After cooling, the system uses a high-resolution microscope to acquire multi-dimensional images of the animal on-chip.
"The advantage of using our microchip is that it's completely compatible with any standard microscope you'd find in a biology laboratory epifluorescence, stereo, multi-photon or confocal with no modification required," explained Lu.
The researchers have shown that the intensity and patterns of fluorescent markers imaged inside cooled animals versus those in anesthetized animals exhibit no discernible differences. Based on each animal's phenotype, or how each animal looks under the microscope, the computer identifies whether it is wild-type or mutant and sorts it into the appropriate group.
Initial tests to assess the system were conducted on C. elegans, one of the tiniest multi-cellular organisms that share many fundamental cellular/molecular mechanisms with more advanced organisms. However, the automated system can also be adapted to study other small organisms such as fruit flies and fish embryos.
For one experiment, Lu and her team tested the ability of the system to analyze the gene expression pattern the intensity, location and timing of appearance of a fluorescent protein in a population of organisms. They were able to sort the free-moving animals into two categories, those fluorescing in a particle neuron and those that are not, at a speed of approximately 900 animals per hour. More than 90 percent of the animals were loaded into the observation chamber within 0.3 seconds after the previous animal exited.
In another experiment, the researchers were successful in separating a small number of mutant animals from a large population of wild-type animals based on the fluorescence in a single pair of neurons. With on-line processing and decision-making without human supervision, the system achieved
|Contact: Abby Vogel|
Georgia Institute of Technology Research News