Phytochemical Analysis最新文献

{"title":"Rapid mitragynine quantification and fingerprinting of products from Mitragyna speciosa Korth. leaf (Kratom) using high-performance thin-layer chromatography.","authors":"Toveelah Hayeema, Juraithip Wungsintaweekul","doi":"10.1002/pca.3442","DOIUrl":"10.1002/pca.3442","url":null,"abstract":"<p><strong>Introduction: </strong>Kratom (leaves from Mitragyna speciosa Korth.; Rubiaceae) is a herbal medicine known for its analgesic properties and psychoactive effects. Kratom in Thailand is currently legal; however, it is prohibited in some countries and considered a narcotic plant.</p><p><strong>Objective: </strong>Our aim was to establish a reliable, simple, and rapid method for quantifying mitragynine in Kratom leaves and related products through a combination of high-performance thin-layer chromatography (HPTLC) and densitometry.</p><p><strong>Methodology: </strong>A densitometric HPTLC method was developed and validated in terms of specificity, linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, and robustness. The fingerprints of kratom leaves, Mitragyna spp., and related products were constructed.</p><p><strong>Results: </strong>For HPTLC, samples were applied to silica gel 60 F₂₅₄ plates, and the mobile phase comprised n-hexane, ethyl acetate, and triethylamine (1:1:0.15, v/v/v). Densitometric detection was carried out under ultraviolet light at a wavelength of 226 nm. The validated method exhibited a range of 14.31-143.10 μg/mL, yielding a correlation coefficient of 0.9993. Spiked recovery rates were within a range of 98.3%-100.9%, and the LOD and LOQ were 3.80 and 11.53 μg/mL, respectively. Kratom samples were analyzed with the developed method, and the correlation coefficient was 0.9641, compared to the high-performance liquid chromatography-diode-array detection (HPLC-DAD) method. The HPTLC fingerprints displayed a distinctive pattern, facilitating discrimination among different plant parts and Mitragyna spp.</p><p><strong>Conclusion: </strong>The established method offers the advantages of simplicity, ease of use, and speed of analysis, serving as a practical alternative for mitragynine quantification in kratom leaf and its related products.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"296-306"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142081254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial metabolomics method to reveal the differences in chemical composition of raw and honey-fried Stemona tuberosa Lour. by using UPLC-Orbitrap Fusion MS and desorption electrospray ionization mass spectrometry imaging.","authors":"Haixuan Xiong, Shuding Sun, Weiwei Zhang, Di Zhao, Xuefang Liu, Yange Tian, Suxiang Feng","doi":"10.1002/pca.3428","DOIUrl":"10.1002/pca.3428","url":null,"abstract":"<p><strong>Introduction: </strong>Stemona tuberosa Lour. (ST) is a significant traditional Chinese medicine (TCM) renowned for its antitussive and insecticidal properties. ST is commonly subjected to processing in clinical practice before being utilized as a medicinal substance. Currently, the customary technique for processing ST is honey-fried. Nevertheless, the specific variations in chemical constituents of ST before and after honey-fried remain unclear.</p><p><strong>Objective: </strong>This work aimed to analyze the variations in chemical constituents of ST before and after honey-fried and to study the distribution of differential markers in the roots.</p><p><strong>Methods: </strong>UPLC-Orbitrap Fusion MS combined with molecular network analysis was used to analyze the metabolome of ST and honey-fried ST (HST) and to screen the differential metabolites by multivariate statistical analysis. Spatial metabolomics was applied to study the distribution of differential metabolites by desorption electrospray ionization mass spectrometry imaging (DESI-MSI).</p><p><strong>Results: </strong>The ST and HST exhibited notable disparities, with 56 and 61 chemical constituents found from each, respectively. After processing, the types of alkaloids decreased, and 12 differential metabolites were screened from the common compounds. The notable component variations were epibisdehydro-tuberostemonine J, neostenine, tuberostemonine, croomine, neotuberostemonine, and so forth. MSI visualized the spatial distribution of differential metabolites.</p><p><strong>Conclusions: </strong>Our research provided a rapid and effective visualization method for the identification and spatial distribution of metabolites in ST. Compared with the traditional method, this method offered more convincing data supporting the processing mechanism investigations of Stemona tuberosa from a macroscopic perspective.