摘要
目的:探讨高脂饮食诱导胰岛素抵抗的机制,以及了解高脂饮食诱导胰岛素抵抗的脂肪细胞的表型变化.方法:雄性C57 BL/6 J小鼠,给予正常饮食和高脂饮食.从正常饮食或高脂饮食喂养2 周的小鼠中分离附睾脂肪组织.实时荧光定量 RT-PCR 检测 γ-干扰素(Interferon γ,IFN-γ)和toll样受体2(toll-like receptor 2,TLR2)mRNA的表达.流式细胞术来检测表达 TLR2 或 IFN-γ 的脂肪细胞的数量.苏木精-伊红染色分析胰腺组织.免疫组化分析脂肪组织中 TLR2 和 IFN-γ 的表达.FFA或Zymosan A处理3T3-L1 脂肪细胞,并通过实时荧光定量RT-PCR检测IFN-γ和TLR2 mRNA的表达.结果:对脂肪细胞中基因表达谱的分析表明,高脂肪摄入诱导了IFN-γ和TLR2 的表达提高.流式细胞术分析显示存在共表达TLR2 和IFN-γ的脂肪细胞(TLR2/IFN-γ脂肪细胞),与皮下脂肪组织相比,高脂肪摄入增加了内脏脂肪组织中TLR2/IFN-γ脂肪细胞的数量.游离脂肪酸通过 TLR2 信号增加3T3-L1 脂肪细胞中IFN-γ 的表达.结论:TLR2/IFN-γ 脂肪细胞可能通过诱导内脏脂肪组织IFN-γ的表达,参与高脂诱导的胰岛素抵抗的发生.
Abstract
Objective:To explore the mechanism of insulin resistance induced by high-fat diet,and to understand the phenotypic changes of adipocytes induced by high-fat diet.Methods:Male C57 BL/6 J mice were fed with normal diet or high-fat diet.Epididymal adipose tissue was isolated from mice fed with normal diet or high-fat diet for 2 weeks.The expression of interferon-γ(IFN-γ)and toll-like receptor 2(TLR2)mRNA was detected by real-time fluorescence quantitative RT-PCR.Flow cytometry was used to detect the number of adipocytes expressing TLR2 or IFN-γ.Pancreatic tissue was analyzed by hematoxylin-eosin stai-ning.The expression of TLR2 and IFN-γ in adipose tissue was analyzed by immunohistochemistry.3T3-L1 adipocytes were treated with FFA or Zymosan A,and the expression of IFN-γ and TLR2 mRNA was detected by real-time fluorescence quantitative RT-PCR.Results:Analysis of gene expression profiles in adipocytes showed that high-fat intake induced increased expression of IFN-γ and TLR2.Flow cytometry analysis showed that there were adipocytes co-expressing TLR2 and IFN-γ(TLR2/IFN-γ adipocytes).Compared with subcutaneous adipose tissue,high fat intake increased the number of TLR2/IFN-γ adipocytes in viscer-al adipose tissue.Free fatty acids increased the expression of IFN-γ in 3T3-L1 adipocytes through TLR2 sig-naling.Conclusion:TLR2/IFN-γ adipocytes may be involved in high-fat-induced insulin resistance by in-ducing IFN-γ expression in visceral adipose tissue.
基金项目
河北省医学科学研究重点课题(2018)(20180352)
维普
万方数据