Integrated LC-MS and Network Pharmacology Reveal Metabolic Profile and Quantitative Analysis of Active Components in Coptidis Rhizoma-Aucklandiae Radix Herb Pair Between Healthy and Diarrheal Mice.

IF 2.6 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Phytochemical Analysis Pub Date : 2025-10-01 Epub Date: 2025-07-30 DOI:10.1002/pca.70019
Lujia Yang, Muyao Li, Xianglan Deng, Fang Deng, Chuanyang Zhang
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引用次数: 0

Abstract

Introduction: Antibiotic-associated diarrhea (AAD) is a common side effect after the use of antibiotics, characterized by symptoms like diarrhea and abdominal pain. However, the active components and in vivo metabolism of the Coptidis Rhizoma-Aucklandiae Radix herb pair (CR-AR) in the treatment of AAD remain unclear.

Objective: This study aimed to (1) investigate the prototype components, metabolites, and potential metabolic pathways of CR-AR in AAD mice and (2) compare the concentration of six active components between healthy and AAD mice.

Materials and methods: AAD model mice received oral administration of the CR-AR extract. UPLC-Q-Exactive-Orbitrap-HRMS was used to analyze the prototype components and metabolites in serum, feces, and intestines of AAD mice. A prototype components-targets-pathways-AAD network was developed using network pharmacology to identify active components and effective targets of CR-AR in treating AAD, based on prototypes detected in serum, fecal, and intestinal samples. Additionally, a comparative analysis of the concentration of six active components was conducted between healthy and AAD mice using UPLC-QqQ-MS.

Results: A total of 45 components were identified in the extract of CR-AR. Among them, 16 prototype compounds and 47 metabolites were identified, and potential metabolic pathways (including hydroxylation, demethylation, reduction, hydrolysis, hydrogenation, and glucuronidation) were proposed. Based on the 16 prototype components, six potentially active components (berberine, jatrorrhizine, palmatine, columbamine, epiberberine, and dehydrocostus lactone) were screened from the prototype components-targets-pathways-AAD disease network. Targeted quantitative analysis showed that alkaloid-based active components were significantly more concentrated in the intestines of AAD mice than in healthy mice after 6 h (p < 0.05).

结合LC-MS和网络药理学揭示健康和腹泻小鼠黄连-木香对有效成分的代谢特征和定量分析。
抗生素相关性腹泻(Antibiotic-associated diarrhea, AAD)是抗生素使用后常见的副作用,以腹泻、腹痛等症状为特征。然而,黄连-木香对(CR-AR)治疗AAD的活性成分和体内代谢机制尚不清楚。目的:本研究旨在(1)研究AAD小鼠中CR-AR的原型成分、代谢物和潜在代谢途径;(2)比较健康小鼠和AAD小鼠中6种活性成分的浓度。材料和方法:AAD模型小鼠口服CR-AR提取物。采用UPLC-Q-Exactive-Orbitrap-HRMS分析AAD小鼠血清、粪便和肠道中的原型成分和代谢物。基于在血清、粪便和肠道样本中检测到的原型,利用网络药理学建立了原型成分-靶点-途径-AAD网络,以鉴定CR-AR治疗AAD的活性成分和有效靶点。此外,采用uplc - qq - ms对健康小鼠和AAD小鼠中6种有效成分的浓度进行了比较分析。结果:提取物中共鉴定出45种成分。其中鉴定出16种原型化合物和47种代谢物,并提出了潜在的代谢途径(包括羟基化、去甲基化、还原、水解、加氢和葡萄糖醛酸化)。基于16种原型成分,从原型成分-靶点-途径- aad疾病网络中筛选出6种潜在活性成分(小檗碱、麻草酸根碱、棕榈碱、columbamine、小檗碱和脱氢木香内酯)。有针对性的定量分析显示,6 h后,生物碱类活性成分在AAD小鼠肠道中的浓度明显高于健康小鼠(p
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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
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.
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