Rosmarinic acid (RA) is a caffeic acid derivative and one of the most abundant and bioactive constituents in Java tea (Orthosiphon stamineus), which has significant biological activities. However, relatively few studies have been conducted to describe this compound's metabolites in vivo. Therefore, an ultra-high-performance liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS/MS) analysis with a three-step data mining strategy was established for the metabolic profile of RA. Firstly, the exogenously sourced ions were filtered out by the MarkerView software and incorporated with Microsoft Office Excel software. Secondly, a novel modified mass detects filter strategy based on the predicted metabolites was developed for screening the target ions with narrow, well-defined mass detection ranges. Thirdly, the diagnostic product ions and neutral loss filtering strategy were applied for the rapid identification of the metabolites. Finally, a total of 16 metabolites were reasonably identified in urine, bile and feces, while metabolites were barely found in plasma. The metabolites of RA could also be distributed rapidly in liver and kidney. Glucuronidation, methylation and sulfation were the primary metabolic pathways of RA. The present findings might provide the theoretical basis for evaluating the biological activities of RA and its future application.
Keywords: Orthosiphon stamineus; UHPLC-QTOF-MS/MS; metabolic profile; rosmarinic acid; three-step data mining strategy.
© 2019 John Wiley & Sons, Ltd.