Autofluorescence removal using a customized filter set
Authors:
- Alberto Santamaria‐PangASAlberto Santamaria‐Pang
- Fiona GintyFiona Ginty
- 16 July 2013
- journal article
- research article
- Published by Wiley in Microscopy Research and Technique
- Vol. 76 (10) , 1007-1015
Abstract
Quantitative fluorescence microscopy is severely hindered by intrinsic autofluorescence (AF). Endogenous fluorescent molecules in tissue and cell samples emit fluorescence that often dominates signals from specific dyes. This makes AF removal critical to the development and practice of quantitative fluorescence microscopy. In this study, we showed that AF signal could be separated from specific signal using a customized filter set. The filter set used the same excitation and beam splitter as the standard filter set, but the emission filter was red‐shifted 40–60 nm from the peak of the specific dye. This filter set configuration collected mostly AF with minimum contribution from the specific dye. A linear transformation of AF images was required to correct for the difference in exposure and filter configuration. The constants (slope and intercept) in linear transformation were obtained through a pixel to pixel comparison between AF images (no staining) obtained by the standard filter set and the customized AF filter set. After staining of specific dye, the standard filter collecting target dye spectra was used to capture both target signal and AF, whereas customized filter was used to capture only AF. AF removal was accomplished by subtracting the linear transformed AF image from the image obtained from the standard filter. To validate our approach, we examined weak staining of androgen receptor in an AF abundant prostate tissue sample. Our method revealed a similar but cleaner nuclear staining of androgen receptor in a specimen, when compared to a traditional autofluorescence removal method. Microsc. Res. Tech., 76:1007–1015, 2013.Keywords
Funding Information
- General Electric Company Global Research Center Molecular Imaging and Diagnostic Advanced Program
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