Phytochemical analysis of different Callicarpa species based on integrating metabolomics and chemometrics.

IF 3 3区生物学 Q2 BIOCHEMICAL RESEARCH METHODS Phytochemical Analysis Pub Date : 2024-09-23 DOI:10.1002/pca.3451

Xiaoxiao Zhang, Qingrui Zhang, Charity Ngina, Peng Lei, Xiaoge Li, Qibao Jiang, Miaomiao Jiang

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Abstract

Introduction: Traditionally, Callicarpa species have been utilized their anti-inflammatory and hemostatic properties. Prominently featured species in the 2020 Edition of the Chinese Pharmacopoeia were Callicarpa nudiflora (CN), Callicarpa macrophylla (CM), Callicarpa formosana (CF), and Callicarpa kwangtungensis (CK), which were formulated into several medicinal preparations. Extensive applications led to the significant depletion of CN's wild resources. The management of germplasm resources was significantly disordered. Adulteration issues were also prevalent.

Objective: It is imperative that the study aims to identify alternative sources for CN and other pharmacopeial varieties and develop methods to distinguish different Callicarpa species.

Results: Data were acquired using three mass spectrometry modes: Data Dependent Analysis (DDA), Data-Independent Analysis (DIA), and full mass spectrometry (MS). The DDA mode identified or inferred information on 54 compounds. The Full MS mode identified or inferred 74 compounds, including 20 that were previously unreported in Callicarpa. These compounds were confirmed using standards. The DIA mode did not facilitate identification due to missing precursor ion data. With metabolomics, 19 differential compounds were identified or inferred. Luteolin, chrysoeriol, and quercetin were selected as potential markers, integrating the 10 active compounds from network pharmacology.

Conclusion: Based on the relative abundance of these markers, it was proposed that Callicarpa giraldii Hesse ex Rehd. var. (CGHRV) and CM could serve as alternative resource species to CN, while CGHRV and Callicarpa giraldii Hesse ex Rehd. (CGHR) could substitute the pharmacopeial CM. Callicarpa longissimi (CLG) was suggested as an alternative to CK, while Callicarpa cathayana (CC) and Callicarpa rubella (CRL) could replace CF. Furthermore, the absence of certain compounds in CK presented a novel opportunity for the differentiation of various Callicarpa species.

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基于代谢组学和化学计量学的不同 Callicarpa 品种的植物化学分析。

简介：传统上，胼胝属植物具有消炎和止血的功效。在 2020 年版《中国药典》中，裸花胼胝属（CN）、大胼胝属（CM）、胼胝属（CF）和光东胼胝属（CK）是主要的特色物种，被配制成多种药剂。广泛的应用导致中国的野生资源严重枯竭。种质资源管理严重混乱。掺假问题也很普遍：当务之急是确定氯化萘和其他药典品种的替代来源，并开发出区分不同马钱子品种的方法：使用三种质谱模式获取数据：结果：采用三种质谱模式获取数据：数据依赖分析（DDA）、数据独立分析（DIA）和全质谱（MS）。DDA 模式识别或推断出 54 种化合物的信息。全质谱模式鉴定或推断出 74 种化合物，包括 20 种以前未在 Callicarpa 中报道过的化合物。这些化合物已通过标准进行了确认。由于前体离子数据缺失，DIA 模式无法帮助鉴定。通过代谢组学，鉴定或推断出 19 种差异化合物。结合网络药理学中的 10 种活性化合物，选择了木犀草素、红景天醇和槲皮素作为潜在的标记物：根据这些标记物的相对丰度，建议长叶女贞（Callicarpa giraldii Hesse ex Rehd.有研究建议，Callicarpa longissimi（CLG）可替代 CK，而 Callicarpa cathayana（CC）和 Callicarpa rubella（CRL）可替代 CF。此外，CK 中某些化合物的缺失为区分不同的 Callicarpa 种类提供了新的机会。

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来源期刊

Phytochemical Analysis 生物-分析化学

CiteScore

6.00

自引率

6.10%

发文量

审稿时长

1.7 months

期刊介绍： Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.