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Metabolites
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Metabolomics in Plant Natural Products Research
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Metabolomics in Plant Natural Products Research

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Plant Metabolism".

Deadline for manuscript submissions: closed (15 January 2025) | Viewed by 9593

Special Issue Editor

Prof. Dr. Junsong Wang

E-Mail Website
Guest Editor
Center for Molecular Metabolism, School of Environmental & Biological Engineering, Nanjing University of Science & Technology, Nanjing 210094, China
Interests: functional metabolomics; natural products chemistry; traditional Chinese medicines; bioinformatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue on plant natural product research and metabolomics aims to bring together works that advance our understanding of plant–environment interactions, the determination of chemical markers, and the prioritization and targeted isolation of active principles from medicinal plants. The natural products from plants have been a reliable source of potential drug-active components, and the bioactivity of natural extracts can be characterized by the synergism between different metabolites. Metabolomic approaches, such as LC/MS, GC/MS, and NMR, are appropriate ways to assess the complex interactions and to identify the different factors that may affect the production and accumulation of specialized metabolites in different species.

Prof. Dr. Junsong Wang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • natural products
  • metabolomics
  • plant–environment interactions
  • chemical markers
  • active principles
  • LC/MS
  • GC/MS
  • NMR

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Published Papers (6 papers)