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"166-180"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141788853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling Colombia's medicinal Cannabis sativa treasure trove: Phenotypic and Chemotypic diversity in legal cultivation.","authors":"Diego J Enríquez, Julio C Alonso, Lucas Hille, Stefan Brand, Ulrike Holzgrabe, Daniela Vergara, Guillermo Montoya, Yesid A Ramírez","doi":"10.1002/pca.3436","DOIUrl":"10.1002/pca.3436","url":null,"abstract":"<p><strong>Introduction: </strong>Cannabis sativa is a highly versatile plant with a long history of cultivation and domestication. It produces multiple compounds that exert distinct and valuable therapeutic effects by modulating diverse biological systems, including the endocannabinoid system (ECS). Access to standardized, metabolically diverse, and reproducible C. sativa chemotypes and chemovars is essential for physicians to optimize individualized patient treatment and for industries to conduct drug-discovery campaigns.</p><p><strong>Objective: </strong>This study aimed to characterize and assess the phytochemical diversity of C. sativa chemotypes in diverse ecological regions of Colombia, South America.</p><p><strong>Methodology: </strong>Ten cannabinoids and 23 terpenes were measured using liquid and gas chromatography, in addition to other phenotypic traits, in 156 C. sativa plants that were grown in diverse ecological regions in Colombia, a hotspot for global biodiversity.</p><p><strong>Results: </strong>Our results reveal significant phytochemical diversity in Colombian-grown C. sativa plants, with four distinct chemotypes based on cannabinoid profile. The significant amount of usually uncommon terpenes suggests that Colombia's environments may have unique capabilities that allow the plant to express these compounds. Colombia's diverse climates offer enormous cultivation potential, making it a key player in both domestic and international medicinal and recreational C. sativa trade.</p><p><strong>Conclusion: </strong>These findings underscore Colombia's capacity to pioneer global C. sativa production diversification, particularly in South America with new emerging markets.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"246-260"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142018289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Degradation of andrographolide in Andrographis paniculata over 1 year storage.","authors":"Md Tanvin Ahammed, Md Zakir Sultan, Md Sabbir Hossain, Mamun Al Mahtab, Sitesh Chandra Bachar","doi":"10.1002/pca.3441","DOIUrl":"10.1002/pca.3441","url":null,"abstract":"<p><strong>Introduction: </strong>Andrographolide is a bioactive component found in the medicinal herb Andrographis paniculata (Burm. f.) Wall. ex Nees (Family-Acanthaceae) is well-known for its ability to cure liver disorders and as a bitter tonic.</p><p><strong>Objective: </strong>In this study, the rate of degradation of andrographolide was examined over the course of a year of storage.</p><p><strong>Materials and methods: </strong>New and old (1-year storage) A. paniculata powder samples were used in the study. High-performance liquid chromatography (HPLC) was used to assess the concentration of andrographolide after its extraction using ethanol as the solvent.</p><p><strong>Results: </strong>The findings demonstrated a 69.26% progressive deterioration of andrographolide over the storage period. Temperature and crystallinity are two factors that affect how quickly andrographolide degrades.</p><p><strong>Conclusion: </strong>The results emphasize how crucial it is to retain the effectiveness of A. paniculata extract by avoiding prolonged storage or by providing ideal storage conditions.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"289-295"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142110844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolomics-based profiling of five Salvia L. (Lamiaceae) species using untargeted data analysis workflow.","authors":"Navaz Kharazian, Farzaneh Jafari Dehkordi, Chun-Lei Xiang","doi":"10.1002/pca.3423","DOIUrl":"10.1002/pca.3423","url":null,"abstract":"<p><strong>Introduction: </strong>The genus Salvia L., a member of the family Lamiaceae, is a keystone genus with a wide range of medicinal properties. It possesses a rich metabolite source that has long been used to treat different disorders.</p><p><strong>Objectives: </strong>Due to a deficiency of untargeted metabolomic profiling in the genus Salvia, this work attempts to investigate a comprehensive mass spectral library matching, computational data annotations, exclusive biomarkers, specific chemotypes, intraspecific metabolite profile variation, and metabolite enrichment by a case study of five medicinal species of Salvia.</p><p><strong>Material and methods: </strong>Aerial parts of each species were subjected to QTRAP liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis workflow based on untargeted metabolites. A comprehensive and multivariate analysis was acquired on the metabolite dataset utilizing MetaboAnalyst 6.0 and the Global Natural Products Social Molecular Networking (GNPS) Web Platform.