Astragli Radix (AR) is one of the most popular traditional Chinese medicines with chemical constituents including flavonoids and saponins. As recently evidenced, some fungi or their fermentation liquid may have the potential to affect the bioactive constituents and different pharmacological effects of AR. Thus, the composition of fermented AR (FAR) produced by Paecilomyces cicadae (Miquel) Samson in liquid-state fermentation was investigated using a UHPLC-LTQ-Orbitrap mass spectrometer in both positive and negative ion modes. Firstly, the MSⁿ data sets were obtained based on a data-dependent acquisition method and a full scan–parent ions list–dynamic exclusion (FS-PIL-DE) strategy. Then, diagnostic product ions (DPIs) and neutral loss fragments (NLFs) were proposed for better constituent detection and structural characterization. Consequently, 107 constituents in total, particularly microconstituents in FAR and AR, were characterized and compared in parallel on the same LTQ–Orbitrap instrument. Our results indicated that AR fermentation with Paecilomyces significantly influenced the production of saponins and flavonoids, especially increasing the content of astragaloside IV. In conclusion, this research was not only the first to show changes in the chemical components of unfermented AR and FAR, but it also provides a foundation for further studies on the chemical interaction between microbiota and AR.

The screening of drug metabolites in biological matrixes and structural characterization based on product ion spectra is among the most important, but also the most challenging due to the significant interferences from endogenous species. Traditionally, metabolite detection is accomplished primarily on the basis of predicted molecular masses or fragmentation patterns of prototype drug metabolites using ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS). Although classical techniques are well-suited for achieving the partial characterization of prototype drug metabolites, there is a pressing need for a strategy to enable comprehensive drug metabolism depiction. Therefore, we present drug metabolite clusters (DMCs), different from, but complementary to, traditional approaches for mining the information regarding drugs and their metabolites on the basis of raw, processed, or identified tandem mass spectrometry (MS/MS) data. In this paper, we describe a DMC-based data-mining method for the metabolite identification of 5-hydroxy-6,7,3′,4′-tetramethoxyflavone (HTF), a typical hydroxylated-polymethoxyflavonoid (OH-PMF), which addressed the challenge of creating a thorough metabolic profile. Consequently, eight primary metabolism clusters, sixteen secondary metabolism clusters, and five tertiary metabolism clusters were proposed and 106 metabolites (19 potential metabolites included) were detected and identified positively and tentatively. These metabolites were presumed to generate through oxidation (mono-oxidation, di-oxidation), methylation, demethylation, methoxylation, glucuronidation, sulfation, ring cleavage, and their composite reactions. In conclusion, our study expounded drug metabolites in rats and provided a reference for further research on therapeutic material basis and the mechanism of drugs.