vascular bundle region of mature roots, 15 alkaloids were mainly located in the pith region of mature stems and 2 alkaloids were enriched in epidermis region of mature stems. A total of 16 alkaloids were detected in leaf veins of mature leaves and 17 alkaloids were detected in shoots. Interestingly, diffusion and transfer of multiple alkaloids in tissues have been observed along with the development and maturation. This study comprehensively characterized the spatial metabolomics of G. elegans alkaloids, and the spatiotemporal distribution of alkaloid synthesis. In addition, the results also have reference value for the development and application of Gelsemium elegans and other medicinal plants.

Identification of key pharmacodynamic markers of American ginseng against heart failure based on metabolomics and zebrafish model

Background: American ginseng (Panax quinquefolium L., AG) is a traditional Chinese medicine with multiple cardiovascular protective properties. Many bioactive components have been discovered in AG over these years. However, the understanding of these key pharmacodynamic components of activity against heart failure is insufficient.

Methods: A heart failure model was established using AB line wild-type zebrafish (Danio rerio) to evaluate the anti-heart failure activity of AG. Untargeted metabolomics analysis based on ultra-high performance liquid chromatography-quadrupole electrostatic field orbitrap-mass spectrometry technology (UHPLC-QE-Orbitrap-MS) was performed to screen differential components from AG samples. The potential active components were verified using the zebrafish model. Simultaneously, network pharmacology and molecular docking techniques were used to predict the possible mechanism. Finally, the key targets of six key pharmacodynamic components were verified in zebrafish using quantitative real-time-polymerase chain reaction (Q-PCR) techniques.

Results: The heart failure model was successfully established in 48 h of post-fertilization (hpf) zebrafish larvae by treating with verapamil hydrochloride. The zebrafish assay showed that the anti-heart failure effects of AG varied with producing regions. The result of the herbal metabolomic analysis based on UHPLC-QE-Orbitrap-MS indicated that ginsenoside Rg3, ginsenoside Rg5, ginsenoside Rg6, malic acid, quinic acid, L-argininosuccinic acid, 3-methyl-3-butenyl-apinosyl (1→6) glucoside, pseudoginsenoside F11, and annonaine were differential components, which might be responsible for variation in efficacy. Further analysis using zebrafish models, network pharmacology, and Q-PCR techniques showed that ginsenoside Rg3, ginsenoside Rg5, ginsenoside Rg6, malic acid, quinic acid, and pseudoginsenoside F11 were the pharmacodynamic markers (P-markers) responsible for anti-heart failure.

Conclusion: We have rapidly identified the P-markers against heart failure in AG using the zebrafish model and metabolomics technology. These P-markers may provide new reference standards for quality control and new drug development of AG.