Researchers at Clarkson University in New York have created an enzyme capable of learning and forgetting information, reports the MIT Technology Review.
This development is an important step forward in research into biochemical computing. The result is the "first realisation of a simple variant of associative memory in an enzymatic biochemical process," according to the researchers, who note that this paves the way for complex biomolecular information processing.
Although conventional electronic computers are highly efficient at certain processes, biological systems are able to perform many other tasks with far greater speed and efficiency than electronics, such as understanding language or recognising facial expressions. Biological methods of encoding information, such as proteins and DNA, are therefore being scrutinised by scientists looking for new ways to process information.
The enzyme set used by Vera Bocharova and her co-authors was trained to produce a certain chemical output when it sensed a particular chemical input. It was later able to "unlearn" this system and stop producing the output.
Although biological computing systems such as this are still very simple, they have potential to eventually outperform electronic computers, and to function in totally different environments.
While enzyme-based memory is an important development in biochemical computing, this year has also seen huge progress in genetically-based biological computing. In March, a Stanford team announced that they had used genetic material to build the first biologically-based transistor, dubbed the transcriptor.
A fully-functional genetically-based computer requires a way to store information, a way to transmit information, and a system of logic to control the function of the computer. Last year, the Stanford team, headed by Drew Endy, assistant professor of bioengineering, developed the first two components: a DNA-based data storage system, and a mechanism to transmit genetic information. The transcriptor is the third and final component necessary for a full genetic computer, providing a logical system based on DNA and RNA.
In order to contribute to faster development of a biological computer, Endy and his team have made all their research open to the public. "Most of biotechnology has not yet been imagined, let alone made true. By freely sharing important basic tools everyone can work better together," says Jerome Bonnet, a postdoctoral bioengineering researcher.
The potential for biological computers is huge, says Endy: "Biological computers can be used to study and reprogramme living systems, monitor environments and improve cellular therapeutics."
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