Paper
6 May 2015 Superiorities of time-correlated single-photon counting against standard fluorimetry in exploiting the potential of fluorochromized oligonucleotide probes for biomedical investigation
Marco Lamperti, Luca Nardo, Maria Bondani
Author Affiliations +
Abstract
Site-specific fluorescence-resonance-energy-transfer donor-acceptor dual-labelled oligonucleotide probes are widely used in state-of-art biotechnological applications. Such applications include their usage as primers in polymerase chain reaction. However, the steady-state fluorescence intensity signal emitted by these molecular tools strongly depends from the specificities of the probe conformation. For this reason, the information which can be reliably inferred by steady-state fluorimetry performed on such samples is forcedly confined to a semi-qualitative level. Namely, fluorescent emission is frequently used as ON/OFF indicator of the probe hybridization state, i.e. detection of fluorescence signals indicates either hybridization to or detachment from the template DNA of the probe. Nonetheless, a fully quantitative analysis of their fluorescence emission properties would disclose other exciting applications of dual-labelled probes in biosensing. Here we show how time-correlated single-photon counting can be applied to get rid of the technical limitations and interpretational ambiguities plaguing the intensity analysis, and to derive information on the template DNA reaching single-base.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marco Lamperti, Luca Nardo, and Maria Bondani "Superiorities of time-correlated single-photon counting against standard fluorimetry in exploiting the potential of fluorochromized oligonucleotide probes for biomedical investigation", Proc. SPIE 9504, Photon Counting Applications 2015, 95040L (6 May 2015); https://doi.org/10.1117/12.2179002
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KEYWORDS
Luminescence

Picosecond phenomena

Fluorescence resonance energy transfer

Annealing

Data modeling

Molecules

Solids

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