A systematic strategy integrating solid-phase extraction, full scan range splitting, mass defect filter and precursor ion list for comprehensive metabolite profiling of Danqi Tongmai tablet in rats.

In vivo metabolite profiling of herbal medicines remains a challenge due to the complex chemical composition and drastic interference from biological matrix. In this study, a systematic strategy was established for comprehensive metabolite profiling of Danqi Tongmai (DQTM) tablet, a combination of salvianolic acids and notoginsenosides, in rats after oral administration. This strategy was composed of six steps. Firstly, the rat plasma and tissue samples were collected at multiple time points to increase the representativeness of samples. Secondly, different sample preparation methods were systematically investigated including protein precipitation, liquid-liquid extraction and solid-phase extraction to obtain superior extraction efficiency for both salvianolic acids and notoginsenosides. Thirdly, the MS acquisition method was optimized by splitting the full scan range into two separate segments to improve the detection capability for minor components. Fourthly, an extended polygonal mass defect filter (EP-MDF) model was constructed to filter potential metabolites of salvianolic acids and notoginsenosides, and remove large amounts of interference ions. Fifthly, ion intensity-based time point-staggered precursor ion list (IITPS-PIL) was generated to trigger more targeted MS/MS acquisition for potential metabolites at the highest concentration. Finally, the absorbed prototypes and metabolites were comprehensively characterized by reference standards and MS/MS fragmentation. The proposed strategy significantly improved the detection ability for trace prototypes and metabolites in vivo. A total of 370 components, including 94 prototypes (38 confirmed with reference standards) and 276 metabolites, were tentatively characterized in rat plasma and tissue samples after oral administration of DQTM. Collectively, this paper provided an applicable reference for comprehensive metabolite profiling of herbal medicines in complex biological samples.