An Integrated Strategy for Rapid Discovery and Identification of Quality Markers in Gardenia Fructus Using an Omics Discrimination-Grey Correlation-Biological Verification Method

Gardenia Fructus (GF), a traditional Chinese medicine of in Rubiaceae family, has the potential to clear heat and purge fire and has been widely used to treat multiple infection-related diseases. However, the quality markers (Q-Markers) of GF have not been revealed comprehensively. In this experiment, the transgenic zebrafish lines, and were used to evaluate two main kinds of traditional efficacies of GF, hepatoprotective and anti-inflammatory effects. All the GF samples from different production areas were tested their anti-liver injury and anti-inflammantory activities. High-performance liquid chromatography-quadrupole time-of-flight mass spectrometry method (HPLC-Q-TOF/MS) was employed for herbal metabonomic analysis of GF samples. Gray correlation analysis (GCA) was utilized to screen out the components closely associated with the activities. Finally, the zebrafish model was applied to verify the bioactivity of the crucial components to determine the Q-Markers of GF. The zebrafish models were established by inducing with hydrogen peroxide or copper sulfate and applied to quickly evaluate the hepatoprotective effect and inflammation of GF samples. 27 potentially active components for liver protection and 21 potentially active components with anti-inflammatory properties were identified by herbal metabolomic analysis based on HPLC-Q-TOF/MS. The GCA result showed that five of the 27 components were highly correlated with liver protection, 15 of the 21 components were highly correlated with anti-inflammatory activity. Among them, geniposide and crocin-1 were confirmed their bioactivities on zebrafish experiment to be responsible for the protective effects of GF against liver injury, and genipin-1-β-D-gentiobioside, quinic acid, gardenoside, d-glucuronic acid, l-malic acid, mannitol, rutin, and chlorogenic acid were confirmed to be responsible for the anti-inflammatory effects. Finally, according to the screening principles of Q-Markers, genipin-1-β-D-gentiobioside, geniposide, and gardenoside were preliminarily identified to be the Q-Markers of GF. This study established an effective research strategy of "Omics Discrimination-Grey Correlation-Biological Verification," which enabled the rapid identification of key pharmacological components of GF. These markers have provided a scientific basis for constructing a modern quality evaluation system for GF.