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Innovation

DNA computer can calculate square roots

Today, square roots... tomorrow, disease detection! Researchers have developed the most powerful molecular computer ever. If successfully integrated into living cells, it could diagnose disease.
Written by Janet Fang, Contributor

DNA is like software, telling our cellular and molecular hardware what to do – except it uses biochemical reactions rather than the electronic circuitry of computers we’re used to.

Now, researchers have built the largest, most sophisticated molecular computer from scratch using DNA molecules – instead of computer chips.

Right now, this ‘DNA computer’ can perform logic operations, like calculating square roots over several hours.

But speed, however, isn’t the point…

One day, these biochemical circuits can be injected into biological systems – like living cells or blood samples – to monitor chemical levels. If that happens, they might be able to diagnose and treat diseases.

In fact, introducing computation into a cell may provide new ways to seek out disease using similar logic and terminology as Google’s search engine.

By engineering these circuits, researchers can explore how info is processed in biological systems, and ultimately design biochemical pathways with decision-making capabilities. Less powerful molecular computers have been around since the 1990s.

Like a conventional computer, the DNA computer uses logic gates that process incoming signals using simple rules. However, these gates are made from carefully designed DNA molecules, not silicon. The input and output signals are also made from DNA, rather than being electrical pulses, Nature News explains.

Caltech’s Lulu Qian and Erik Winfree designed their new circuit – made from 74 single-strands of DNA – to find the square root of numbers up to 15 and round the answer to the nearest whole number.

Different types of DNA strands represent 1s and 0s, the binary numbers used in standard digital circuits. They took advantage of DNA’s natural ability to zip (when two single strands of DNA bind together at complementary sites) and unzip, Science News explains:

The basic design incorporates two types of synthetic DNA in a test tube: single-stranded DNA molecules that float free like lone wolves and double-stranded ones that carry a small notch of open DNA called a “toehold.” The single-stranded DNA cruises solo until bumping into an entwined pair of DNA strands with a matching toehold. The lone wolves anchor onto that toehold by zipping, eventually booting off one of the original two strands. After the zipping and unzipping is done, a new double-stranded molecule and single-stranded lone wolf float around the test tube.

By precisely designing these DNA cascades, the team could squirt molecules representing 1001 in binary notation, or 9, into the mix and isolate a binary answer once the resulting reactions finished. In this case, that answer was a square root: binary 11, or 3.

(If I’ve mixed too many metaphors or if it’s still unclear, consult Wiki’s ‘counting in binary’ section and then take a look at a diagram over at Ars Technica.)

A set of 4 fluorescent colors was used to communicate the two-digit binary answer. For each digit of the answer, one color would signal a "1" while another would signal a "0." Up to 130 different double stranded molecules existed in the same test tube.

"If you can get chemistry to do something as utterly alien as computing the square root of a four-digit binary number,” Winfree says, “then you can probably get it to do a lot of other things too.”

Teams are already applying the design towards cheaper and more deployable means of disease detection. A biochemical circuit to diagnose malaria, for example, calculates its answer using chemicals found in blood.

"We'd like to make chemical systems that can probe their molecular environments, process chemical signals, make decisions, and take actions at the chemical level,” Winfree says.

The study was published in Science last week.

Image: DNA molecules in the largest synthetic circuit of its type / Lulu Qian, Caltech

This post was originally published on Smartplanet.com

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