Improved in Vivo Whole-Animal Detection Limits of Green Fluorescent Protein–Expressing Tumor Lines by Spectral Fluorescence Imaging
Open Access
- 1 July 2007
- journal article
- Published by SAGE Publications in Molecular Imaging
- Vol. 6 (4) , 269-76
- https://doi.org/10.2310/7290.2007.00023
Abstract
Green fluorescent protein (GFP) has been used for cell tracking and imaging gene expression in superficial or surgically exposed structures. However, in vivo murine imaging is often limited by several factors, including scatter and attenuation with depth and overlapping autofluorescence. The autofluorescence signals have spectral profiles that are markedly different from the GFP emission spectral profile. The use of spectral imaging allows separation and quantitation of these contributions to the total fluorescence signal seen in vivo by weighting known pure component profiles. Separation of relative GFP and autofluorescence signals is not readily possible using epifluorescent continuous-wave single excitation and emission bandpass imaging (EFI). To evaluate detection thresholds using these two methods, nude mice were subcutaneously injected with a series of GFP-expressing cells. For EFI, optimized excitation and emission bandpass filters were used. Owing to the ability to separate autofluorescence contributions from the emission signal using spectral imaging compared with the mixed contributions of GFP and autofluorescence in the emission signal recorded by the EFI system, we achieved a 300-fold improvement in the cellular detection limit. The detection limit was 3 × 103 cells for spectral imaging versus 1 × 106 cells for EFI. Despite contributions to image stacks from autofluorescence, a 100-fold dynamic range of cell number in the same image was readily visualized. Finally, spectral imaging was able to separate signal interference of red fluorescent protein from GFP images and vice versa. These findings demonstrate the utility of the approach in detecting low levels of multiple fluorescent markers for whole-animal in vivo applications.Keywords
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