A Statistical Analysis of Fluorescence Correlation Data

Abstract

Fluorescence correlation spectroscopy (FCS) is a relatively recent technique in which the diffusion coefficient of fluorescently labeled molecules can be determined. The change in diffusion behavior when these molecules interact with others can also be used to study interactions in solution. A new statistical method is proposed to analyze FCS measurements that cannot be evaluated with a classical autocorrelation function, which is normally used to analyze FCS data. It applies to binding studies where one of the interacting particles has a much brighter fluorescence intensity with respect to the other, which causes high fluorescence bursts whenever these molecules are detected. This biases the autocorrelation function, making it in most cases impossible to use this function as a fitting equation. Here, a statistical approach is used to quantify the amount of fluorescence found in bursts, thereby enabling to perform binding studies in cases where the fluorescence per molecule of both interacting species differs greatly. The method is demonstrated on a system of known composition, making it a promising tool for future FCS measurements.