Transcriptome analysis to reveal the mechanism of the effect of Echinops latifolius polysaccharide B on palmitate-induced insulin-resistant

Biomed Pharmacother. 2021 Nov;143:112203. doi: 10.1016/j.biopha.2021.112203. Epub 2021 Sep 24.


Hepatic insulin resistance is a crucial pathological process in type 2 diabetes mellitus (T2DM) associated with visceral adiposity and metabolic disorders. Echinops latifolius polysaccharide B (ETPB), a polysaccharide extracted from Echinops latifolius Tausch, increases insulin sensitivity in the high-fat diet-fed and STZ induced SD rat model and even prevented hepatic metabolic disorders. However, the mechanism by which ETPB improves carbohydrate and lipid metabolisms in the liver with insulin resistance remains largely unknown. In the present work, an lnsulin resistance cell model (IR-HepG2) was established. Glucose consumption, glycogen content, triglycerides (TG), and free fatty acids (FFAs) levels were detected. The result revealed that the intervention of ETPB significantly increased glucose consumption and glycogen synthesis and reduced FFAs and TG production in IR-HepG2 cells. Further, we also employed RNA-seq to identify differentially expressed miRNAs (DEMs) and mRNAs (DEGs) with a fold change of ≥ 1.5 and p-value of <0.05. Finally, we identified 1028, 682, 382, 1614, 519 and 825 DEGs, and 71, 113, 94, 68, 52 and 38 DEMs in different comparisons, respectively. Based on a short time-series expression miner (STEM) analysis, six profiles were chosen for further analysis. Seventeen insulin resistance-associated dynamic DEGs were identified during ETPB stimulation. Based on these dynamic DEGs, the related miRNAs were acquired from DEMs, and an integrated miRNA-mRNA regulatory network was subsequently constructed. Besides, some DEGs and DEMs were validated using qPCR. This study provides transcriptomic evidence of the molecular mechanism involved in HepG2 insulin resistance, leading to the discovery of miRNA-based target therapies for ETPB.

Keywords: ETPB; HepG2; Insulin resistance; MiRNAs; RNA sequencing.