A systematic data acquisition and mining strategy for chemical profiling of Aster tataricus rhizoma (Ziwan) by UHPLC-Q-TOF-MS and the corresponding anti-depressive activity screening.

In this study, a systematic data acquisition and mining strategy aimed at the traditional Chinese medicine (TCM) complex system based on ultra high-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS) was reported. The workflow of this strategy is as follows: First, the high resolution mass data are acquired by both data-dependent acquisition mode (DDA) and data-independent acquisition mode (DIA). Then a global data mining that combined targeted and non-targeted compound finding is applied to analyze mass spectral data. Furthermore, some assistant tools, such as key product ions (KPIs), are employed for compound hunting and identification. The TCM Ziwan (ZW, Aster tataricus rhizoma) was used to illustrate this strategy for the first time. In this research, total 131 compounds including organic acids, peptides, terpenes, steroids, flavonoids, coumarins, anthraquinones and aldehydes were identified or tentatively characterized in ZW based on accurate mass measurements within ±5 ppm error, and 50 of them were unambiguously confirmed by comparing standard compounds. Afterwards, based on the traditional Chinese medical theory and the key determinants of firing patterns of ventral tegmental area (VTA) dopamine (DA) neurons in the development of depression, the confirmed compounds were subsequently evaluated the pharmacological effect of activity of VTA DA neurons and anti-depressive efficacy. This research provided not only a chemical profiling for further in vivo study of ZW, but also an efficient data acquisition and mining strategy to profile the chemical constituents and find new bioactive substances for other TCM complex system.