UHPLC-Q-Orbitrap结合DESI-MSI对姜黄根和根茎差异代谢物的空间分布及比较分析

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Jin Wang, Ying Zhu, Chuyue Wu, Qinwan Huang
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引用次数: 0

摘要

姜黄的根和根茎是不同的中药,治疗效果不同,可能与这些部位代谢物的积累和分布不同有关。目的:研究龙葵根、根茎代谢产物的差异及空间分布规律。方法:采用超高效液相色谱-四重轨道阱高分辨率质谱法(UHPLC-Q-Orbitrap HRMS)结合解吸电喷雾质谱法(DESI-MSI)对根和根茎进行代谢物分析。采用主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA)筛选差异代谢物。用热图显示不同代谢物的相对含量。此外,基于DESI-MSI分析了差异代谢物的空间分布。结果:采用UHPLC-Q-Orbitrap高效液相色谱法,从根和根茎中鉴定出49种主要化学成分。通过UHPLC-Q-Orbitrap HRMS联合PCA和OPLS-DA进行非靶向代谢组学分析,鉴定出24个差异标志物;此外,将DESI-MSI与PCA和OPLS-DA结合使用,选择了18个差异标记。根据DESI-MSI结果,姜黄素和倍半萜类物质,包括双去甲氧基姜黄素、去甲氧基姜黄素、呋喃二烯酮、呋喃二烯酮、呋喃二烯、β-榄香烯和莪术烯,在根茎中的含量高于根。这些差异化合物在根和根的表皮、韧皮部和木质部表现出空间分布上的差异。结论:利用UHPLC-Q-Orbitrap HRMS结合DESI-MSI进行代谢组学分析,发现龙骨根和根茎中代谢物的积累和空间分布存在差异,可能与次生代谢物的生物合成有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Distribution and Comparative Analysis of Differential Metabolites in Curcuma longa L. Roots and Rhizomes Using UHPLC-Q-Orbitrap HRMS Combined With DESI-MSI.

Introduction: The roots and rhizomes of Curcuma longa L. serve as distinct traditional Chinese medicines with varying therapeutic effects, likely attributed to differences in the accumulation and distribution of metabolites in these parts.

Objective: The study aims to investigate the differences and spatial distribution patterns of metabolites in C. longa L. roots and rhizomes.

Methods: Metabolite analysis of roots and rhizomes was conducted using ultra-high-performance liquid chromatography-quadruple orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) combined with desorption electrospray ionization mass spectrometry imaging (DESI-MSI). Using principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to screen for differential metabolites. The relative contents of differential metabolites were visualized using heat maps. Additionally, the spatial distribution of differential metabolites was analyzed based on DESI-MSI.

Results: A total of 49 main chemical components were identified in roots and rhizomes using UHPLC-Q-Orbitrap HRMS. Through nontargeted metabolomics analysis combining UHPLC-Q-Orbitrap HRMS with PCA and OPLS-DA, 24 differential markers were identified; Additionally, using DESI-MSI alongside PCA and OPLS-DA, 18 differential markers were selected. Based on the DESI-MSI results, curcuminoids and sesquiterpenoids, including bisdemethoxycurcumin, demethoxycurcumin, furanodienone, furanogermenone, furanodiene, β-elemene, and curzerene, were more abundant in the rhizomes compared to the roots. And these differential compounds exhibited spatial distribution differences in the epidermis, phloem, and xylem between the roots and rhizomes.

Conclusion: The metabolomics analysis using UHPLC-Q-Orbitrap HRMS combined with DESI-MSI suggest differences in the accumulation and spatial distribution of metabolites in C. longa L. roots and rhizomes, possibly related to the biosynthesis of secondary metabolites.

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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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