Revelation of processing-induced chemical alterations of ligustri lucidi fructus by integrating molecular networking, pseudo-targeted metabolomics and in-situ spatial imaging

Standardization of processing strategy is an optimizing approach to improve the yield of active chemical compounds thereby improving quality control (QC) and pharmaceutical effect. Ligustri Lucidi Fructus (LLF), the mature fruit of Ligustrum lucidum Ait. (Oleaceae), has been traditionally processed using different pharmaceutical adjuvants to nourish the liver and kidneys and to strengthen muscles and bones. Common processing forms include drying (LLF), steaming (SLLF), steaming with salt-solution (SLLFSS), steaming with rice-wine (SLLFRW), and steaming with rice-vinegar (SLLFRV). After processing, the five LLFs exhibit overlapping yet distinct pharmacological properties. Despite the extensive empirical uses, the chemical basis underlying the processing-dependent therapeutic effects remains unclear. Thus, an integrated “molecular networking-pseudo-targeted metabolomics-mass spectrometry imaging” strategy was applied to characterize metabolites in processed LLFs. A total of 233 compounds, including 89 iridoids, 26 flavonoids, 79 triterpenoids, and 10 phenylethanols were identified using high resolution mass spectroscopy (HRMS) combined with molecular networking (MN). Eighteen metabolites were screened as differential markers, whose spatial visualization and quantity analysis were provided by desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and targeted quantification, highlighting processing-induced spatial and compositional variations. Eleven QC markers were further identified with targeted quantification and receiver operating characteristic (ROC) curve validation. In conclusion, this study systematically characterized the material basis underlying all clinically used processing forms of LLF for the first time. The findings provide a scientific reference for clinical application of processed LLF and offer new insights into herbal medicine processing. • Established a strategy enabling multidimensional characterization and quality evaluation of processed LLFs. • Profiled 233 metabolites with MN-based clustering and structural categorization. • Identified 18 core differential metabolites through semi-quantification, and targeted quantification. • Visualized spatial distribution by DESI-MSI revealing processing-induced compositional and localization changes. • Screened 11 QC markers via ROC validation, providing a scientific basis for processing-based quality control.