A new method for assigning common spot boundaries for multiple gels in two‐dimensional gel electrophoresis

Abstract

The benefits of defining common spot boundaries when several gels from 2-DE are compared and analyzed have lately been stressed by both commercial software producers and users of this software. Though the importance of common spot boundaries is clearly stated, few reports exist that target this issue explicitly. In this study a method for defining common spots boundaries is developed, called the spot density method. The method consists of the following steps: segmentation and spot identification on each individual gel, transferring the spot-center coordinates for all gels onto a single new gel, collecting spot centers clustered together in the new gel and finally assigning pixels and new spot boundaries based on the spots in each cluster. The method is compared to a synthetic gel approach, and validated by visual inspection of three representative areas in the gels. The gel images need to be aligned prior to segmentation and spot identification, but the method can be used regardless of the choice of segmentation procedure. This makes the method an easy extension to existing methods for spot identification and matching. Conclusions based on the visual inspection are that the spot density method identifies partly overlapping spots and low-intensity spots better than the synthetic gel approach.

Operator- and software-related post-experimental variability and source of error in 2-DE analysis

“…Hence more operator manual interventions will be required in direct proportion to the number of gels studied. Since the performance of spot-matching algorithms worsens when more gels are added to the analysis (Rye et al 2008), a possible solution would be the use of a 4th generation program, where the spot matching is substituted by the image warping and the creation of the fusion gel image.…”

New approach for segmentation and quantification of two-dimensional gel electrophoresis images

“…In summary, this article presents an efficient way of automatic detection of quality markers to use in conjunction with the Marker Controlled Watershed Transform or even with the Image Foresting Transform (Falcao et al, 2004) for the segmentation of 2-DE images and quantification of protein spots. Also, the presented technique can be used in the segmentation step for approaches that use common spot boundaries such as Rye et al (2008) or even Progenesis Samespots. The results can also be used by gel alignment for gel alignment methods such as the one presented in Pèrés et al (2008).…”