Literature DB >> 16888770

Quantitative linear unmixing of CFP and YFP from spectral images acquired with two-photon excitation.

Christopher Thaler1, Steven S Vogel.   

Abstract

BACKGROUND: Spectrally distinct fluorescent proteins (FPs) have been developed permitting the visualization of several proteins simultaneously in living cells. The emission spectra of FPs, in most cases, overlap, making signal separation based on filter technology inefficient and in cases of bleed-through, inaccurate. Spectral imaging can overcome these obstacles through a process called linear unmixing. Given a complex spectra composed of multiple fluorophores, linear unmixing can reduce the complex signal to its individual, weighted, component spectra. Spectral imaging with two-photon excitation allows the collection of nontruncated emission spectra. The accuracy of linear unmixing under these conditions needs to be evaluated.
METHODS: Capillaries containing defined mixtures of CFP and YFP were used to test the accuracy of linear unmixing using spectral images obtained with two-photon excitation.
RESULTS: Linear unmixing can be accurate when wavelength and power-matched reference spectra are provided to the algorithm. Linear unmixing errors can occur due to (1) excitation laser contamination of emission signals, (2) the presence of FRET, (3) poor selection of excitation wavelength, and (4) failure to background subtract reference spectra.
CONCLUSIONS: Linear unmixing, when judiciously performed, can accurately measure the abundance of CFP and YFP in mixed samples, even when their relative intensities range from 90:1. (c) 2006 International Society for Analytical Cytology.

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Year:  2006        PMID: 16888770     DOI: 10.1002/cyto.a.20267

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  12 in total

1.  Energy migration alters the fluorescence lifetime of Cerulean: implications for fluorescence lifetime imaging Forster resonance energy transfer measurements.

Authors:  Srinagesh V Koushik; Steven S Vogel
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2.  Thin-film tunable filters for hyperspectral fluorescence microscopy.

Authors:  Peter Favreau; Clarissa Hernandez; Ashley Stringfellow Lindsey; Diego F Alvarez; Thomas Rich; Prashant Prabhat; Silas J Leavesley
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3.  Hyperspectral imaging microscopy for identification and quantitative analysis of fluorescently-labeled cells in highly autofluorescent tissue.

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Review 4.  A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

Authors:  Silas J Leavesley; Brenner Sweat; Caitlyn Abbott; Peter Favreau; Thomas C Rich
Journal:  J Biophotonics       Date:  2017-05-09       Impact factor: 3.207

5.  Fluorescence lifetime imaging microscopy of intracellular glucose dynamics.

Authors:  Jithesh V Veetil; Sha Jin; Kaiming Ye
Journal:  J Diabetes Sci Technol       Date:  2012-11-01

Review 6.  Advanced fluorescence microscopy techniques--FRAP, FLIP, FLAP, FRET and FLIM.

Authors:  Hellen C Ishikawa-Ankerhold; Richard Ankerhold; Gregor P C Drummen
Journal:  Molecules       Date:  2012-04-02       Impact factor: 4.411

7.  Assessing FRET using spectral techniques.

Authors:  Silas J Leavesley; Andrea L Britain; Lauren K Cichon; Viacheslav O Nikolaev; Thomas C Rich
Journal:  Cytometry A       Date:  2013-08-08       Impact factor: 4.355

Review 8.  Two-photon probes for in vivo multicolor microscopy of the structure and signals of brain cells.

Authors:  Clément Ricard; Erica D Arroyo; Cynthia X He; Carlos Portera-Cailliau; Gabriel Lepousez; Marco Canepari; Daniel Fiole
Journal:  Brain Struct Funct       Date:  2018-05-11       Impact factor: 3.270

9.  Simultaneous quantitative live cell imaging of multiple FRET-based biosensors.

Authors:  Andrew Woehler
Journal:  PLoS One       Date:  2013-04-16       Impact factor: 3.240

10.  Spectral unmixing: analysis of performance in the olfactory bulb in vivo.

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Journal:  PLoS One       Date:  2009-02-09       Impact factor: 3.240

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