Department of Chemistry and Biochemistry, University of Texas at Arlington, Arlington, TX, USA.
Methods Mol Biol. 2020;2184:61-75. doi: 10.1007/978-1-0716-0802-9_5.
Macrophages play a critical role in innate immunity through Toll-like receptor (TLR) signaling. Lipopolysaccharides (LPS) are a ligand of microbial origin that can trigger cell signaling in macrophages through TLRs and production of pro-inflammatory cytokines. Statin, a hypercholesterolemia drug, on the contrary, can reduce inflammatory cytokine production, and inflammation at large. Discovery-based quantitative proteomics is a useful method for unraveling complex protein networks and inter-protein interactions. Here, we describe protocols for studying the inflammatory proteomics network in RAW 264.7 cells (a model murine macrophage cell line) with the singular or sequential treatment of LPS and statin. We provide detailed protocols, including a quantitative proteomic analysis by mass spectrometry data, a protein network analysis by bioinformatics, and a validation of target through biochemical methods (e.g., immunocytochemistry, immunoblotting, gene silencing, and real-time PCR).
巨噬细胞通过 Toll 样受体 (TLR) 信号在先天免疫中发挥关键作用。脂多糖 (LPS) 是一种微生物来源的配体,可通过 TLR 触发巨噬细胞的细胞信号转导,并产生促炎细胞因子。他汀类药物是一种降胆固醇药物,相反,它可以减少炎症细胞因子的产生,从而减轻炎症。基于发现的定量蛋白质组学是一种用于揭示复杂蛋白质网络和蛋白质间相互作用的有用方法。在这里,我们描述了使用 LPS 和他汀类药物单一或序贯处理 RAW 264.7 细胞(一种模型鼠巨噬细胞系)来研究炎症蛋白质组学网络的方案。我们提供了详细的方案,包括通过质谱数据分析进行定量蛋白质组学分析、通过生物信息学进行蛋白质网络分析以及通过生化方法(例如免疫细胞化学、免疫印迹、基因沉默和实时 PCR)验证靶标。