RESUMEN
Colloidal quantum dots (QDs) are now commercially available in a biofunctionalized form, and Förster resonance energy transfer (FRET) between bioconjugated dots and fluorophores within the visible range has been observed. We are particularly interested in the far-red region, as from a biological perspective there are benefits in pushing to approximately 700 nm to minimize optical absorption (ABS) within tissue and to avoid cell autofluorescence. We report on FRET between streptavidin- (STV-) conjugated CdTe quantum dots, Qdot705-STV, with biotinylated DY731-Bio fluorophores in a donor-acceptor assay. We also highlight the changes in DY731-Bio absorptivity during the streptavidin-biotin binding process which can be attributed to the structural reorientation. For fluorescence beyond 700 nm, different alloy compositions are required for the QD core and these changes directly affect the fluorescence decay dynamics producing a marked biexponential decay with a long-lifetime component in excess of 100 nanoseconds. We compare the influence of the two QD relaxation routes upon FRET dynamics in the presence of DY731-Bio.
RESUMEN
A study of the practicality a simple technique for obtaining time-domain information that uses continuous wave detection of fluorescence is presented. We show that this technique has potential for use in assays for which a change in the lifetime of an indicator occurs in reaction to an analyte, in fluorescence resonance energy transfer, for example, and could be particularly important when one is carrying out such measurements in the scaled-down environment of a lab on a chip (biochip). A rate-equation model is presented that allows an objective analysis to be made of the relative importance of the key measurement parameters: optical saturation of the fluorophore and period of the excitation pulse. An experimental demonstration of the technique that uses a cuvette-based analysis of a carbocyanine dye and for which the excitation source is a 650 nm wavelength, self-pulsing AlGaInP laser diode is compared with the model.