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📄 原文题目
An Integrated Method for Profiling Lipid-Protein Interactions Using Multifunctional Lipid Probes
🔗 原文链接
💡 AI 核心解读
创新性整合光化学、点击化学和质谱技术,建立完整的脂质互作组分析流程;首次系统提供从细胞处理到蛋白质组学样本制备的标准化方案;通过多功能脂质探针实现特定脂质物种的蛋白质互作网络解析。
📝 英文原版摘要
Cellular lipids shape health and disease through specific protein interactions, yet lipid-protein networks remain poorly defined. Despite rapid advances in functional lipid probes, the field still lacks a practical, dedicated protocol for conducting lipid-protein interaction studies. We describe detailed methods for determining lipid interactomes from cells using multifunctionalized lipid derivatives. We provide protocols that detail 1) how to treat cells with lipid derivatives and perform photochemistry to obtain lipid-protein conjugates; 2) how to perform click chemistry with a fluorophore and observe lipid-protein conjugates by in-gel fluorescence; 3) how to perform click chemistry with azide beads and prepare lipid-protein conjugates for proteomic analysis. We provide context on important parameters for each step and include guidelines for controls, as well as suggestions for troubleshooting based on common problems encountered during the preparation of this protocol. This protocol enables mapping lipid interactomes across diverse biological systems. The entire workflow from cell treatment to complete proteomic sample preparation requires ~15 hours over four days, depending on the type of experimental readout (in-gel fluorescence or proteomics), and the usage of pause points. Practitioners are expected to be familiar with standard biochemical techniques, such as sterile sample handling and tissue culture and gel electrophoresis. Additional skills are needed for mass spectrometric analysis, and collaboration with a proteomics core facility is recommended. The described procedures uniquely enable the identification of the protein interactors (the interactome) of select lipid species, providing for a major shift in the characterization of the biological roles of lipids
in cellular systems.
- 作者:NotionNext
- 链接:https://tangly1024.com/article/2ec48bd6-1f96-8114-a51f-f9b63da18cfb
- 声明:本文采用 CC BY-NC-SA 4.0 许可协议,转载请注明出处。
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