Department of Chemistry, University of Akron, Akron, OH 44325, USA.
Food Animal Health Research Program, Ohio Agriculture Research and Development Center, Department of Veterinary Preventive Medicine, The Ohio State University, Wooster, OH 44691, USA.
Methods. 2018 May 1;140-141:40-51. doi: 10.1016/j.ymeth.2018.02.002. Epub 2018 Feb 13.
Fluorescence cross-correlation spectroscopy (FCCS) is an advanced fluorescence technique that can quantify protein-protein interactions in vivo. Due to the dynamic, heterogeneous nature of the membrane, special considerations must be made to interpret FCCS data accurately. In this study, we describe a method to quantify the oligomerization of membrane proteins tagged with two commonly used fluorescent probes, mCherry (mCH) and enhanced green (eGFP) fluorescent proteins. A mathematical model is described that relates the relative cross-correlation value (f) to the degree of oligomerization. This treatment accounts for mismatch in the confocal volumes, combinatoric effects of using two fluorescent probes, and the presence of non-fluorescent probes. Using this model, we calculate a ladder of f values which can be used to determine the oligomer state of membrane proteins from live-cell experimental data. Additionally, a probabilistic mathematical simulation is described to resolve the affinity of different dimeric and oligomeric protein controls.
荧光相关光谱技术(FCCS)是一种先进的荧光技术,可定量测量体内蛋白质-蛋白质相互作用。由于膜的动态、异质性,必须特别考虑以准确解释 FCCS 数据。在这项研究中,我们描述了一种方法来量化用两种常用荧光探针 mCherry(mCH)和增强型绿色荧光蛋白(eGFP)标记的膜蛋白的寡聚化。描述了一种数学模型,该模型将相对相关值(f)与寡聚度联系起来。这种处理方法考虑到共聚焦体积的不匹配、使用两种荧光探针的组合效应以及非荧光探针的存在。使用该模型,我们计算了一系列 f 值,可以根据活细胞实验数据确定膜蛋白的寡聚状态。此外,还描述了一种概率数学模拟,以确定不同二聚体和寡聚体蛋白对照物的亲和力。