While researchers have already manipulated atoms to make letters small enough to fit all the words of the Encyclopedia Britannica on the head of a pin, and have assembled rudimentary molecular computers and machines, these feats remain novelties whose creation depends on difficult and expensive methods.
Now Paul Rothemund, a computer scientist at Caltech, with a background in biology, has developed a relatively inexpensive way to quickly design and build arbitrary shapes and patterns using DNA – and, he says, it’s simple enough for high-school students to use. Since a variety of molecules and nanoparticles can be linked to DNA, this technique could be a way of quickly patterning components as diverse as proteins and semiconducting nanotubes, possibly leading to minute electronic devices or devices for studying cells at an unprecedented level of detail.
[Click here for images of some of these self-assembled DNA shapes.]
“It’s really spectacular work. I’m extremely excited about it,” says William Shih, professor of biological chemistry and molecular pharmacology at Harvard Medical School, who is now working to extend Rothemund’s technique to building three-dimensional structures. Rothemund’s work, he says, has taken the small field of DNA nanotechnology and “opened it up to becoming a mainstream tool by making it one or two orders of magnitude cheaper and easier to do.”
Nadrian Seeman, the New York University chemist who pioneered the use of DNA for constructing complex shapes, says, “By moving up in scale, he is able to produce more intricate and larger patterns than were practical with previous approaches. This is an exciting advance which is likely to revolutionize pattern formation on this scale.”
In Rothemund’s method, a long strand of DNA snakes back and forth until it forms a desired shape. The key to getting the DNA to form this way, and to holding it in place, are short “staples” of DNA with sequences chosen to attach to specific parts of the long strand. Rothemund divides the long strand into sections; then a staple might attach to sections 86 and 112, for example, bringing them together and causing the long strand to fold. A couple of hundred unique staples can fold the DNA into just the right shape.
A computer program takes care of identifying the sequences the staples need to have. “I design [the structure] I want on the computer,” Rothemund says. “It spits out a set of 250 DNA sequences. I order them; they come in the mail in a bunch of little tubes. I mix them together [along with the long strand of DNA], add some salt, heat it up to boiling and cool it down to about room temperature, and then it’s done.” Once mixed together, the strands of DNA assemble themselves into the desired structure.
Such self-assembly methods can be used to make any shape or pattern measuring 100 nanometers across or less, and with features about 6 nanometers apart. In comparison, a red blood cell is about 7,000 nanometers across. An article describing Rothemund’s work appearing today in the journal Nature demonstrates the versatility of the technique with pictures of smiley faces, squares, triangles, and stars (click here). But Rothemund can also make intricate patterns on these shapes – for example, he’s drawn a 1:200 trillion scale map of the Western Hemisphere that could fit inside a cell.
Designing each structure took about a week, according to Rothemund. After that, trillions of copies self-assemble in just a few hours – this speed of production is one of the qualities that makes self-assembly so attractive.
Right now, though, the technique is a solution in search of the problem. But Rothemund and others, such as Shih, expect practical applications to come soon, as researchers learn how easy the technique is and find ways to apply it to specific problems. One possibility is patterning electronic devices at a smaller scale than is possible using today’s optical lithography methods. Thomas LaBean, a chemist and computer scientist at Duke University, who has developed another general-purpose DNA self-assembly technique that is a bit more difficult and has a lower resolution than Rothemund’s, is developing single-electron transistors patterned with DNA that could serve as components for such a device.
There are significant challenges remaining, however, before working devices using this method appear. “With self-assembly, there is an inherent error rate,” says Harvard’s Shih. Unlike today’s computers, for example, self-assembled computers will need to detect and work around non-functioning components. Also, many applications will require bigger patterns than Rothemund has made so far. One potential solution to that problem, which Rothemund has tried already with limited success, is combining smaller shapes using strands of DNA, much as cells come together to build an organism, he explains.
Also, while the new technique is affordable for labs, it is not yet cheap enough for making bulk materials. The self-assembly already demonstrated, however, could be practical for building “nanoarrays” that can measure the precise contents of single cells, Shih says, allowing biologists to better learn the roles played by individual cells, for example, those in a nervous system.
In fact, the best application may not yet have been thought of. “I don’t feel discouraged that we haven’t found the super-killer applications for this yet,” says Shih. “Being able to assemble trillions of molecularly precise devices is something we have just not been able to do. And now suddenly we have this method where we can do that, for an affordable price. It’s not obvious what those payoffs will be, but we all feel like they’re there.”
Lloyd Smith, a chemist from University of Wisconsin, Madison, and author of a commentary on the work in Nature, wrote, “We are now perhaps more limited by our imagination than our ability.”
Geoffrey Hinton tells us why he’s now scared of the tech he helped build
“I have suddenly switched my views on whether these things are going to be more intelligent than us.”
Meet the people who use Notion to plan their whole lives
The workplace tool’s appeal extends far beyond organizing work projects. Many users find it’s just as useful for managing their free time.
Learning to code isn’t enough
Historically, learn-to-code efforts have provided opportunities for the few, but new efforts are aiming to be inclusive.
Deep learning pioneer Geoffrey Hinton has quit Google
Hinton will be speaking at EmTech Digital on Wednesday.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.