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Research

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19 pages, 11976 KiB  
Article
Metabolome Profiling and Predictive Modeling of Dark Green Leaf Trait in Bunching Onion Varieties
by Tetsuya Nakajima, Mari Kobayashi, Masato Fuji, Kouei Fujii, Mostafa Abdelrahman, Yasumasa Matsuoka, Jun’ichi Mano, Muneo Sato, Masami Yokota Hirai, Naoki Yamauchi and Masayoshi Shigyo
Metabolites 2025, 15(4), 226; https://doi.org/10.3390/metabo15040226 - 26 Mar 2025
Viewed by 1035
Abstract
Background: The dark green coloration of bunching onion leaf blades is a key determinant of market value, nutritional quality, and visual appeal. This trait is regulated by a complex network of pigment interactions, which not only determine coloration but also serve as critical [...] Read more.
Background: The dark green coloration of bunching onion leaf blades is a key determinant of market value, nutritional quality, and visual appeal. This trait is regulated by a complex network of pigment interactions, which not only determine coloration but also serve as critical indicators of plant growth dynamics and stress responses. This study aimed to elucidate the mechanisms regulating the dark green trait and develop a predictive model for accurately assessing pigment composition. These advancements enable the efficient selection of dark green varieties and facilitate the establishment of optimal growth environments through plant growth monitoring. Methods: Seven varieties and lines of heat-tolerant bunching onions were analyzed, including two commercial F1 cultivars, along with two purebred varieties and three F1 hybrid lines bred in Yamaguchi Prefecture. The analysis was conducted on visible spectral reflectance data (400–700 nm at 20 nm intervals) and pigment compounds (chlorophyll a, chlorophyll b and pheophytin a, lutein, and β-carotene), whereas primary and secondary metabolites were assessed by using widely targeted metabolomics. In addition, a random forest regression model was constructed by using spectral reflectance data and pigment compound contents. Results: Principal component analysis based on spectral reflectance data and the comparative profiling of 186 metabolites revealed characteristic metabolite accumulation associated with each green color pattern. The “green” group showed greater accumulation of sugars, the “gray green” group was characterized by the accumulation of phenolic compounds, and the “dark green” group exhibited accumulation of cyanidins. These metabolites are suggested to accumulate in response to environmental stress, and these differences are likely to influence green coloration traits. Furthermore, among the regression models for estimating pigment compound contents, the one for chlorophyll a content achieved high accuracy, with an R2 value of 0.88 in the test dataset and 0.78 in Leave-One-Out Cross-Validation, demonstrating its potential for practical application in trait evaluation. However, since the regression model developed in this study is based on data obtained from greenhouse conditions, it is necessary to incorporate field trial results and reconstruct the model to enhance its adaptability. Conclusions: This study revealed that cyanidin is involved in the characteristics of dark green varieties. Additionally, it was demonstrated that chlorophyll a can be predicted using visible spectral reflectance. These findings suggest the potential for developing markers for the dark green trait, selecting high-pigment-accumulating varieties, and facilitating the simple real-time diagnosis of plant growth conditions and stress status, thereby enabling the establishment of optimal environmental conditions. Future studies will aim to elucidate the genetic factors regulating pigment accumulation, facilitating the breeding of dark green varieties with enhanced coloration traits for summer cultivation. Full article
(This article belongs to the Special Issue Metabolomics in Plant Natural Products Research)
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17 pages, 6426 KiB  
Article
NMR-Based Metabolomics Analysis of Metabolite Profiles in Two Species of Boletes Subjected to Different Drying Methods
by Yangzong Zhuoma, Minghong Yang, Yijie Chen, Xiangxi Zhang, Xingyan Duan, Hongwei Cui, Xin Fang and Xujia Hu
Metabolites 2025, 15(3), 152; https://doi.org/10.3390/metabo15030152 - 23 Feb 2025
Viewed by 530
Abstract
Background: Wild boletes are famous for their exceptional flavor and nutritional value. Due to their susceptibility to decay and spoilage, dry storage is a common method for processing and preservation. However, few studies have reported on the alterations of metabolites of boletes resulting [...] Read more.
Background: Wild boletes are famous for their exceptional flavor and nutritional value. Due to their susceptibility to decay and spoilage, dry storage is a common method for processing and preservation. However, few studies have reported on the alterations of metabolites of boletes resulting from different drying methods. This paper aims to investigate the metabolic changes in two species of boletes, Butyriboletus roseoflavus and Lanmaoa asiatica, subjected to three drying methods: hot-air drying, microwave drying, and freeze drying. Method and Result: Nuclear magnetic resonance (NMR) metabolomics was utilized for multivariate data analysis. In total, 27 metabolites were identified from the two species of boletes, including amino acids such as glutamate and leucine, sugars like glucose and sucrose, and alkaloids like choline. Among these, 17 metabolites were classified as differential metabolites, comprising 12 amino acids, 4 sugars, and 1 alkaloid. Differential metabolites were quantified by quantitative NMR (qNMR), and these metabolites were subsequently analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database for pathway enrichment analysis. KEGG pathway analysis revealed that the different drying methods resulted in significantly distinct metabolic pathways for these differential metabolites, resulting in the enrichment of amino acid metabolism and starch and sucrose metabolism pathways. Conclusions: This metabolomics study elucidates the differences in metabolite composition and abundance between the two species of boletes, providing a theoretical foundation for selecting appropriate drying methods for their preservation. Full article