</p><p><strong>Results: </strong>The untargeted approach empowered the identification of 117 metabolites by library matching and 92 nodes annotated by automated matching. A machine learning algorithm as substructural topic modeling, MS2LDA, was further implemented to explore the metabolite substructures, resulting in four Mass2Motifs. The automated library newly discovered a total of 23 metabolites. In addition, 87 verified biomarkers of library matching, 58 biomarkers of GNPS annotations, and 11 specific chemotypes were screened.</p><p><strong>Conclusion: </strong>Integrative spectral library matching and automated annotation by the GNPS platform provide comprehensive metabolite profiling through a workflow. In addition, QTRAP LC-MS/MS with multivariate analysis unveiled reliable information about inter and intraspecific levels of differentiation. The rigorous investigation of metabolite profiling presents a large-scale overview and new insights for chemotaxonomy and pharmaceutical studies.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"113-143"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141604022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HerbMet: Enhancing metabolomics data analysis for accurate identification of Chinese herbal medicines using deep learning.","authors":"Yuyang Sha, Meiting Jiang, Gang Luo, Weiyu Meng, Xiaobing Zhai, Hongxin Pan, Junrong Li, Yan Yan, Yongkang Qiao, Wenzhi Yang, Kefeng Li","doi":"10.1002/pca.3437","DOIUrl":"10.1002/pca.3437","url":null,"abstract":"<p><strong>Introduction: </strong>Chinese herbal medicines have been utilized for thousands of years to prevent and treat diseases. Accurate identification is crucial since their medicinal effects vary between species and varieties. Metabolomics is a promising approach to distinguish herbs. However, current metabolomics data analysis and modeling in Chinese herbal medicines are limited by small sample sizes, high dimensionality, and overfitting.</p><p><strong>Objectives: </strong>This study aims to use metabolomics data to develop HerbMet, a high-performance artificial intelligence system for accurately identifying Chinese herbal medicines, particularly those from different species of the same genus.</p><p><strong>Methods: </strong>We propose HerbMet, an AI-based system for accurately identifying Chinese herbal medicines. HerbMet employs a 1D-ResNet architecture to extract discriminative features from input samples and uses a multilayer perceptron for classification. Additionally, we design the double dropout regularization module to alleviate overfitting and improve model's performance.</p><p><strong>Results: </strong>Compared to 10 commonly used machine learning and deep learning methods, HerbMet achieves superior accuracy and robustness, with an accuracy of 0.9571 and an F1-score of 0.9542 for distinguishing seven similar Panax ginseng species. After feature selection by 25 different feature ranking techniques in combination with prior knowledge, we obtained 100% accuracy and an F1-score for discriminating P. ginseng species. Furthermore, HerbMet exhibits acceptable inference speed and computational costs compared to existing approaches on both CPU and GPU.</p><p><strong>Conclusions: </strong>HerbMet surpasses existing solutions for identifying Chinese herbal medicines species. It is simple to use in real-world scenarios, eliminating the need for feature ranking and selection in classical machine learning-based methods.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"261-272"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142009256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive identification of polyphenolic metabolites in aspen knotwood by combination of 2D NMR and HPLC-HRMS.","authors":"Anna V Faleva, Danil I Falev, Aleksandra A Onuchina, Nikolay V Ulyanovskii, Dmitry S Kosyakov","doi":"10.1002/pca.3443","DOIUrl":"10.1002/pca.3443","url":null,"abstract":"<p><strong>Introduction: </strong>European aspen (Populus tremula L.) knotwood contains large amounts of polyphenolic metabolites, mainly flavonoids, and can be considered as a promising industrial-scale source of valuable bioactive compounds. Valorization of knotwood extractives requires detailed information on their chemical composition and a relevant analytical methodology.</p><p><strong>Objective: </strong>This study proposes combined analytical strategy for non-targeted screening and identification of polyphenolic plant metabolites and is aimed at comprehensive characterization of knotwood extractives.