Separating structural heterogeneities from stochastic variations in fluorescence resonance energy transfer distributions via photon distribution analysis.
We establish a probability distribution analysis (PDA) method for the analysis of fluorescence resonance energy transfer (FRET) signals to determine with high precision the originating value of a shot-noise-limited signal distribution. PDA theoretical distributions are calculated explicitly including crosstalk, stochastic variations, and background and represent the minimum width that a FRET distribution must have. In this way an unambiguous distinction is made between shot-noise distributions and distributions broadened by heterogeneities. This method simultaneously and effectively extracts highly resolved information from FRET distributions. The theoretical histograms match the exact profile of histograms generated from constant transfer efficiency experimental data with a chi2 near unity. The chi2 surface suggests an ultimate level of precision with FRET of < 1% of the Förster radius. Distributions of FRET signals in donor-acceptor-labeled DNA were unambiguously identified as being broader than shot-noise variations could explain. A model describing a Gaussian distribution of distances was tested with the PDA method and demonstrated 5 A inhomogeneities due to dye motions. The capability of this method to recover quantitative information from FRET distributions has potential applications for studying molecular conformations and dynamics. Potential sources for artifacts such as acceptor photobleaching, spectrally different observation volumes, and fluctuations of the Förster radius are ruled out.
Antonik
Matthew
M
Institut für Physikalische Chemie, Lehrstuhl für Molekulare Physikalische Chemie, Heinrich-Heine-Universität, Universitätsstrasse 1, Geb 26.32, 40225 Düsseldorf, Germany. mattew.antonik@uni-duesseldorf.de
Felekyan
Suren
S
Gaiduk
Alexander
A
Seidel
Claus A M
CA
D004247:DNA / Q000737:chemistry; D031541:Fluorescence Resonance Energy Transfer; D017785:Photons; D011336:Probability; D013269:Stochastic Processes
D004247:DNA