Telometer Paper

Telomeres shorten in cancer and pre-cancerous lesions, therefore, the measurement of telomere lengths in situ will facilitate studies on cancer pathogenesis. To overcome the limitations posed by traditional Southern-based methods, we recently developed a technique for telomere length analysis in fixed tissue samples. In this method, quantitative data can be extracted using existing digital image analysis software. However, several of the image processing steps are cumbersome, requiring extensive manual intervention. We therefore have developed a custom software plugin for extracting telomere length data from fluorescence images using the analysis program ImageJ. This software streamlines the process of quantitative telomere length analysis and allows for direct export of results to an established MS Access database.

Design

Quantification of the digitized fluorescent signals is accomplished through the image analysis software package ImageJ (http://rsb.info.nih.gov/ij/) and the custom designed plugin as follows: matched telomeric and nuclear DNA grayscale image files are captured using a Zeiss Axioskop epifluorescence microscope equipped with appropriate fluorescence filter sets (Carl Zeiss Inc, Thornwood, NY; Omega Optical, Brattleboro, VT) and a cooled CCD camera (Micro MAX digital camera, Princeton Instruments, Trenton, NJ). The images are first normalized with a simple background subtraction, and the resulting telomere image is run through a sharpening filter, followed by enhancement using a rolling ball algorithm (http://rsb.info.nih.gov/ij/developer/api/ij/plugin/filter/BackgroundSubtracter.html.) for contouring of telomeric spots, followed by manual thresholding to remove any remaining background noise. Binarized masks are then created and applied to the original fluorescence images. For a given cell, telomeric signals identified by the segment mask, which are contained within the area inscribed by the nuclear DNA signal, are then measured, and the data for each telomeric spot tabulated. The total DAPI (DNA) fluorescence signal for each nucleus is likewise quantified. For each cell, the individual telomere intensities are summed, and this total is divided by the total DAPI fluorescence signal for that nucleus. This normalization to the nuclear DAPI signal corrects for differences in nuclear cutting planes and ploidy. Tabulated data is then stored in a MySQL (www.mysql.com) database and is viewed through Microsoft Access (Microsoft Corp.).

Results

The newly written ImageJ plugin described above performed equivalently to the prior, more labor-intensive method, when assessed on standard curve validation image sets. In particular, use of the rolling ball algorithm provides rapid and superior delineation of telomeric signals in the context of high levels of background autofluorescence, as is commonly the case with formalin-fixed tissue specimens. Overall, the new plugin largely eliminates the need for manual intervention and should be applicable to other situations requiring quantification of fluorescence signals, such as with FISH images.

Conclusion

The newly developed plugin for ImageJ accelerates the process of extracting quantitative data from fluorescence microscopy images. The new program features superior discrimination of fluorescent signals and substantially reduces the need for user intervention during image processing. This software has proven useful in telomere length analysis and should be broadly applicable to other FISH studies where quantification is desired.