Artificial Intelligence Helps Detect Subtle Differences In Mutant Worms
Research into the genetic factors behind certain disease mechanisms, illness progression and response to new drugs is frequently carried out using tiny multi-cellular animals such as nematodes, fruit flies or zebra fish. Often, progress relies on the microscopic visual examination of many individual animals to detect mutants worthy of further study. Now, scientists have demonstrated an automated system that uses artificial intelligence and cutting-edge image processing to rapidly examine large numbers of individual Caenorhabditis elegans, a species of nematode widely used in biological research. Beyond replacing existing manual examination steps using microfluidics and automated hardware, the system's ability to detect subtle differences from worm-to-worm – without human intervention – can identify genetic mutations that might not have been detected otherwise. By allowing thousands of worms to be examined autonomously in a fraction of the time required for conventional manual screening, the technique could change the way that high throughput genetic screening is carried out using C. elegans.
Image credit: Georgia Tech; Bob Goldstein, UNC Chapel Hill