Colocalization analysis is a powerful tool in confocal and deconvolution microscopy for the demonstration of spatial and temporal overlap in the distribution patterns of fluorescent probes. A number of commercial software packages contain colocalization algorithms and a number of techniques have been introduced to address specific applications. Many of the references listed below are review articles that thoroughly discuss a wide range of parameters for colocalization analysis and should be useful as a starting point for gathering information on this subject.
Quantitative colocalization analysis of confocal fluorescence microscopy images. Current Protocols in Cell Biology 4.19.1-4.19.16 (2008). The authors present a comprehensive review of colocalization analysis in biological applications. Discussed are a brief introduction to the technique and a step-by-step procedure for the analysis, including specimen preparation, microscope configuration, and the algorithms used to generate and analyze scatterplots.
A guided tour into subcellular colocalization analysis in light microscopy. Journal of Microscopy 224: 213-232 (2006). This review assesses the most popular colocalization analysis methods and introduces the basic optical concepts important for image acquisition and subsequent analysis. In addition, practical tips for image capture and treatment prior to analysis are suggested, as well as several example applications. The authors also introduce a new toolbox, named JACoP, which integrates into ImageJ for colocalization analysis.
A guide to accurate fluorescence microscopy colocalization measurements. Biophysical Journal 91: 4611-4622 (2006). A review of the application of image cross-correlation spectroscopy (ICCS), a technique that analyzes spatial intensity fluctuations in images gathered from two separate channels, to colocalization measurements in fluorescence microscopy. The theory behind ICCS is described and several examples are presented using dual-labeled biological specimens.
Multicolour analysis and local image correlation in confocal microscopy. Journal of Microscopy 185: 21-36 (1997). This research report describes colocalization analysis in thick specimens using optical sections obtained with laser scanning confocal microscopy. Included is a discussion of microscope configuration parameters, implementation of image processing algorithms, scatter plot analysis, and strategies for detection of colocalization. Numerous examples are presented.
Colocalization of fluorescent markers in confocal microscope images of plant cells. Nature Protocols 3: 619-628 (2008). An excellent protocol paper that describes the steps necessary to perform quantitative statistical colocalization on two-color confocal images using plant cells as an example. Included is a detailed step-by-step procedure, as well as a new software tool designed to calculate the Pearson and Spearman correlation coefficients.
Image acquisition for colocalization using optical microscopy. American Journal of Physiology: Cell Physiology 294: C1119-C1122 (2008). In this brief commentary, the authors highlight important factors in the acquisition of fluorescence images used to demonstrate colocalization. Also discussed is the maximum amount of information that should be included in a manuscript so that a reader can interpret both the fluorescent images and any observed colocalization.
Quantitative colocalization analysis of multicolor confocal immunofluorescence microscopy images: pushing pixels to explore biological phenomena. Acta Histochemica et Cytochemica 40: 101-111 (2007). An excellent review of quantitative colocalization analysis applied to examine antigen targets of interest in immunofluorescence images obtained using confocal microscopy. Discussed are the theoretical basis of colocalization analysis, limitations to the technique, and proper application with biological samples of interest.
Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophysical Journal 86: 3993-4003 (2004). This research report introduces a novel statistical approach that quantifies the amount of colocalization of two fluorescent-labeled proteins in an image automatically, removing the bias of visual interpretation. The analysis is accomplished by estimating simultaneously the maximum threshold of intensity for each color below which pixels do not show any statistical correlation.
An automated method to quantify and visualize colocalized fluorescent signals. Journal of Neuroscience Methods 146: 42-49 (2005). The authors describe a unique colocalization analysis method that combines quantification and imaging of colocalization using an algorithm based on edge detection combined with calculation of signal intensity deviation. The technique is demonstrated on both simulated images and experimental data.
Colocalization analysis yields superior results after image restoration. Microscopy Research and Technique 64: 103-112 (2004). A review of the application of colocalization analysis to images that have been restored using filtration techniques or deconvolution algorithms. Included is a review of colocalization principles, a discussion of background artifacts, and choosing a thresholding method. Several examples comparing raw data to images that have been subjected to a median filter and deconvolution are presented.