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Georgia Tech Team Develops Automated Microfluidic System to Screen C. elegans

Investigators at the Georgia Institute of Technology have developed a microfluidic device that can automate and standardize the genetic screening of small, multicellular animals.
The system, which also includes software that can acquire and analyze the images and sort the organisms, could eventually enable researchers to more widely use these animals in drug discovery, according to a researcher involved in developing it.
“I think it definitely moves us a step closer to the use of these multicellular organisms in research, including drug discovery,” said Hang Lu, an assistant professor at the Georgia Tech School of Chemical and Biomolecular Engineering.
Currently, little is available for high-resolution, microscopy-based screening techniques. Platforms that use small, multicellular organisms such as zebrafish and C. elegans can be alternatives to cell-based assays in situations where cells are difficult to work with, because most small, multicellular organisms are inexpensive, easy to image, and develop rapidly.
“This technology is fairly easily adapted to other systems such as fly embryos and zebrafish,” said Lu. These organisms are small, and one would just have to change the geometry of the devices. The basic principle will be the same, she said.
Lu said that the system can facilitate rapid genetic screens based on subtle phenotypes that would be difficult to detect manually by, for example, simply viewing the organisms through a microscope, because the human eye is imprecise at detecting phenotypic indicators such as absolute changes in brightness.
Lu also said that using this system, researchers can potentially screen for mutants that have altered the intensity of reporters or have slightly altered morphology. 
The investigators said that the chip has five features that ensure its consistent operation for an extended period of time: it automatically self-regulates the loading of the nematodes by a simple, passive design; the setup automatically positions the nematodes in an identical position in the chip to minimize the travel of the motorized stage to locate the worm, which reduces the processing time and increases throughput; the device has an integrated local temperature-control system to cool the worms to ~4°C for imaging; the microchip and setup are compatible with any standard microscopy setup with no modification required; and the microchip has no permanent features and is easy to fabricate.
The researchers also mentioned that losses of worms through the system were minimal (~3 percent).      
The team described the system online this week in Nature Methods.
To test their system, the researchers compared it with a complex object parametric analyzer and sorter, or COPAS, made by Union Biometrica, which they said “is high-throughput but low magnification.” They found that their system has higher optical resolution than COPAS, and therefore has a broader range of potential applications.
In addition, because the Georgia Tech system is modular, supplementary devices can be incorporated for tasks such as administering small molecule libraries to populations prior to screening in pharmacological studies.    
Single File
The organisms, in this case C. elegans, are sent into the polydimethylsiloxane microfluidic chip one at a time using on-chip valves, and pictures are taken of each individual animal. The researchers then “do computational work” and determine if the animal has a wild type or mutant phenotype, Lu explained.
The nematodes are then sorted on the chip according to phenotype. “The chip essentially allows you to do a lot of these manipulations automatically instead of manually … in front of a microscope,” Lu said.
The approach can perform screens based on cellular and subcellular phenotypes with 95-percent accuracy per round at a rate of several hundred nematodes per hour, according to Lu.

“People are definitely using microfluidic platforms more and more to look at small, multicellular animals.”

“People are definitely using microfluidic platforms more and more to look at small, multicellular animals such as C. elegans,” said David Weitz, a professor of physics and applied physics at Harvard University, who is not part of the Georgia Tech team. He called the system “a nice piece of engineering,” and said it that is complementary to work being done elsewhere.

“I am not sure that C. elegans would be used that widely in drug discovery, but they would be more likely to be used in systems biology work,” he said.
Lu, who studied C. elegans as a postdoc, said her team’s technology could also make the task of studying the worms less tedious and labor-intensive. When she established her own lab at Georgia Tech, Lu and her colleagues “thought it would be nice if we could easily manipulate [C. elegans] on microfluidic chips, so we decided to try to automate the whole process.”
In the course of trying to automate the screens, they determined that the system can do some things much better than humans in terms of manipulating the worms. “For example, human eyes are very good at picking out certain things, and not very good at quantifying certain things,” Lu said.  
For example, humans are not very good at quantifying the brightness and intensity of emitted fluorescence. “You cannot tell me exactly how many photons came off of a particular spot,” said Lu. “But a computer, a bioinformatics software program, can quantitate that for you.”
“The way that you manipulate certain things may not always be the way I manipulate things,” said Lu. Even if two investigators are looking at the same animals and using the same lab equipment, they may reach slightly different conclusions.
But “if you sort the worms automatically using bioinformatics tools, you can actually do a much better, more consistent job.”

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