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Wait, Could We Make a Computer Out of Our DNA?

Related: Why would we want to?


It's easy to miss the amazing natural computing power of living things. Our brains recognize faces with a facility that the latest software struggles to match; an amoeba can create a transportation network as efficient as one designed by the Tokyo rail system's crack team of engineers, and even single-celled bacteria perform sophisticated navigational computations as they hunt for food. Every single one of our cells continually carries out basic computing functions, taking inputs from the environment and processing them to come up with the correct output. So what would it take to harness the tremendous computing power of biology and make a computer out of DNA?

Before answering that question, let’s step back: Why would anyone want to make a computer out of biological parts? While it's true that organisms can perform spectacular feats of computation, there are some clear downsides to wetware computers. Rather than being housed in a plastic case that sits on your desk, a DNA computer would exist in a test tube or Petri dish, with a poor user interface and no networking capabilities. In general, DNA computers will always be downright terrible at most of the tasks that we expect of conventional computers. A biological version of IBM's Watson (which must be named IBM Crick) is never going to appear on Jeopardy!, although scientists have invented a DNA computer that plays a mean (and slow and expensive) game of Tic-Tac-Toe.

So, if you're not likely to replace your iPad with a Petri dish, is there anything useful that we can do with a biological computer?

A programmable DNA computer could be inserted into human tumors to act as a diagnostic or treatment tool.

Aside from the mere coolness of making things with DNA, there are two major reasons to engineer biological computers. First, biological computers have the advantage of massive parallelization. Most laptop and desktop computers have only a handful of processing cores, meaning that they are limited in the number of computations that they can execute simultaneously. A biological computer could easily be made of billions or trillions of processors, substantially more than the world's fastest supercomputer, all working simultaneously to solve a problem. As a bonus, biological computation consumes relatively little energy, compared with a silicon supercomputer that, at its peak, burns through enough energy to power a small town.

The second and more important advantage of biological computers is that they can be integrated into living systems. For example, a programmable DNA computer could be inserted into human tumors to act as a diagnostic or treatment tool. The DNA computer would sense the state of each cell and generate some useful output. In a proof-of-concept experiment, a group of researchers created a biological circuit that was able to classify a mix of lab-grown cells as either cancerous or not and then send the cancerous cells a signal to self-destruct. In the future, biological computing devices like this could be used to non-invasively monitor the progression of tumors or target drug treatments to very specific cellular sites.

WHILE IT’S EASY TO envision exciting (and even dangerous) applications, so far, biological computers, like quantum computers, exist mainly as ideas or expensive and impractical proof-of-concept set-ups. After several decades of research and tens of millions of dollars in funding, our ability to engineer biological computers remains extremely limited, and not even very useful to other scientists. So what's keeping us from building genuinely useful DNA computers?

A key part of almost any practical computer is a set of reliable parts, such as transistors or logic gates that assess one or more inputs and then output one of two possible answers, such as one or zero, or true or false. So far, it's been extremely difficult to build reliable logic gates inside a living cell, because the cell's natural machinery often interferes with the functioning of the synthetic logic gate.

But recently Stanford Professor Drew Endy's research team came up with an improved DNA logic gate, better insulated from unintended effects caused by a cell's natural systems. The researchers demonstrated that they can reliably build any of the basic types of logic gate, including two that have been particularly difficult to implement with DNA. These new devices, called “transcriptors,” work in many ways like a transistor, except instead of switching an electrical current, the transcriptor switches a gene on or off (by controlling the process of "transcription"). It does this with enzymes that literally flip a segment of DNA inside of a cell. When the DNA segment is oriented one way, the output gene is off; flip the DNA segment and the gene comes on. Independently, Timothy Lu's team at MIT came up with a related design that achieves similar results.

If we can build reliable DNA logic gates, the fundamental building blocks of a computer, what are the prospects for useful biological computers in the near future? Making biology easy to engineer is one of Drew Endy's major goals, but actually, utility is only one of several reasons for his interest in building parts for biological computers. He's one of the leaders of a project called Synthetic Aesthetics, which brings together not only bio-engineers, but also social scientists, artists, and designers to create "shared and new territory between synthetic biology, art and design," a collaboration that is not unusual in other engineering endeavors (think architecture), but seems radical in the context of biology.

A collaboration centered around designing biology may sound premature, given the very limited technical abilities we have right now, but Endy says "I don't want to talk about it, I want to do it." Doing it, however, will likely involve moving away from traditional ideas about computer architecture like logic gates, and to the far frontier of the poorly understood computing principles used by living beings. We can explain how millions of transistors on a silicon chip work together to make a functioning computer processor, but we have no idea how the billions of neurons in the human brain work together to execute the incredibly challenging computations involved in everyday activities, the most remarkable ones being the basis of consciousness itself. The most profound outcome of our efforts to build biological computers might be a new understanding of ourselves.