Development and application of mass spectrometric molecular networking for analyzing the ingredients of areca nut†

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2023-12-21 DOI:10.1039/D3MO00232B
Jialiang Zhao, Jiachen Shi, Xiaoying Chen, Yuanluo Lei, Tian Tian, Shuang Zhu, Chin-Ping Tan, Yuanfa Liu and Yong-Jiang Xu
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Abstract

Areca nut (Areca catechu L.) is commonly consumed as a chewing food in the Asian region. However, the investigations into the components of areca nut are limited. In this study, we have developed an approach that combines mass spectrometry with feature-based molecular network to explore the chemical characteristics of the areca nut. In comparison to the conventional method, this technique demonstrates a superior capability in annotating unknown compounds present in areca nut. We annotated a total of 52 compounds, including one potential previously unreported alkaloid, one carbohydrate, and one phenol and confirmed the presence of 7 of them by comparing with commercial standards. The validated method was used to evaluate chemical features of areca nut at different growth stages, annotating 25 compounds as potential biomarkers for distinguishing areca nut growth stages. Therefore, this approach offers a rapid and accurate method for the component analysis of areca nut.

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开发和应用质谱分子网络分析猕猴桃成分
在亚洲地区,人们通常将阿卡坚果(Areca catechu L.)作为咀嚼食品食用。然而,对其成分的研究却十分有限。在这项研究中,我们开发了一种将质谱法与基于特征的分子网络相结合的方法,以探索槟榔的化学特征。与传统方法相比,该技术在注释存在于果仁中的未知化合物方面表现出卓越的能力。我们共标注了 52 种化合物,包括一种以前未报道过的潜在生物碱、一种碳水化合物和一种酚,并通过与商业标准进行比较,确认了其中 6 种化合物的存在。该验证方法被用于评估不同生长阶段的山苍子的化学特征,注释出 25 种化合物作为区分山苍子生长阶段的潜在生物标志物。因此,该方法为分析山苍子的成分提供了一种快速、准确的方法。
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CiteScore
7.20
自引率
4.30%
发文量
567
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