</p><p><strong>Materials and methods: </strong>Aspen knotwood acetone extract with determined antioxidant activity was an object of the study. Two-dimensional NMR spectroscopy with Structure Elucidator expert system was used for preliminary search of major components and specific structures. Liquid chromatography-high-resolution mass spectrometry (HPLC-HRMS) with data-dependent MS/MS spectra acquisition was used as a complementary technique providing molecular-level characterization and identification of the detected metabolites.</p><p><strong>Results: </strong>Twenty-eight phenolic metabolites were found and identified. Among them, flavonoids, aromadendrin and naringenin, as well as their glycosylated derivatives (mainly O-glucosides) and methyl ethers, dominated. Taxifolin and its 7-O-glucoside were detected as minor components. Other detected compounds are represented by p-coumaric acid and its rutinoside and small amounts of glycosylated ferulic acid. Nineteen of the detected compounds were discovered in aspen knotwood for the first time. The results were confirmed by preparative isolation of individual compounds and NMR studies.</p><p><strong>Conclusion: </strong>The proposed analytical strategy based on 2D NMR and HPLC-HRMS can be considered a powerful tool in the analysis of plant extractives and allowed for the identification and semi-quantification of a large number of polyphenols in aspen knotwood.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"307-316"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142120444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A strategy to distinguish similar traditional Chinese medicines by liquid chromatography-mass spectrometry, electronic senses, and gas chromatography-ion mobility spectrometry: Marsdeniae tenacissimae Caulis and Paederiae scandens Caulis as examples.","authors":"Jia-Wei Wang, Zhi-Dong Pei, Yue-Hua Chen, Si-Yu Li, Tian-Min Wang, Ting-Guo Kang, Na Li, Ya-Mei Song, Hui-Peng Song, Hui Zhang","doi":"10.1002/pca.3425","DOIUrl":"10.1002/pca.3425","url":null,"abstract":"<p><strong>Introduction: </strong>Marsdeniae tenacissimae Caulis (MTC), a popular traditional Chinese medicine, has been widely used in the treatment of tumor diseases. Paederiae scandens Caulis (PSC), which is similar in appearance to MTC, is a common counterfeit product. It is difficult for traditional methods to effectively distinguish between MTC and PSC. Therefore, there is an urgent need for a rapid and accurate method to identify MTC and PSC.</p><p><strong>Objectives: </strong>The aim is to distinguish between MTC and PSC by analyzing the differences in nonvolatile organic compounds (NVOCs), taste, odor, and volatile organic compounds (VOCs).</p><p><strong>Methods: </strong>Liquid chromatography-mass spectrometry (LC-MS) was utilized to analyze the NVOCs of MTC and PSC. Electronic tongue (E-tongue) and electronic nose (E-nose) were used to analyze their taste and odor respectively. Gas chromatography-ion mobility spectrometry (GC-IMS) was applied to analyze VOCs. Finally, multivariate statistical analyses were conducted to further investigate the differences between MTC and PSC, including principal component analysis, orthogonal partial least squares discriminant analysis, discriminant factor analysis, and soft independent modeling of class analysis.</p><p><strong>Results: </strong>The results of this study indicate that the integrated strategy of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis can be effectively applied to distinguish between MTC and PSC. Using LC-MS, 25 NVOCs were identified in MTC, while 18 NVOCs were identified in PSC. The major compounds in MTC are steroids, while the major compounds in PSC are iridoid glycosides. Similarly, the distinct taste difference between MTC and PSC was precisely revealed by the E-tongue. Specifically, the pronounced bitterness in PSC was proven to stem from iridoid glycosides, whereas the bitterness evident in MTC was intimately tied to steroids. The E-nose detected eight odor components in MTC and six in PSC, respectively. The subsequent statistical analysis uncovered notable differences in their odor profiles. GC-IMS provided a visual representation of the differences in VOCs between MTC and PSC. The results indicated a relatively high relative content of 82 VOCs in MTC, contrasted with 32 VOCs exhibiting a similarly high relative content in PSC.</p><p><strong>Conclusion: </strong>In this study, for the first time, the combined use of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis has proven to be an effective method for distinguishing between MTC and PSC from multiple perspectives. This approach provides a valuable reference for the identification of other visually similar traditional Chinese medicines.