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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Development and application of mass spectrometric molecular networking for analyzing the ingredients of areca nut†
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.
Molecular omicsBiochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
5.40
自引率
3.40%
发文量
91
期刊介绍:
Molecular Omics publishes high-quality research from across the -omics sciences.
Topics include, but are not limited to:
-omics studies to gain mechanistic insight into biological processes – for example, determining the mode of action of a drug or the basis of a particular phenotype, such as drought tolerance
-omics studies for clinical applications with validation, such as finding biomarkers for diagnostics or potential new drug targets
-omics studies looking at the sub-cellular make-up of cells – for example, the subcellular localisation of certain proteins or post-translational modifications or new imaging techniques
-studies presenting new methods and tools to support omics studies, including new spectroscopic/chromatographic techniques, chip-based/array technologies and new classification/data analysis techniques. New methods should be proven and demonstrate an advance in the field.
Molecular Omics only accepts articles of high importance and interest that provide significant new insight into important chemical or biological problems. This could be fundamental research that significantly increases understanding or research that demonstrates clear functional benefits.
Papers reporting new results that could be routinely predicted, do not show a significant improvement over known research, or are of interest only to the specialist in the area are not suitable for publication in Molecular Omics.