Automated Image Analysis of Fluorescence Microscopic Images to Identify Protein-protein Interactions

The identification of protein-protein interactions along with their spatial and temporal localization is vital data for assigning functional information to proteins. Historically, these data sets obtained from fluorescence microscopy, have been analyzed manually, a process that is both time consuming and tedious. The development of an automated system that can measure the location dynamics of the interaction between two proteins inside a live cell is a high priority. This paper describes an automated image analysis system used to identify the interactions between two proteins of interest fused to either GFP or DIV IVA, a bacterial cell division protein that localizes to the cell poles. Upon the induction of DIV IVA fusion protein expression, the GFP-fusion protein will be recruited to the cell poles if a positive interaction occurs. Advanced image processing and feature extraction algorithms are discussed in detail and a statistical feature set used to quantify the image-based information is developed