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"144-155"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141734910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative study on metabolite variations of two rose teas by plant metabolomics and revealing their skin-whitening candidates by spectrum-effect relationship analysis.","authors":"Jian Xu, Hongwei Ye, Xindan Zhang, Yangbin Lv, Shengqiang Tong, Biao Liu, Zhimin Ou, Chu Chu","doi":"10.1002/pca.3420","DOIUrl":"10.1002/pca.3420","url":null,"abstract":"<p><strong>Introduction: </strong>Rosa rugosa var. plena Rehd (CBR) and Rosa chinensis cv. \"JinBian\" (JBR) are two common species used in rose tea among different original species. CBR, the officially documented original plant of the rose species for food and medicinal purposes, is more costly than JBR. With increasing demand for different rose teas, it is meaningful to compare the chemical constituents for their quality control and reveal their skin-whitening components that will provide in-depth insights for the expansion of the rose tea industry.</p><p><strong>Objective: </strong>This study aims to reveal the chemical variances between CBR and JBR and determine their skin-whitening components.</p><p><strong>Methodology: </strong>A strategy obtained by combining MS-based plant-metabolomics with spectrum-effect relationship analysis has been proposed for unveiling chemical differences between CBR and JBR and further exploring their potential skin-whitening components.</p><p><strong>Results: </strong>A total of 2030 metabolites were found that revealed considerable differences between CBR and JBR. The results of bioactivity assay demonstrated that JBR exhibited stronger tyrosinase inhibition activity than CBR. Six potential skin-whitening compounds (di-O-galloyl-HHDP-glucoside, tri-O-galloyl-HHDP-glucoside, spiraeoside, quinic acid, rugosin A, and 1,2,3,6-tetra-O-galloyl-glucose) were discovered as potential tyrosinase inhibitors, via spectrum-effect relationship analysis. This is the first time that di-O-galloyl-HHDP-glucoside, tri-O-galloyl-HHDP-glucoside, rugosin A, and 1,2,3,6-tetra-O-galloyl-glucose have been reported with tyrosinase inhibitory activity. Additionally, molecular docking analysis was used to reveal the inhibition mechanism of these compounds toward tyrosinase.</p><p><strong>Conclusion: </strong>The finding of this study will be of great importance for the quality control of the two types of rose teas, and the revealed active ingredients will provide in-depth insights for the expansion of the rose tea industry.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"80-91"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141760317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated metabolomic and transcriptomic analysis reveals variation in the metabolites of Dendrobium officinale, Dendrobium huoshanense, Dendrobium nobile.","authors":"Li Chen, Shuna Duan, Jiahui Huang, Li Hu, Shuping Liu, Qiqian Lan, Gang Wei","doi":"10.1002/pca.3429","DOIUrl":"10.1002/pca.3429","url":null,"abstract":"<p><strong>Introduction: </strong>Dendrobium is a perennial herb of the genus Dendrobium in the orchid family. Generally, Dendrobium officinale (TP) and Dendrobium huoshanense (HS) are both considered to have the function of yin-nourishing, while Dendrobium nobile (JC) has better efficacy of heat-clearing. However, because of the wide variety of Dendrobium species, the classification and clinical application of Dendrobium are often confused clearly distinguished in different medicinal uses.</p><p><strong>Objective: </strong>In order to compare the differentially accumulated metabolites (DAMs) and differentially expressed genes (DEGs) of the three Dendrobium.</p><p><strong>Methods: </strong>We selected TP, HS, and JC cultivated on stone for metabolomic and transcriptomic analyses between 2 and 3 years.</p><p><strong>Results: </strong>The results showed that a total of 489 metabolites were obtained, including 72 were DAMs. The 72 DAMs were mainly enriched in metabolic pathways and biosynthesis of secondary metabolites. Transcriptome analysis results showed that 1,038 annotated DEGs were identified among the three Dendrobium species. The comprehensive analysis showed that the three Dendrobium differed in the distribution of the content of four major active components: flavonoids, amino acids, alkaloids, and sugars and alcohols, among which the DAMs and DEGs were mainly enriched in metabolic pathways and secondary metabolite biosynthesis.</p><p><strong>Conclusion: </strong>In this study, metabolomics and transcriptomics were utilized to compare the differences among the three species of Dendrobium, to provide theoretical references for future research and selection of different species of Dendrobium based on different medicinal uses, and to lay the foundation for further research on the biosynthesis of flavonoids in Dendrobium.</p>","PeriodicalId":20095,"journal":{"name":"Phytochemical Analysis","volume":" ","pages":"181-193"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141907365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}