MIT scientists invent remote control acid-stimulation of neurons

MIT scientists invent a new nanotechnology that stimulates acid-sensing ion channels on neurons with wireless proton generation.

Illustration of the new nanotransducer technology from MIT.

 

Wireless, remote-controlled brain stimulation is a rapidly growing field of science. Not only do these types of technologies help neuroscientists study basic biology, but they also have the potential to help patients by treating neurological disorders. 

Five years ago, the Anikeeva lab at MIT published a paper in Science describing a technology utilizing magnetic nanoparticles that allows for remote controlled, deep brain stimulation in mice using heat. Some neurons have channels that activate when heated. By injecting magnetic nanoparticles into the brain and heating them using externally applied alternating magnetic fields, neurons could be stimulated on demand.

Earlier this year, the same lab extended this idea to mechanically-sensitive neurons. In a paper in ACS Nano these scientists showed that magnetic nanodiscs, which start ‘wiggling’ when a magnetic field is applied, can apply enough mechanical force on neurons to stimulate their force-sensing receptors.

In a new paper online today in Nano Letters, we extended this idea to neurons that are stimulated by acid release. Some neurons have what are known as acid-sensing ion channels, or ASICs. In this study led by my colleague Jimin Park, we invented a new technology we called nanotransducers that marry polymers to magnetic nanoparticles. When these nanotransducers are exposed to an alternating magnetic field cue, they convert that cue into acid (i.e. proton) release. This acid stimulates ASICs on neurons. This new platform provides an alternative to other neuromodulation technologies, such as those that utilize heat or force, which might not be suitable for some diseases or applications. This also provides a new tool to study the role of acid in biology, which is critical in diseases like many cancers. 


 

Ph.D. Candidate at the Massachusetts Institute of Technology