There have been created a computer based on DNA, which finally can be reprogrammed
There is an opinion that DNA will save us from computers. Thanks to advances in the replacement of silicon transistors, DNA-based computers promise to provide us with massive parallel computational architectures that are currently impossible. But here’s the catch: the molecular chips that were created until today did not have any flexibility at all. Today, using DNA for computation is the same as “creating a new computer from a new equipment to run a program alone,” says scientist David Doty.
Doty, a professor at the University of California at Davis, and his colleagues decided to find out what would be needed to create a DNA computer that could actually be reprogrammed.
In an article published this week in Nature magazine, Doty and his colleagues at the University of California and Maynooth University demonstrated just that. They showed that you can use a simple trigger to force the same basic set of DNA molecules to implement many different algorithms. Although this study is still exploratory in nature, reprogrammable molecular algorithms can be used in the future to program DNA robots that have already successfully delivered drugs to cancer cells.
“This is one of the most important work in the field,” says Torsten-Lars Schmidt, an assistant professor in the Department of Experimental Biophysics at Kent State University, who did not participate in the study. “Previously, there was an algorithmic self-assembly, but not to such a degree of complexity.”
In electronic computers, like what you use to read this article, bits are binary information units that tell a computer what to do. They represent the discrete physical state of the underlying equipment, usually in the form of the presence or absence of electric current. These bits — or even the electrical signals that implement them — are transmitted through circuits consisting of logic elements that perform an operation with one or more input bits and output one bit as an output.
By combining these simple building blocks again and again, computers can run surprisingly complex programs. The idea behind DNA computation is to replace electrical signals with nucleic acids — silicon — with chemical bonds and create biomolecular software. According to Eric Winfrey, a computer scientist from Caltech and co-author of the work, molecular algorithms use the natural information processing capability of DNA, but instead of giving control to nature, “computers control the growth process.”
Over the past 20 years, several experiments have used molecular algorithms for such things as playing tic-tac-toe or building different shapes. In each of these cases, the DNA sequences had to be carefully designed to create one particular algorithm that would generate the DNA structure. What is different in this case is that the researchers developed a system in which the same basic DNA fragments can be ordered to create completely different algorithms and, therefore, completely different end-products.
This process begins with DNA origami, the method of folding a long section of DNA into the desired shape. This folded piece of DNA serves as a “seed” (seed, seed), which launches an algorithmic conveyor, just as caramel gradually grows on a thread dipped in sugared water. The seed remains largely the same, regardless of the algorithm, and changes are made only in a few small sequences for each new experiment.
After the scientists created the seed, they added it to the solution from 100 other DNA strands, DNA fragments. These fragments, each of which consists of a unique arrangement of 42 nucleic bases (the four basic biological compounds that make up DNA), are taken from a large collection of 355 DNA fragments created by scientists. To create a different algorithm, scientists must select a different set of starting fragments. A molecular algorithm that involves a random walk requires different sets of DNA fragments, which the algorithm uses for counting. Since these DNA fragments are connected during the assembly process, they form a circuit that implements the selected molecular algorithm on the input bits provided by the seed.
Using this system, scientists created 21 different algorithms that can perform tasks such as recognizing multiples of three, choosing a leader, generating patterns, and counting up to 63. All these algorithms were implemented using different combinations of the same 355 DNA fragments.
Of course, writing code by dropping DNA fragments into a test tube will not work yet, but this whole undertaking is a model of future iterations of flexible computers based on DNA. If Doty, Winfrey and Woods succeed, the molecular programmers of tomorrow will not even think about the biomechanics underlying their programs in the same way that modern programmers do not have to understand the physics of transistors to write good software.
The potential uses for this nano-scale assembly technique are astounding, but these predictions are based on our relatively limited understanding of the nanoscale world. Alan Turing was unable to predict the emergence of the Internet, and therefore we may also have to wait for incomprehensible applications of molecular informatics.