Comprehensive feature‐based molecular networking and metabolomics approaches to reveal the differences components in Cinnamomum cassia and Cinnamomum verum. Issue 20 (1st September 2021)

• Record Type: Journal Article
• Authors: Wu, Xingdong; Long, Huali; Li, Feifei; Wu, Wenyong; Zhou, Jing; Liu, Chen; Hou, Jinjun; Wu, Wanying; Guo, Dean
• Is Part Of: Journal of separation science. Volume 44:Issue 20(2021)
• Page Start: 3810
• Page End: 3821
• Publication Date: 2021-09-01
• Subjects: alkaloids -- Cinnamomum -- feature‐based molecular networking -- metabolite profiling -- proanthocyanidins; Separation (Technology) -- Periodicals; Chromatographic analysis -- Periodicals; 543.089
• DOI: 10.1002/jssc.202100399
• Languages: English
• ISSNs: 1615-9306

Abstract

Abstract: Cinnamon was been a widely used plant in medicinal and spices for a long time and has spread all over the world. However, the differences in the components of the bark from Cinnamomum cassia and Cinnamomum verum, the two most common types of cinnamon, have not been thoroughly investigated. In the present experiment, ultra‐high‐performance liquid chromatography LTQ‐Orbitrap Velos Pro hybrid mass spectrometer‐based metabolomics coupled with chemometrics and feature‐based molecular networking were employed to dramatically distinguish and annotate Cinnamomum cassia Bark and Cinnamomum verum bark. As a consequence, principal component analysis, orthogonal projection to latent structures discriminates analysis, and heat map analysis demonstrated clear discrimination between the profiles of metabolites in cinnamon. Besides, as the known compounds, proanthocyanidins (cinnamtannin B1 and procyanidin B2) and alkaloids (norboldine, norisoboldine) with variable importance in the projection scores >6, and an unknown alkaloid (formula C24 H33 NO6 ) were selected as the best markers to discriminate cinnamon. Furthermore, large numbers of proanthocyanidins and alkaloids components were identified through feature‐based molecular networking for the first time. Our investigation provides new ideas for the discovery of quality markers and identification of unknown components in natural products.