Image correlation spectroscopy (ICS) has been widely used to quantify spatiotemporal distributions of fluorescently labelled cell membrane proteins and receptors. When the membrane proteins are randomly distributed, ICS may be used to estimate protein densities, provided the proteins behave as point-like objects. At high protein area fraction, however, even randomly placed proteins cannot obey Poisson statistics, because of excluded area. The difficulty can arise if the protein effective area is quite large, or if proteins form large complexes or aggregate into clusters. In these cases, there is a need to determine the correct form of the intensity correlation function for hard disks in two dimensions, including the excluded area effects. We present an approximate but highly accurate algorithm for the computation of this correlation function. The correlation function was verified using test images of randomly distributed hard disks of uniform intensity convolved with the microscope point spread function. This algorithm can be readily modified to compute exact intensity correlation functions for any probe geometry, interaction potential, and fluorophore distribution; we show how to apply it to describe a random distribution of large proteins labeled with a single fluorophore.
ICS Hard disk Excluded area Receptor clusters Fluorescence microscopy
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K.S. was supported in part by the Program in Interdisciplinary Biological and Biomedical Sciences funded by the University of New Mexico and by Award Number T32EB009414 from the National Institute of Biomedical Imaging and Bioengineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Biomedical Imaging and Bioengineering or the National Institutes of Health.
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