Frequency Domain Multidimensional Fluorescence:  A Route to Model-Independent Fluorescence Decay Analysis

Abstract

A multivariate method for analyzing complex fluorescence decays without model assumptions is described. This method is applicable to the decays of mixtures of spectrally distinct fluorophores. The method does not require specific information concerning the component spectra or lifetimes, but such information can be used when it is available. The decay is analyzed as the complex quantum yield (a function of the steady-state intensity, modulation ratio, and phase angle) measured as a function of modulation frequency and, in most cases, emission wavelength. When the spectra of the mixture components are known, the frequency domain decays of the components can be calculated from complex quantum yield matrices measured at all or selected wavelengths. Matrices describing component photokinetics and relative concentrations are calculated from the frequency domain decays. When the component emission spectra are not known, complex quantum yield matrices can be factored into the emission spectra and frequency domain decays of the sample components via principal components analysis of the matrix. In this paper, the principles of frequency domain decay analysis are discussed. In particular, the variation of the analysis procedure with the amount of data acquired and the extent of the analyst's knowledge of the sample components are described. These procedural variations are illustrated by the analysis of simulated decays and the decays of mixtures of polynuclear aromatic hydrocarbons in isotropic and microheterogeneous solution.

Spectroscopic Investigations of Poly(Propyleneimine)Dendrimers Using the Solvatochromic Probe Phenol Blue and Comparisons to Poly(Amidoamine) Dendrimers

“…The lifetimes and fractional intensities were obtained from the phase and modulation data using the maximum entropy method (MEM). − Advantages of using MEM compared to traditional nonlinear least squares (NLLS) are documented and include the fact that MEM is self-modeling, does not require selection of an a priori model, and returns more consistent lifetime distributions. ,,− The three replicate phase and modulation data sets collected for each sample were analyzed both individually and as a combined file. The lifetime window consisted of 500 discrete, equally spaced cells from 0.01 to 10 ns.…”

Photokinetic Analysis of PRODAN and LAURDAN in Large Unilamellar Vesicles from Multivariate Frequency-Domain Fluorescence

“…Data in this format can be partitioned into sets of component spectral and decay responses using minimal photokinetic model assumptions by multivariate data analysis methods based on principal components analysis. [57][58][59] Moreover, nonheuristic, statistical methods for determining the number of components contributing to matrix formatted data (rank estimation) are available. 60,61 The Fourier transformed emission-decay matrices of the probes' emission in DMPC vesicles were measured as a function of temperature around the DMPC gel phase transition temperature.…”

“…After measuring decay profiles at multiple wavelengths, the data were arranged in the Fourier transformed emission-decay matrix (FT-EDM) format. Data in this format can be partitioned into sets of component spectral and decay responses using minimal photokinetic model assumptions by multivariate data analysis methods based on principal components analysis. − Moreover, nonheuristic, statistical methods for determining the number of components contributing to matrix formatted data (rank estimation) are available. , The Fourier transformed emission-decay matrices of the probes' emission in DMPC vesicles were measured as a function of temperature around the DMPC gel phase transition temperature. Analysis of the matrices revealed that both probes typically emit at least three spectral components, which vary in intensity as the membrane undergoes gel to liquid-crystalline phase transitions.…”

Numerical Correction of Detector Channel Cross-Talk Using Full-Spectrum Fluorescence Correlation Spectroscopy

“…Simultaneous fitting (GLOBALS) of model spectra to multiple data streams is not the only way to separate the components of overlapping spectra. As has been demonstrated in the case of time-and frequency-domain lifetime measurements, multichannel detection of a sample spectrum as a function of a second parameter coupled with multivariate data analysis can resolve substantially overlapped spectra 29,30 without a priori spectral models. The work presented in this report uses CCD detection of two-photon induced fluorescence spectrum fluctuations in combination with multivariate data analysis to resolve fluctuation data into fluorophore-specific signals in spite of significant spectral overlap.…”