HRPIF data mining based on data-dependent/independent acquisition for Rhei Radix et Rhizoma metabolite screening in rats

In traditional Chinese medicine (TCM), components with identical nuclei often share structural similarity, indicating the possibility of similar second-level mass spectrometry (MS/MS) fragments. High-resolution product-ion filter (HRPIF) technique can be utilized to identify metabolites, with similar fragments, in vivo. In principle, this technique applies to TCM; however, its application has been restricted due to the limitations of traditional MS/MS data acquisition. Therefore, a novel analysis strategy, based on data-dependent acquisition (DDA) and data-independent acquisition (DIA) datasets, has been developed for the determination of template product ions and efficient non-targeted identification of TCM-related components in vivo by HRPIF and background subtraction (BS). This DDA-DIA combination strategy, taking Rhei Radix et Rhizoma as a test case, identified 71 anthraquinone prototype components in vitro (36 of which were discovered for the first time), and 45 related components in vivo, confirming glucuronidation and sulfation as the main reactions. The developed strategy could rapidly identify TCM-related components in vivo with high sensitivity, indicating the immense importance of this novel HRPIF data mining technology in TCM analysis.