Two-dimensional electrophoresis analysis of proteomics based on image feature and mathematical morphology

In this paper, a novel method to automatically detect protein spots on a two-dimensional (2-D) electrophoresis gel image is proposed to implement proteomics analysis of complex analyte. On the basis of the identifying spots results based on color variation and spot size features, morphological feature is introduced as a new criterion to distinguish protein spots from non-protein spots. Image-sharpening, edge-detecting and morphological feature extraction methods were consequently combined to detect protein spots on a 2-D electrophoresis gel image subject to strong disturbance. The proposed method was applied to detect the protein spots of proteomic gel images from E. coli cell, human kidney tissue and human serum. The results demonstrated that this method is more accurate and reliable than previous methods such as PDQuest 7.2 and ImageMaster 5.0 software for detecting protein spots on gel images with strong interferences.