The bacteria Geobacter sulfurreducens came from humble beginnings; it was first isolated from dirt in a ditch in Norman, Oklahoma. But now, the surprisingly remarkable microbes are the key to the first ever artificial neurons that can directly interact with living cells.
G. sulfurreducens communicate with each other through tiny, protein-based wires that researchers at the University of Massachusetts Amherst have harvested and used to make artificial neurons that can, for the first time, process information from living cells without an intermediary device amplifying or modulating the signals, the researchers say.
While some artificial neurons already exist, they require electronic amplification to sense the signals our bodies produce, explains Jun Yao, who works on bioelectronics and nanoelectronics at UMass Amherst. The amplification inflates both power usage and circuit complexity, and so counters efficiencies found in the brain.
Yao’s team’s neuron can understand the body’s signals at their natural amplitude of around 0.1 volts. This “is highly novel,” says Bozhi Tian, a biophysicist who studies living bioelectronics at The University of Chicago and was not involved in the work. This work “bridges the long-standing gap between electronic and biological signaling” and demonstrates interaction between artificial neurons and living cells that Tian calls “unprecedented.”
Real neurons and artificial neurons
Biological neurons are the fundamental building blocks of the brain. If external stimuli are strong enough, charge builds up in a neuron, triggering an action potential, a spike of voltage that travels down the neuron’s body to enable all types of bodily functions, including emotion and movement.
Scientists have been working to engineer a synthetic neuron for decades, chasing after the efficiency of the human brain, which have so far seemed to escape the abilities of electronics.
Yao’s group has designed new artificial neurons that mimic how biological neurons sense and react to electrical signals. They use sensors to monitor external biochemical changes and memristors—essentially resistors with memory—to emulate the action potential process.
As voltage from the external biochemical events increases, ions accumulate and begin to form a filament across a gap in the memristor—which in this case was filled with protein nanowires. If there is enough voltage, the filament completely bridges the gap. Current shoots through the device, and the filament then dissolves, dispersing the ions and stopping the current. The complete process mimics a neuron’s action potential.
The team tested its artificial neurons by connecting them to cardiac tissue. The devices measured a baseline amount of cellular contraction, which did not produce enough signal to cause the artificial neuron to fire. Then the researchers took another measurement after the tissue was dosed with norepinephrine—a drug that increases how frequently cells contract. The artificial neurons only triggered action potentials during the higher, medicated trial, proving that they can detect changes in living cells.
The experimental results were published 29 September in Nature Communications.
Natural nanowires
The group has G. sulfurreducens to thank for the breakthrough.
The microbes synthesize miniature cables, called protein nanowires, that they use for intraspecies communication. These cables are charge conductors that survive for long periods of time in the wild without decaying. (Remember, they evolved for Oklahoma ditches.) They’re extremely stable, even for device fabrication, Yao says.
To the engineers, the most notable property of the nanowires is how efficiently ions move along them. The nanowires offered a low energy means of transferring charge between human cells and artificial neurons, thus avoiding the need for a separate amplifier or modulator. “And amazingly, the material is designed for this,” says Yao.
The group developed a method to shear the cables off of bacterial bodies, purifying the material and suspending it in a solution. They lay the mixture out and let the water evaporate, leaving a one-molecule-thin film made from the protein nanowire material.
This efficiency allows the artificial neuron to yield huge power savings. Yao’s group integrated the film into the memristor at the core of the neuron, lowering the energy barrier for the reaction that causes the memristor to respond to signals recognized by the sensor. With this innovation, the researchers say, the artificial neuron uses 1/10th the voltage and 1/100th the power of others.
Chicago’s Tian thinks this “extremely impressive” energy efficiency is “essential for future low-power, implantable, and biointegrated computing systems.”
The power advantages make this synthetic neuron design attractive for all kinds of applications, researchers say.
Responsive wearable electronics, like prosthetics that adapt to stimuli from the body, could make use of these new artificial neurons, Tian says. Eventually, implantable systems that rely on the neurons could “learn like living tissues, advancing personalized medicine and brain-inspired computing” to “interpret physiological states, leading to biohybrid networks that merge electronics with living intelligence,” he says.
The artificial neurons could also be useful in electronics outside the biomedical field. Millions of them on a chip could replace transistors, completing the same tasks while decreasing power usage, Yao says. The fabrication process for the neurons does not involve high temperatures and utilizes the same kind of photolithography silicon chip manufacturers do, he says.
Yao does, however, point out two possible bottlenecks producers could face when scaling up these artificial neurons for electronics. The first is obtaining more of the protein nanowires from G. sulfurreducens. His lab currently works for three days to generate only 100 micrograms of material—that’s about the mass of one grain of table salt. And that amount can only coat a very small device, so Yao questions how this step in the process could scale up for production.
His other concern is how to achieve a uniform coating of the film at the scale of a silicon wafer. “If you wanted to make high-density, small devices, the uniformity of film thickness actually is a critical parameter,” he explains. But the artificial neurons his group has developed are too small to do any meaningful uniformity testing for now.
Tian doesn’t expect artificial neurons to replace silicon transistors in conventional computing, but instead sees them as a parallel offering for “hybrid chips that merge biological adaptability with electronic precision,” he says.
In the far future, Yao hopes that such bio-derived devices will also be appreciated for not contributing to e-waste. When a user no longer wants a device, they can simply dump the biological component in the surrounding environment, Yao says, because it won’t cause an environmental hazard.
“By using this kind of nature-derived, microbial material, we can create a greener technology that’s more sustainable for the world,” Yao says.
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