脂肪变性
脂肪性肝炎
非酒精性脂肪肝
脂肪肝
内科学
过氧化物酶体增殖物激活受体
纤维化
内分泌学
非酒精性脂肪性肝炎
肝纤维化
化学
受体
医学
疾病
作者
Yichen Tong,Wentao Zhu,Tianzhi Wen,Zere Mukhamejanova,Fang Xu,Qi Xiang,Jiyan Pang
标识
DOI:10.1021/acs.jnatprod.2c00259
摘要
Nonalcoholic fatty liver disease (NAFLD) represents a class of disorders including hepatic steatosis, steatohepatitis, and liver fibrosis. Previous research suggested that xyloketal B (Xyl-B), a marine-derived natural product, could attenuate the NAFLD-related lipid accumulation. Herein, we investigated the protective mechanism of Xyl-B in a high-fat diet (HFD) mice fatty liver model by combining a quantitative proteomic approach with experimental methods. The results showed that the administration of Xyl-B (20 and 40 mg·kg–1·day–1, ip) ameliorated the hepatic steatosis in HFD mice. Proteomic profiling together with bioinformatics analysis highlighted the upregulation of a cluster of peroxisome proliferator-activated receptor-α (PPARα) downstream enzymes mainly related to fatty acid oxidation (FAO) as key changes after the treatment. These changes were subsequently confirmed by bioassays. Moreover, further results showed that the expression levels of PPARα and PPARγ coactivator-1α (PGC1α) were increased after the treatment. The related mode-of-action was confirmed by PPARα inhibition. Furthermore, we evaluated the PPARα-mediated anti-inflammatory and antifibrosis effect of Xyl-B in methionine-choline-deficient (MCD) mice hepatitis and liver fibrosis models. According to the results, the histological features were improved, and the levels of inflammatory factors, adhesion molecules, as well as fibrosis markers were decreased after the treatment. Collectively, these results indicated that Xyl-B ameliorated different phases of NAFLD through activation of the PPARα/PGC1α signaling pathway. Our findings revealed the possible metabolism-regulating mechanism of Xyl-B, broadened the application of xyloketal family compounds, and may provide a new strategy to curb the development of NAFLD.
科研通智能强力驱动
Strongly Powered by AbleSci AI