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Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI
Published on: December 16, 2022
Tissue distribution of metabolites in Cordyceps cicadae determined by DESI-MSI analysis
Mayijie Cao1, Jie Wu1, Xiaoli Zhu1
1Key Laboratory of Southwestern Chinese Medicine Resources, School of Pharmacy, Chengdu University of Traditional Chinese Medicine, 1166 Liutai Avenue, Wenjiang District, Chengdu, Sichuan, China.
Abstract:
In this paper, we establish an in situ visualization analysis method to image the spatial distribution of metabolites in different parts (sclerotium, coremium) and different microregions of Cordyceps cicadae (C. cicadae) to achieve the in situ visual characterization of tissues for a variety of metabolites such as nucleosides, amino acids, polysaccharides, organic acids, fatty acids, and so on. The study included LC-MS chemical composition identification, preparation of C. cicadae tissue sections, DEDI-MSI analysis, DESI combined with Q-TOF/MS to obtain high-resolution imaging of mass-to-charge ratio and space, imaging of C. cicadae in positive-negative ion mode with a spatial resolution of 100 μm, and localizing and identifying its chemical compositions based on its precise mass. A total of 62 compounds were identified; nucleosides were mainly distributed in the coremium, L-threonine and DL-isoleucine, and other essential amino acids; peptides were mainly distributed in the sclerotium of C. cicadae; and the rest of the amino acids did not have a clear pattern; sugars and sugar alcohols were mainly distributed in the coremium of C. cicadae; organic acids and fatty acids were distributed in the nucleus of C. cicadae more than in the sclerotium, and the mass spectrometry imaging method is established in the research. The mass spectrometry imaging method established in this study is simple and fast and can visualize and analyse the spatial distribution of metabolites of C. cicadae, which is of great significance in characterizing the metabolic network of C. cicadae, and provides support for the quality evaluation of C. cicadae and the study of the temporal and spatial metabolic network of chemical compounds.
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