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Method of the future uses single-cell imaging to identify gene interactions
Date:2/8/2010

n collaboration with Chris Bakal and Norbert Perrimon at Harvard Medical School, they "knocked-down" components of the Rho-signaling network using RNA interference and then imaged thousands of fly cells, gathering measurements of cell perimeter, nuclear area, and more than 150 other morphological features for each cell. The data was then passed through the computational framework to produce a set of high-confidence interactions, supported by confirmation of previously known interactions.

The group found that by making combinatorial knockdowns of Rho network components, their computational method was able to accurately infer Rho-signaling network interactions more precisely than when using only data from single knockdowns. Berger noted that this finding highlights the importance of combinatorial experiments for inferring complex networks, necessary to overcome natural redundancy in signaling pathways. As perturbation of the Rho pathway in humans has been implicated in cancer and other diseases, the authors believe that these predicted interactions will be excellent candidates for future study.

Berger expects that in combination with other sources of data, imaging as a new source of high-throughput data should appreciably increase the accuracy of known signaling networks. "This work provides a glimpse into the future," added Berger, "where looking under the microscope manually at cells one-by-one is replaced with automated high-throughput processing of many cellular images."


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Contact: Peggy Calicchia
calicchi@cshl.edu
516-422-4012
Cold Spring Harbor Laboratory
Source:Eurekalert

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