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Better biosensors through nanopore technology

Research and discovery High performance systems May 2, 2019

Sometimes science requires thinking on a small scale…a very small scale. Nanotechnology involves the manipulation of matter on an atomic and molecular level, and has enabled advances in fields from health care to renewable energy. But what happens when experiments are performed at a scale too small to be observed?

At the University of Illinois at Urbana-Champaign, Aleksei Aksimentiev, Kumar Sarthak, and their colleagues are using computer-based simulations to offer a fuller picture of nanopore technology. This process involves passing an analyte (the substance to be identified and measures, such as a strand of DNA or a protein) through a tiny pore in a membrane, which is immersed in an electrolyte solution, allowing ions to flow through the pore. As the analyte moves through the pore, researchers measure ionic current blockages, which are sensitive to its unique properties. The pores, though, are far smaller in diameter than a human hair, and the human eye is ill equipped to see inside. Thankfully, the team has created a method for simulating the process, allowing scientists to observe what’s happening in the pore.

Aleksei Aksimentiev, UIUC

With the aid of Jetstream’s on-demand, cloud-based system, the team has developed a robust, inexpensive model called the steric exclusion model (SEM) of nanopore conductance. This method is far more efficient than current methods, but is still sensitive enough to account for the atomic structure of both the nanopore and the analyte. Given the large amount of memory required, the team needed a way to perform calculations that the average desktop can’t come close to accommodating. The team designed a workflow that runs on a desktop, running the jobs and then sending the data back to the team in a self-contained, convenient way.

Without SEM, researchers are forced to rely on experience and intuition when choosing or modifying nanopores to detect a particular analyte. There are other computational methods, but they are often prohibitively expensive to run, or are not sensitive enough to yield the information researchers need about the pore and analyte. The simulations Aksimentiev, Sarthak, and their colleagues have devised trade out guesswork and expense for a fast, accurate method that will afford researchers the opportunity to determine the best modifications for their experiments. The team would like to make the workflow accessible to the scientific community, so that they can run the simulations themselves. The tool will be a game-changer, allowing experimentalists to screen different designs of pores and conditions, and thus, to design better biosensors.

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