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The long-term goal of research in the Näthke laboratory is to understand how cellular adhesion, migration, and division are regulated in concert during development and differentiation and how changes in these processes contribute to tumor formation. Our aim is to determine the molecular mechanisms that govern the function of the adenomatous polyposis coli (APC) protein in these fundamental cellular processes and to understand why mutations in APC predispose patients to colorectal cancer, the second-leading cause of cancer deaths in the Western world. APC is a large cytoplasmic protein that is involved in many basic cellular processes including cell migration, adhesion, and proliferation. We use a wide range of experimental approaches to study its biochemistry and cell biology, including embryos, whole tissue, cultured cells, in vitro assays combined with cellular and molecular biology techniques, and high-resolution microscopy. Ultimately, we hope that understanding the function of APC and its interactions with the cytoskeleton and key signaling pathways will help in the development of novel prognostic and therapeutic agents for colorectal cancer.
www.dundee.ac.uk/biocentre/SLSBDIV4isn.htm
The Technique
Fluorescence microscopy is a key tool that we use to gain insight into biological processes regulated by APC. This technique usually generates large numbers of images whose full value can only be realized if quantitative information can be extracted from them. This was the case in our project aimed at measuring the effect of APC on spindle checkpoint proteins during mitosis. We required a method that could detect and quantitate spot-like objects in a large number of multichannel fluorescence images. To facilitate this, we made use of the Open Microscopy Environment (OME), a powerful open-source software system for the management and analysis of images obtained by microscopy and other imaging techniques. Together with Ilya Goldberg, we developed a method for the automated analysis of our images: given a set of suitable images, the system will analyze each in turn, finding and quantifying all spot-like objects in each image. Quantitative information about the size, intensity, shape, etc., of each spot is generated, and the results are summarized in a spreadsheet. This work has also demonstrated more generally how OME can be employed for quantitative image analysis: by replacing the current spot finding routine with different plug-in algorithms, other types of analysis can be achieved.
Open Microscopy Environment and FindSpots: integrating image informatics with quantitative multidimensional image analysis, p. 199.
