结合逆流分离和 qNMR 的代谢组学策略用于何首乌加工的综合化学评估

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Trung Huy Ngo, Yoon-Jin Lee, Hyukjae Choi, Kyung-Sik Song, Kyu Joon Lee, Joo-Won Nam
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引用次数: 0

摘要

简介何首乌是传统医学中常用的生药和加工药。生何首乌通过加工程序制成加工何首乌;然而,目前缺乏确保加工完整性的标准化规程:目的:本研究旨在开发一种基于代谢组学方法的策略,用于全面分析和比较原生药材和加工药材的化学成分,并为原生药材加工标准化奠定基础:采用离心分离色谱法(CPC)对原生和加工永磁铁的甲醇提取物进行分馏,并根据摇瓶法计算出的分配系数优化两相溶剂系统,以产生富含一级代谢物(1°Ms)和二级代谢物(2°Ms)的馏分。通过一维、二维和选择性一维核磁共振实验、光谱拟合以及与参考标准的比较,对这些馏分进行了分析。通过定量 1H NMR(qHNMR)对所分析的化合物进行定量,以显示化学变化,这些变化与 H2452 细胞抗氧化效果的变化相关联:结果:开发出一种 CPC 方法,可有效分离 1°Ms 和 2°Ms 富集馏分。qHNMR 有效地定量分析了原生和加工永磁铁中的 4 种 2°Ms 和 21 种 1°Ms 物质,包括首次报道的加工永磁铁中的介丁烷-2,3-二醇。加工过程中永磁铁化学成分的变化与抗氧化活性的提高高度相关:结论:通过结合逆流分离和 qHNMR,开发出了一种方便且经济有效的策略,用于对未加工和加工过的永磁铁进行全面的化学分析。这种方法将有助于药材的标准化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Metabolomics Strategy Combining Countercurrent Separation and qNMR for the Comprehensive Chemical Evaluation of Polygoni Multiflori Radix Processing.

Introduction: Polygoni Multiflori Radix (PMR) is commonly used in traditional medicine as both raw and processed forms. Raw PMR was prepared into processed PMR via processing procedure; however, there is a lack of standardized protocols ensuring the completeness of processing.

Objective: This aims to develop a strategy based on a metabolomics approach for the comprehensive chemical profiling and comparison of raw and processed PMR and establish a basis for PMR processing standardization.

Materials and methods: Methanol extracts of raw and processed PMR were fractionated by centrifugal partition chromatography (CPC) with an optimized two-phase solvent system based on the partition coefficient calculated from the shake-flask method to produce primary (1°Ms)- and secondary metabolites (2°Ms)-enriched fractions. These fractions were profiled by 1D and 2D and selective 1D NMR experiments, spectral fitting, and comparison with reference standards. The profiled compounds were quantified via quantitative 1H NMR (qHNMR) to show the chemical changes, which were correlated with changes in antioxidant effects on H2452 cells.

Results: A CPC method was developed to efficiently separate 1°Ms- and 2°Ms-enriched fractions. This method achieved high purity of the major stilbene in PMR in a single run. qHNMR effectively quantified four 2°Ms and twenty-one 1°Ms in both raw and processed PMR, including meso-butane-2,3-diol, which was first reported from processed PMR. Changes in chemical composition of PMR because of processing are highly correlated to the increase of antioxidant activity.

Conclusion: A convenient and cost-effective strategy for the comprehensive chemical profiling of raw and processed PMR was developed by combining countercurrent separation and qHNMR. This approach will contribute to the standardization of medicinal herbal materials.

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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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