Video: Time-lapse videos of a single rolling DNA-based motor and its path tracked through fluorescent imaging are shown side by side. Andrew Mugler, an assistant professor of physics at Purdue University, is part of the research team that created the motor. (Video courtesy of Emory University)
A Purdue University professor is part of a research team that created a DNA-based motor that “rolls” rather than “walks” and is 1,000 times faster than conventional DNA-based motors.
Andrew Mugler, an assistant professor of physics in Purdue’s Department of Physics and Astronomy, provided insight into the theoretical framework of the physics associated with the motors and created computer models and simulations used in the research.
DNA motors have the potential to become easily programmable nanomachines that could be used as drug-delivery vehicles or sensors to detect markers of disease or contaminants, but their speed and fidelity must first be improved, Mugler said.
A paper detailing the research, led by Khalid Salaita at Emory University, will be published in Nature Nanotechnology and is currently available online.
The team’s motor has a tiny plastic bead center coated with thousands of protruding DNA strands, allowing it to roll as the DNA binds to a surface of complementary RNA. The motor is powered by an enzyme that chops up the RNA after the DNA motor has rolled over and bound to it. This prevents the rolling motor from moving backward or repeating steps in a path, which has slowed down conventional DNA-motors, Mugler said.
The motors provide a simple way to look for DNA mutations by observing a change in speed that can be detected through the use of a smartphone camera modified with a magnifying lens, which the team demonstrated.
“Our method offers a way of doing low-cost, low-tech diagnostics in settings with limited resources,” Salaita said in a statement.
Mugler, who was a post-doctoral researcher at Emory at the time of the research, also used the motors to explore a longstanding problem in statistical physics called the “self-avoiding random walk.”
He used computer modeling to show that the movements of the motors captured on video interpolate between the purely random regime at the sub-second timescale to the self-avoiding regime at the minute timescale.
“The motors roll around in a winding fashion, but they generally do not cross their own path because the RNA has already been chopped up there,” said Mugler. “At first, over short length and time scales, the motors’ behavior is equivalent to a purely random walk, but at the longer length and time scales the motors’ behavior becomes that of the self-avoiding random walk. This was very exciting to me as a theoretical physicist because, to our knowledge, it is the first nano-scale experimental system that truly acts like a self-avoiding random walk. It allows for rigorous tests of the associated statistics and path probabilities, which have only recently been theoretically worked out.”
The National Institutes of Health and the National Science Foundation funded the research.