Automated suppression of sample-related artifacts in Fluorescence Correlation Spectroscopy

Abstract

Fluorescence Correlation Spectroscopy (FCS) in cells often suffers from artifacts caused by bright aggregates or vesicles, depletion of fluorophores or bleaching of a fluorescent background. The common practice of manually discarding distorted curves is time consuming and subjective. Here we demonstrate the feasibility of automated FCS data analysis with efficient rejection of corrupted parts of the signal. As test systems we use a solution of fluorescent molecules, contaminated with bright fluorescent beads, as well as cells expressing a fluorescent protein (ICA512-EGFP), which partitions into bright secretory granules. This approach improves the accuracy of FCS measurements in biological samples, extends its applicability to especially challenging systems and greatly simplifies and accelerates the data analysis.