Spatial distribution of differential metabolites in different parts of Curcuma phaeocaulis Val. by ultra-highperformance liquid chromatography-quadrupole orbitrap high-resolution mass spectrometry and desorption electrospray ionization mass spectrometry imaging
Abstract
Background:Roots and rhizomes of Curcuma phaeocaulis Val. are used as distinct traditional Chinese medicines with a reported blood-circulating and stasis-removing effect. This may be related to differences in the accumulation and distribution of active compounds.Purpose: This study investigates spatial variations in secondary metabolites across different parts of Curcuma phaeocaulis Val. and explores the underlying pharmacological basis. Methods: Ultra-high-performance liquid chromatography-quadruple orbitrap highresolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) coupled with desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was employed to analyze the spatial distribution of metabolites in different parts of Curcuma phaeocaulis Val. Multivariate statistical analysis was performed to identify differential metabolites. DESI-MSI visualization further characterized the spatial distribution. Network pharmacology was subsequently employed to predict the pharmacological mechanisms of key differential components. Results: UHPLC-Q-Orbitrap HRMS analysis identified 54 chemical compounds in different parts of Curcuma phaeocaulis Val., primarily sesquiterpenes and curcuminoids. Rhizomes displayed significantly higher levels of these compounds compared to roots. Multivariate statistical analysis using UHPLC-Q-Orbitrap HRMS and DESI-MSI identified 23 and 20 differentially abundant metabolites in roots and rhizomes, respectively, with 14 compounds common to both methods. DESI-MSI imaging localized β-elemene and curcumenol predominantly to the rhizome cortex. Network pharmacology suggests STAT3, PIK3CA, PIK3R1 and AKT1 as potential key targets for Curcuma phaeocaulis Val. in treating blood stasis.1 Abbreviations: UHPLC-Q
Please wait while we load your content...