(This article belongs to the Special Issue Metabolomics in Plant Natural Products Research)
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18 pages, 1123 KiB  
Article
Development of a Dispersive Liquid–Liquid Microextraction Method for Quantification of Volatile Compounds in Wines Using Gas Chromatography–Mass Spectrometry
by Dinesha Katugampala Appuhamilage, Rebecca E. Jelley, Emma Sherman, Lisa I. Pilkington, Farhana R. Pinu and Bruno Fedrizzi
Metabolites 2025, 15(2), 129; https://doi.org/10.3390/metabo15020129 - 13 Feb 2025
Viewed by 683
Abstract
Background/Objectives: This study reports the development of a straightforward, efficient, and cost-effective dispersive liquid–liquid microextraction (DLLME) method for the gas chromatography–mass spectrometry (GC-MS) analysis of volatile compounds present in wine. Methods: Four critical parameters were optimised using a D-optimal design to [...] Read more.
Background/Objectives: This study reports the development of a straightforward, efficient, and cost-effective dispersive liquid–liquid microextraction (DLLME) method for the gas chromatography–mass spectrometry (GC-MS) analysis of volatile compounds present in wine. Methods: Four critical parameters were optimised using a D-optimal design to maximise extraction outcomes of the targeted analytes from a 10 mL sample, while minimising interference from other compounds. The analytical characteristics of the method were assessed using 36 target compounds. Results: The method provided satisfactory linearity (correlation coefficients > 0.990), good repeatability for both for intra- and inter-day measurements (RSD < 10.3%), and suitable recoveries of target analytes from both model (83–110%) and real matrices (80–120%). The validated method was subsequently applied to analyse the aroma profile of 30 New Zealand Pinot noir (PN) wine samples. Conclusions: This study contributes to the advancement of analytical techniques available to both industry and researchers to explore the complex aroma profiles of wines. Full article
(This article belongs to the Special Issue Metabolomics in Plant Natural Products Research)
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20 pages, 7485 KiB  
Article
Comparative Evaluation of the Chemical Components and Anti-Inflammatory Potential of Yellow- and Blue-Flowered Meconopsis Species: M. integrifolia and M. betonicifolia
by Peizhao Cheng, Ruixi Gan, Cong Wang, Qian Xu, Kelsang Norbu, Feng Zhou, Sixin Kong, Zhuoma Jia, Dawa Jiabu, Xin Feng and Junsong Wang
Metabolites 2024, 14(10), 563; https://doi.org/10.3390/metabo14100563 - 20 Oct 2024
Viewed by 1575
Abstract
Background/Objectives: Meconopsis has long been used in traditional Tibetan medicine to treat various inflammatory and pain-related conditions. However, blue-flowered Meconopsis (M. betonicifolia) is becoming increasingly scarce due to overharvesting. As a potential alternative, yellow-flowered Meconopsis (M. integrifolia) shows [...] Read more.
Background/Objectives: Meconopsis has long been used in traditional Tibetan medicine to treat various inflammatory and pain-related conditions. However, blue-flowered Meconopsis (M. betonicifolia) is becoming increasingly scarce due to overharvesting. As a potential alternative, yellow-flowered Meconopsis (M. integrifolia) shows promise but requires comprehensive characterization. This study aimed to evaluate and compare the anti-inflammatory potential of yellow- and blue-flowered Meconopsis species. Methods: Liquid chromatography–mass spectrometry (LC-MS) techniques were used to analyze the chemical profiles of yellow- and blue-flowered Meconopsis. Putative targets of shared constituents were subjected to GO and disease enrichment analysis. The LPS-induced RAW264.7 macrophage model was employed to assess anti-inflammatory effects. Metabolomics was applied to gain mechanistic insights. Results: LC-MS revealed over 70% chemical similarity between species. Enrichment analysis associated targets with inflammation-related pathways. In macrophage assays, both species demonstrated dose-dependent antioxidative and anti-inflammatory activities, with yellow Meconopsis exhibiting superior efficacy. Metabolomics showed modulation of key inflammatory metabolic pathways. Conclusions: This integrative study validated yellow-flowered Meconopsis as a credible alternative to its blue-flowered counterpart for anti-inflammatory applications. Metabolic profiling provided initial clues regarding their multi-targeted modes of action, highlighting their potential for sustainable utilization and biodiversity conservation. Full article
(This article belongs to the Special Issue Metabolomics in Plant Natural Products Research)
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14 pages, 3423 KiB  
