Distribution Characterization with Fluorescence Cumulant Analysis

Abstract

Fluorescence correlation spectroscopy (FCS) is a powerful tool for biophysical research, capable of monitoring concentrations and molecular interactions on a femtoliter scale. However, it is difficult in practice to resolve multiple molecular species using FCS unless there is a large difference in molecular weight. Several techniques have been developed to combat this problem, including photon counting histograms (PCH), fluorescence intensity distribution analysis (FIDA), and fluorescence cumulant analysis (FCA). These are capable of resolving multiple components on the basis of differences in molecular brightness, but have typically focused on studying samples with a small number of species. Fluorescence cumulant analysis can be extended to determine the parameters of brightness distributions containing many components, yielding a set of simple algebraic relations between the factorial cumulants of a measured fluorescence intensity series and the moments of the brightness distribution. Using PCH in conjunction with FCA, the best-fit distribution may be distinguished from several candidate models. We present simulations and experiments testing the applicability of this analysis. This technique may be useful in studies where the molecules of interest form a variety of multimers or aggregates.