Investigation of the chemical profile and anti-inflammatory mechanisms of flavonoids from Artemisia vestita Wall. ex Besser via targeted metabolomics, zebrafish model, and network pharmacology

Artemisia vestita Wall. ex Besser is a wild compositae medical plant distributed in the western high-altitude area of China (Tian et al., 2018). It has been used as a folk medicine for the treatment of inflammatory diseases, such as encephalitis, mastitis, throat diseases, etc (Chen et al., 2021; Ding et al., 2019). Artemisia vestita Wall. ex Besser mainly contains flavonoids, sesquiterpenoids, and other components (Yang et al., 2015). Previously, we demonstrated the content of total flavonoids in Artemisia vestita Wall. ex Besser (TFA) was 276.62 mg/g (Chen et al., 2015). Yin et al. isolated and identified nine flavones from Artemisia vestita Wall. ex Besser, including pectolinarigenin, jaceosidin, cirsilineol, cirsimaritin, hispidulin, quercetin, 6-methoxytricin, acacetin, and apigenin (Yin et al., 2008). All of these compounds have been reported to have anti-inflammatory activity (Ai et al., 2021; Heimfarth et al., 2021; Kang et al., 2021; Li et al., 2016; Nageen et al., 2021; Park et al., 2020; Shin et al., 2017; Sun et al., 2018). However, the chemical profile of TFA has not been clarified. The anti-inflammatory active ingredients and mechanisms of TFA are still largely unknown.

Combined applications of LC-MS/MS and targeted metabolomics have been widely used in the analysis and identification of plant metabolites due to the advantages of high throughput, fast separation, high sensitivity, and wide coverage (Wang et al., 2019). Zebrafish has emerged to become an ideal spinal model organism for activity evaluation of compounds thanks to its embryonic transparency, small size, fast breeding, similar biology, and genome to humans (Patton et al., 2021; Zhang et al., 2022). Many publications have reported that the zebrafish inflammation models are induced by CuSO4, lipopolysaccharide, or tail cutting (Zhang et al., 2020). These models are easy to establish, and the inflammatory responses are visualized (Nguyen et al., 2020). Network pharmacology is a promising method to predict the active compounds and underlying mechanisms of traditional Chinese medicine (TCM) (Zhou et al., 2022). Nonetheless, due to the complexity of TCM, the results of network pharmacology require verification by pharmacology experiments (He et al., 2022).

In the present study, TFA was prepared by a semi-bionic method. The chemical profile of TFA was analyzed using a broad targeted metabolomics approach based on LC-MS/MS. The anti-inflammatory effects of TFA were evaluated on CuSO4-induced and tail cutting-induced zebrafish models. The anti-inflammatory active flavonoids and mechanisms of TFA were predicted by a network pharmacology method and verified via zebrafish and qRT-PCR assays.

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