Article
Exploring Metabolic Characteristics in Different Geographical Locations and Yields of Nicotiana tabacum L. Using Gas Chromatography–Mass Spectrometry Pseudotargeted Metabolomics Combined with Chemometrics
by Yuan Jing, Wei Chen, Xuebai Qiu, Shuyue Qin, Weichang Gao, Chaochan Li, Wenxuan Quan and Kai Cai
Metabolites 2024, 14(4), 176; https://doi.org/10.3390/metabo14040176 - 22 Mar 2024
Cited by 4 | Viewed by 1864
Abstract
The quality of crops is closely associated with their geographical location and yield, which is reflected in the composition of their metabolites. Hence, we employed GC–MS pseudotargeted metabolomics to investigate the metabolic characteristics of high-, medium-, and low-yield Nicotiana tabacum (tobacco) leaves from [...] Read more.
The quality of crops is closely associated with their geographical location and yield, which is reflected in the composition of their metabolites. Hence, we employed GC–MS pseudotargeted metabolomics to investigate the metabolic characteristics of high-, medium-, and low-yield Nicotiana tabacum (tobacco) leaves from the Bozhou (sweet honey flavour) and Shuicheng (light flavour) regions of Guizhou Province. A total of 124 metabolites were identified and classified into 22 chemical categories. Principal component analysis revealed that the geographical location exerted a greater influence on the metabolic profiling than the yield. Light-flavoured tobacco exhibited increased levels of sugar metabolism- and glycolysis-related intermediate products (trehalose, glucose-6-phosphate, and fructose-6-phosphate) and a few amino acids (proline and leucine), while sweet honey-flavoured tobacco exhibited increases in the tricarboxylic acid cycle (TCA cycle) and the phenylpropane metabolic pathway (p-hydroxybenzoic acid, caffeic acid, and maleic acid). Additionally, metabolite pathway enrichment analysis conducted at different yields and showed that both Shuicheng and Bozhou exhibited changes in six pathways and four of them were the same, mainly C/N metabolism. Metabolic pathway analysis revealed higher levels of intermediates related to glycolysis and sugar, amino acid, and alkaloid metabolism in the high-yield samples, while higher levels of phenylpropane in the low-yield samples. This study demonstrated that GC–MS pseudotargeted metabolomics-based metabolic profiling can be used to effectively discriminate tobacco leaves from different geographical locations and yields, thus facilitating a better understanding of the relationship between metabolites, yield, and geographical location. Consequently, metabolic profiles can serve as valuable indicators for characterizing tobacco yield and geographical location. Full article
(This article belongs to the Special Issue Metabolomics in Plant Natural Products Research)
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26 pages, 1978 KiB  
Systematic Review
Evaluating the Metabolomic Profile and Anti-Pathogenic Properties of Cannabis Species
by Shadrack Monyela, Prudence Ngalula Kayoka, Wonder Ngezimana and Lufuno Ethel Nemadodzi
Metabolites 2024, 14(5), 253; https://doi.org/10.3390/metabo14050253 - 26 Apr 2024
Cited by 5 | Viewed by 2785
Abstract
The Cannabis species is one of the potent ancient medicinal plants acclaimed for its medicinal properties and recreational purposes. The plant parts are used and exploited all over the world for several agricultural and industrial applications. For many years Cannabis spp. has proven [...] Read more.
The Cannabis species is one of the potent ancient medicinal plants acclaimed for its medicinal properties and recreational purposes. The plant parts are used and exploited all over the world for several agricultural and industrial applications. For many years Cannabis spp. has proven to present a highly diverse metabolomic profile with a pool of bioactive metabolites used for numerous pharmacological purposes ranging from anti-inflammatory to antimicrobial. Cannabis sativa has since been an extensive subject of investigation, monopolizing the research. Hence, there are fewer studies with a comprehensive understanding of the composition of bioactive metabolites grown in different environmental conditions, especially C. indica and a few other Cannabis strains. These pharmacological properties are mostly attributed to a few phytocannabinoids and some phytochemicals such as terpenoids or essential oils which have been tested for antimicrobial properties. Many other discovered compounds are yet to be tested for antimicrobial properties. These phytochemicals have a series of useful properties including anti-insecticidal, anti-acaricidal, anti-nematicidal, anti-bacterial, anti-fungal, and anti-viral properties. Research studies have reported excellent antibacterial activity against Gram-positive and Gram-negative multidrug-resistant bacteria as well as methicillin-resistant Staphylococcus aureus (MRSA). Although there has been an extensive investigation on the antimicrobial properties of Cannabis, the antimicrobial properties of Cannabis on phytopathogens and aquatic animal pathogens, mostly those affecting fish, remain under-researched. Therefore, the current review intends to investigate the existing body of research on metabolomic profile and anti-microbial properties whilst trying to expand the scope of the properties of the Cannabis plant to benefit the health of other animal species and plant crops, particularly in agriculture. Full article
(This article belongs to the Special Issue Metabolomics in Plant Natural Products Research)
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