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28 August 2014 Reduced temporal sampling effect on accuracy of time-domain fluorescence lifetime Förster resonance energy transfer
Travis Omer, Lingling Zhao, Xavier Intes, Juergen Hahn
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Abstract
Fluorescence lifetime imaging (FLIM) aims at quantifying the exponential decay rate of fluorophores to yield lifetime maps over the imaged sample. When combined with Förster resonance energy transfer (FRET), the technique can be used to indirectly sense interactions at the nanoscale such as protein–protein interactions, protein–DNA interactions, and protein conformational changes. In the case of FLIM-FRET, the fluorescence intensity decays are fitted to a biexponential model in order to estimate the lifetime and fractional amplitude coefficients of each component of the population of the donor fluorophore (quenched and nonquenched). Numerous time data points, also called temporal or time gates, are typically employed for accurately estimating the model parameters, leading to lengthy acquisition times and significant computational demands. This work investigates the effect of the number and location of time gates on model parameter estimation accuracy. A detailed model of a FLIM-FRET imaging system is used for the investigation, and the simulation outcomes are validated with in vitro and in vivo experimental data. In all cases investigated, it is found that 10 equally spaced time gates allow robust estimation of model-based parameters with accuracy similar to that of full temporal datasets (90 gates).
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2014/$25.00 © 2014 SPIE
Travis Omer, Lingling Zhao, Xavier Intes, and Juergen Hahn "Reduced temporal sampling effect on accuracy of time-domain fluorescence lifetime Förster resonance energy transfer," Journal of Biomedical Optics 19(8), 086023 (28 August 2014). https://doi.org/10.1117/1.JBO.19.8.086023
Published: 28 August 2014
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CITATIONS
Cited by 22 scholarly publications.
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KEYWORDS
Luminescence

Fluorescence resonance energy transfer

In vivo imaging

Data modeling

Picosecond phenomena

In vitro testing

Error analysis


CHORUS Article. This article was made freely available starting 28 August 2015

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