Analyzing Multiple 2D Protein Gel Images with Matlab Image Processing Toolbox for the Identification of Maize Proteins Associated with the Resistance to Aflatoxin Accumulation

Two-dimensional gel electrophoresis (2DE) has been instrumental in proteomics studies for revealing differences in proteomic profiles expressed in tissues of interest under different treatments. However, the limitations such as gel to gel variation and lack of an effective quantification method to digitally analyze all the protein spots across multiple gels have limited the adaptation of this technique as a quantitative tool.  In this research, we established a working protocol for detection and quantification of protein spots from multiple maize 2D protein gel images using Matlab Image Processing Toolbox. Developing kernels from two resistant (Mp715 and Mp719) and two susceptible (Va35 and Mp04:87) maize inbred lines were used in this research to identify proteins associated with the resistance to Aspergillus flavus infection and aflatoxin accumulation. Protein extraction was performed using TCA/acetone precipitation in combination of a phenol extraction step. The protein gel electrophoresis was performed using PROTEAN IEF Cell (Bio-Rad) and PROTEAN II XL cell (Bio-Rad). Gel images were obtained with an Alpha imager or a Typhoon Imager (GE Healthcare). Matlab image processing tools were used to analyze all the 2D protein gel images in the experiment simultaneously. The 2D protein gel images were first aligned and cropped. Mean gel image was calculated for image segmentation and detection of protein spots. Differentially expressed maize proteins associated with resistance to Aspergillus flavus infection and aflatoxin accumulation were identified through principal components analysis on the mean intensities of detected protein spots. This approach provides a potential means for high throughput comparative quantitative proteomics studies with large datasets under various treatments.