Abstract
Fluorescence fluctuation methods have become invaluable research tools for characterizing the molecular-level physical and chemical properties of complex systems, such as molecular concentrations, dynamics, and the stoichiometry of molecular interactions. However, information recovery via curve fitting analysis of fluctuation data is complicated by limited resolution and challenges associated with identifying accurate fit models. We introduce a new approach to fluorescence fluctuation spectroscopy that couples multi-modal fluorescence measurements with multi-modal global curve fitting analysis. This approach yields dramatically enhanced resolution and fitting model discrimination capabilities in fluctuation measurements. The resolution enhancement allows the concentration of a secondary species to be accurately measured even when it constitutes only a few percent of the molecules within a sample mixture, an important new capability that will allow accurate measurements of molecular concentrations and interaction stoichiometry of minor sample species that can be functionally important but difficult to measure experimentally. We demonstrate this capability using τFCS, a new fluctuation method which uses simultaneous global analysis of fluorescence correlation spectroscopy and fluorescence lifetime data, and show that τFCS can accurately recover the concentrations, diffusion coefficients, lifetimes, and molecular brightness values for a two component mixture over a wide range of relative concentrations.
Highlights
Modern scientific studies increasingly demand accurate characterization of the spatial and temporal dynamics of identifiable molecules [1–3]
The primary goal of this work is to demonstrate how experimental resolution and model discrimination capabilities in Fluorescence fluctuation spectroscopy (FFS) can be dramatically enhanced by using multi-parameter fluorescence detection (MFD) and multimethod global analysis, here shown through the implementation of tFCS
We demonstrate the capability to resolve the molecular composition of a mixture of two identical molecular weight fluorescence dyes, Rhodamine 6G and Rhodamine B, for which standard fluorescence correlation spectroscopy (FCS) experiments would be unable to identify the presence of the two sample components (DR6G = 390 mm2s21; DRhB = 465 mm2s21) [10] or to accurately recover their concentrations and other physical properties since their diffusion coefficients are too close [10]
Summary
Modern scientific studies increasingly demand accurate characterization of the spatial and temporal dynamics of identifiable molecules [1–3]. When FFS data is analyzed successfully, impressive resolution of sample composition and dynamics is often achievable This includes the unique capabilities to measure dynamics over a wide range of time-scales, to accurately measure molecular concentrations, and to directly measure the stoichiometric composition of interacting molecular species. FCS measurements offer limited capability to discriminate between fitting models when knowledge of the sample composition or physical dynamics driving fluctuations is not available a priori, as is often the case for measurements within living cells or other complex systems. These types of limitations can leave detection of a large number of potentially important molecular phenomena and interactions outside current experimental capabilities. Global analysis [27–33], i.e. curve fitting using global parameters ‘linked’ across multiple data sets, greatly constrains the fitting parameter space that can fit all experimental data simultaneously, enhancing resolution, and improving model discrimination capabilities in curve fitting routines
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