Method of the future uses single-cell imaging to identify gene interactions

CAMBRIDGE, Mass. Cellular imaging offers a wealth of data about how cells respond to stimuli, but harnessing this technique to study biological systems is a daunting challenge. In a study published online in researchers have developed a novel method of interpreting data from single-cell images to identify genetic interactions within biological networks, offering a glimpse into the future of high-throughput cell imaging analysis. For years, scientists have been peering through a microscope at cells as they change appearance in response to different treatments, yet data collection is arduous, largely conducted qualitatively by eye. However, recent technological advances have led to the development of high-throughput image screening methods that can produce extensive datasets of hundreds of different morphological features. With the ability to collect large imaging datasets, researchers from MIT and Harvard Medical School recognized an opportunity to explore the cellular networks that regulate cell morphology. ?These images are an enormous source of data that is only beginning to be tapped,? said MIT researcher Bonnie Berger, senior author of the work published today.