Silicon is Slow

In March of this year, Adleman and his colleagues at USC reported taking DNA computing a giant step further, solving what they say may be the largest problem ever tackled by a nonelectronic device. In this experiment, Adleman sought to compile a viable guest list for a group of demanding partygoers, each of whom imposes specific demands: I'll come only if so-and-so is snubbed but my good friend so-and-so is invited. To accommodate the demands of 20 such finicky attendees, more than a million combinations of guests must be considered. After four days of chemical reactions and code sifting, during which nucleic acids representing individual partygoers attracted and repelled each other, Adleman's DNA computer produced the master party list. This wasn't the first time USC researchers had attempted to unravel the party puzzle with a DNA computer, but earlier efforts had involved at most nine guests. Taking into account the preferences of 20 people, which required calculations by trillions of snippets of DNA molecules, was an immeasurably more imposing experiment.


Other researchers have suggested that DNA computing based on reliable, robust DNA-based structures, rather than strands floating in solution, could be even more powerful. One of the more successful efforts is at Duke University, where computer scientists John Reif and Thom LaBean are working with so-called DNA tiles-strands of nucleic acids woven into interlocking structures that, by virtue of their interaction with other tiles, form simple logic circuits. LaBean and Reif are testing their concept at the simplest binary level: Do the combined tiles reliably behave like basic logic gates? Their initial tests prove a tile-based DNA computer actually works. Connect a sufficient number of such logic gates and the result could be a supercomputer no larger than a teardrop.


Huge barriers must be overcome before even a small full-fledged DNA computer can be designed. For one thing, says Reif, the more complex the DNA structure, the more likely it is to make errors that can produce faulty computations. In nature, these errors are mutations, and error correction through constant DNA repair is built into living cells; no such automatic correction exists, however, in DNA computing. Moreover, the parts of the DNA that contain the "answer" have to be extracted and analyzed. Consequently, researchers still need to develop an efficient way to read results. Otherwise the speed of the DNA computation would be offset by the time it takes to actually ascertain the outcome.


"In theory," says Reif, "you could probably use a DNA computer to do anything a normal computer could do. But in practice, you probably wouldn't use one for running Microsoft Windows. You'd use it for things you couldn't otherwise build at the molecular scale."


Suggestions for DNA computers include the creation of biosensors that could identify pathogens in the environment or detect biochemical events at the cellular level within the body. Another logical use: deploying DNA computers to aid in the enormous data searches undertaken in the hugely expanding field of genetic research.