Laboratory for Scientific Image Analysis (SCIAN-Lab) at the Anatomy and Developmental Biology Program, ICBM, Universidad de Chile, Santiago, Chile.
J Microsc. 2010 Sep 1;239(3):173-83. doi: 10.1111/j.1365-2818.2010.03369.x.
The quantification of colocalizing signals in multichannel fluorescence microscopy images depends on the reliable segmentation of corresponding regions of interest, on the selection of appropriate colocalization coefficients, and on a robust statistical criterion to discriminate true from random colocalization. Here, we introduce a confined displacement algorithm based on image correlation spectroscopy in combination with Manders colocalization coefficients M1(ROI) and M2(ROI) to quantify true and random colocalization of a given florescence pattern. We show that existing algorithms based on block scrambling exaggerate the randomization of fluorescent patterns with resulting inappropriately narrow probability density functions and false significance of true colocalization in terms of p values. We further confine our approach to subcellular compartments and show that true and random colocalization can be analysed for model dendrites and for GABA(B) receptor subunits GABA(B)R1/2 in cultured hippocampal neurons. Together, we demonstrate that the confined displacement algorithm detects true colocalization of specific fluorescence patterns down to subcellular levels.
多通道荧光显微镜图像中荧光信号的共定位定量分析依赖于对相应感兴趣区域的可靠分割，合适的共定位系数的选择，以及用于区分真实共定位和随机共定位的稳健统计标准。在此，我们引入了一种基于图像相关光谱学的约束位移算法，并结合 Manders 共定位系数 M1(ROI)和 M2(ROI)，用于量化给定荧光模式的真实和随机共定位。我们表明，现有的基于块混淆的算法夸大了荧光模式的随机化，导致概率密度函数不适当变窄，以及 p 值方面真实共定位的错误显著性。我们进一步将我们的方法限制在亚细胞隔室，并表明可以对模型树突和培养的海马神经元中的 GABA(B)受体亚基 GABA(B)R1/2 进行真实和随机共定位分析。总之，我们证明了约束位移算法可以检测到特定荧光模式的真实共定位，其分辨率达到亚细胞水平。
