1 September 2006 Time-domain fluorescent plate reader for cell based protein-protein interaction and protein conformation assays
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J. of Biomedical Optics, 11(5), 054024 (2006). doi:10.1117/1.2363367
Abstract
Fluorescence lifetime measurement is widely used in the biological sciences due to its inherent sensitivity and concentration independence. Frequency domain high-throughput plate readers and time-resolved energy transfer (TRET) plate readers are in common use and have been successful in a variety of applications ranging from basic biochemistry to drug discovery. Time-domain systems would have advantages due to their ability to distinguish both FRETing and non- FRETing populations, but have been difficult to develop due to inherent difficulties with background autofluorescence and lifetime component separation. Using a modified commercial lifetime plate reader, we demonstrate a method for removal of the complex auto-fluorescent background decay, described using a stretched exponential function (StrEF). We develop a generalized multi-exponential fitting algorithm (GeMEF), which progressively accounts for confounding lifetime components in FRET-based assays using a series of control experiments. We demonstrate the separability of FRET strength and efficiency and apply the technique to protein–protein interactions and protein conformational assays in a cell-based format. Presenilin 1 (PS1) is known to be important in Amyloid Precursor Protein (APP) processing in Alzheimer's disease. Using transfected cells, we demonstrate APP-PS1 interactions by FRET in a cell-based, 96-well plate format.
Phill B. Jones, Lauren Herl, Oksana Berezovska, Anand T. N. Kumar, Brian J. Bacskai, Bradley T. Hyman, "Time-domain fluorescent plate reader for cell based protein-protein interaction and protein conformation assays," Journal of Biomedical Optics 11(5), 054024 (1 September 2006). http://dx.doi.org/10.1117/1.2363367
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KEYWORDS
Proteins

Fluorescence resonance energy transfer

Fluorescence lifetime imaging

Luminescence

Picosecond phenomena

Alzheimer's disease

Data modeling

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