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ABSTRACT
Biomolecular interactions are fundamental to the vast majority of cellular processes, and identification of the major interacting components is usually the first step toward an understanding of the mechanisms that govern various cell functions. Thus, statistical image analyses that can be performed on fluorescence microscopy images of fixed or live cells have been routinely applied for biophysical and cell biological studies. These approaches measure the fraction of interacting particles by analyzing dual color fluorescence images for cotocalized pixels. Colocalization algorithms have proven to be effective, although the dynamic range and accuracy of these measurements has never been well established. Spatial image cross-correlation spectroscopy (ICCS), which cross-correlates spatial intensity fluctuations recorded in images from two detection channels simultaneously, has also recently been shown to be an effective measure of colocalization as well. Through simulations, imaging of fluorescent antibodies adsorbed on glass and cell measurements, we show that ICCS performs much better than standard colocalization algorithms at moderate to high densities of particles, which are often encountered in cellular systems. Furthermore, it was found that the density ratio between the two labeled species of interest plays a major role in the accuracy of the colocalization analysis. By applying a direct and systematic comparison between the standard, fluorescence microscopy colocalization algorithm and spatial ICCS, we show regimes where each approach is applicable, and more importantly, where they fail to yield accurate results.
INTRODUCTION
From mitosis to apoptosis, almost all cellular processes are regulated through complex interactions between macromolecules such as proteins, lipids, DNA, RNA, and other types of biomolecules. Identification of the major interacting components is an essential step toward understanding the underlying mechanisms that regulate cellular functions. To this end, fluorescence microscopy has proven to be an invaluable tool for in vitro and in vivo studies of molecular interactions, in part due to the advances in fluorescence labeling techniques and commercialization of the laser scanning microscope (LSM). To date, most approaches for measuring interacting cellular constituents using fluorescence microscopy require the analysis of dual color images for the presence of colocalized signal, that is, overlapping signals within images collected on separate detection channels. The measurement of a high degree of colocalization indicates close proximity of the two labeled species, and therefore suggests a nonrandom interaction...