利用超高效液相色谱-Q-Orbitrap-HRMS系统定性分析胶浆(Pistacia lentiscus L.)提取物中的萜烯类化合物及其碎片。

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Phytochemical Analysis Pub Date : 2024-07-01 Epub Date: 2024-03-18 DOI:10.1002/pca.3342
Gulimire Kahaer, Rahima Abdulla, Tao Wu, Haji Akber Aisa
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引用次数: 0

摘要

简介胶泥是一种由Pistacia lentiscus L.(天南星科)产生的天然树脂。这种树脂的有益特性归功于其三萜类和挥发性化合物:本研究旨在筛选和表征胶浆乙酸乙酯提取物(M-Ex)中的萜烯类化合物:方法:开发了一种超高效液相色谱-四极杆 Orbitrap 高分辨率质谱(UHPLC-Q-Orbitrap-HRMS)方法,用于定性分析 M-Ex 中的萜烯类化合物。我们利用内部分离的化合物作为参比物质(Rs),包括具有 α-蒎烷结构的单萜烯(A)、含有 tirucallane 骨架的四环三萜(B)以及属于 olean、moronic、amyrone 和 lupane 类型的五环三萜(C)。根据上述化合物的质谱特征以及同分异构化合物中特征诊断碎片离子(DFIs)的差异,在 M-Ex 中对萜烯化合物进行了进一步鉴定:结果:在包括单萜烯、四环和五环三萜在内的 70 种化合物中,有 20 种通过 Rs、保留时间(RT)和 DFIs 得到了准确测定。根据上述 20 种化合物的裂解模式总结,并参考所报道的文献,又有 50 种化合物被初步鉴定出来。根据我们的发现,首次在胶泥中鉴定出六种 A-seco-tirucallane 类型的萜酸和一种单萜烯二聚体:我们的研究不仅为快速鉴定和筛选胶泥中的萜烯化合物奠定了基础,还为鉴定其他类型树脂中的此类化合物提供了补充依据。
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Systematic qualitative analysis of terpenes in mastic (Pistacia lentiscus L.) extract and their fragmentations by UHPLC-Q-Orbitrap-HRMS.

Introduction: Mastic is a natural resin produced by Pistacia lentiscus L. (Anacardiaceae). The beneficial properties of this resin are attributed to its triterpenes and volatile compounds.

Objective: This study was conducted to screen and characterize the terpenes in mastic ethyl acetate extract (M-Ex).

Methods: An ultrahigh-performance liquid chromatography coupled to quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS) method was developed for the qualitative analysis of terpenes in M-Ex. We utilized in-house-isolated compounds as reference substance (Rs), including monoterpenes (A) with α-pinane structures, tetracyclic triterpene (B) containing tirucallane skeletons, and pentacyclic triterpene (C) belonging to olean, moronic, amyrone, and lupane types. Based on the mass spectrometric characteristics of the above compounds, and the difference in characteristic diagnostic fragment ions (DFIs) in isomeric compounds, the terpene compounds were further identified in M-Ex.

Results: Out of a total of 70 compounds, including monoterpenes and tetra-, and pentacyclic triterpenes, 20 were accurately determined by Rs, retention time (RT), and DFIs. Based on the cleavage patterns summarized from the above 20 compounds and with reference to the reported literature, another 50 compounds were putatively identified. Based on our discovery, six terpenic acids with A-seco-tirucallane types and one monoterpene dimer were identified for the first time in mastic.

Conclusion: Our research serves not only as a foundation for the rapid identification and screening of terpene compounds in mastic but also as a supplementary basis for the identification of such compounds in other types of resins.

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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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