The dawn of biological computers is at hand. In a major first for synthetic biology, Stanford engineers have used genetic material to create a biological transistor. Called the "transcriptor," the creation is the final, missing component necessary for the creation of a biological computer that could enable researchers to program functions into living cells.
Modern computers rely on three standard functions. One: they must be able to store information. Two: they have to be able to transmit information. Three: they need a basic system of logic – a set of rules that governs how they should function given one or more forms of input. A biological computer would implement all three on a cellular level, using proteins and DNA in place of silicon chips.
The first two functions have been demonstrated with cellular materials before. Several labs have now demonstrated the ability to store digital data in DNA, some of them at jaw-dropping densities; and last year, a team led by Stanford bioengineer Drew Endy developed a system for transmitting genetic information between cells. Now, in a study recounted in the latest issue of Science, Endy's team has developed what it calls a "transcriptor" – the biological equivalent of a digital transistor – and with it a system of logic that can control cellular function.
In your standard computer, transistors govern the flow of electricity by playing red light/green light with electrons along a circuit. Similarly, a transcriptor regulates the flow of a protein called RNA polymerase along a strand of DNA. Transistors and transcriptors are, at their most basic, on/off switches – the gatekeepers of information transmission, storage, amplification, and so forth.
The rules that these gatekeepers follow give rise to the logic systems that dictate what problems a computer can solve. A transcriptor gatekeeper that lives by a code of "AND," for example, might allow RNA polymerase to continue along a strand of DNA when two predetermined conditions are "true" – if, for example, the transcriptor detects the presence of Enzyme-A AND Enzyme-B inside the cell.
A transcriptor that abides by the code of "OR," on the other hand, would allow RNA polymerase to continue when either or both of the enzymes are present. In computer science, transistors that abide by AND-/NAND-/OR-/XOR-/NOR-/XNOR-rules (which you can read all about here) are called Boolean logic gates. Endy calls his transcriptor equivalents Boolean Integrase Logic gates. Or "BIL" gates, for short. Below, Endy provides an in-depth explanation of Transcriptors and BIL gates.
Here's the takeaway: if you line a bunch of these logic gates up, you form a logic circuit. Get enough logic circuits together, and you have a computer that can handle just about any computation you throw at it – whether it's addition and subtraction on a calculator, or gene expression inside a cell.
Endy plans on starting small. For now, he's working with bacteria, helping other researchers use his BIL gates to engineer E. coli that can be programmed to change color. And in a refreshingly practical take on the potential applications of his team's creation, Endy told NPR's Morning Edition that he doubts these DNA computers will ever outwit your iPhone; but this, he said, is missing the point.
"We're building computers that will operate in a place where your cellphone isn't going to work."
Endy's team's research is published in the latest issue of Science. For a fantastic animated explanation of Transcriptors, check out this series of graphics created by Adam Cole for NPR.
Think the memory card in your camera is high-capacity? It's got nothing on DNA. With data accumulating at a faster rate now than any other point in human history, scientists and engineers are looking to genetic code as a form of next-generation digital information storage.
Now, a team of Harvard and Johns Hopkins geneticists has developed a new method of DNA encoding that makes it possible to store more digital information than ever before. We spoke with lead researcher Sriram Kosuri to learn why the future of archival data storage is in genetic code, and why his team's novel encoding scheme represents such an important step toward harnessing DNA's vast storage potential.
Humanity has a storage problem. Recent surveys conducted by IDC Digital Universe suggest that the perfusion of technology throughout society has triggered an explosion in the volume of information that we as a species produce on a daily basis. Between photos, video, texts, tweets, Facebook updates, unsolicited FarmVille requests, Instagram posts and various other forms of digital data production, the world's information is doubling every two years, and that raises some important questions, chief among them being: where the hell do we put it all?
"In 2011 we had 1.8 * 1021 bytes of information stored and replicated" explains Sriram Kosuri, a Harvard geneticist and member of the Wyss Institute's synthetic biology platform, in an email to io9. "By 2020 it will be 50 times that. That's an astounding number; and doesn't include a much larger set of data that's thrown away (e.g., video feeds)."
As Kosuri points out, not all of this information needs to be stored, but — being the diligent little hoarders that we are — a good deal of it will be cached away somewhere for posterity; and at the rate we're generating information, we'll need to find new storage solutions if we want to have any hope of keeping up with our demand for space. "Our ability to store, manage, and archive such information is being constantly strained already," notes Kosuri. "Archival storage is also a large problem."
The (Theoretical) Solution: The Advantages of DNA Storage
Archival storage is where DNA comes in. As storage media go, it's hard to compete with the universal building blocks of life. In an article published in today's issue of Science, Kosuri — in co-authorship with geneticist Yuan Gao and synthetic biology pioneer George Church — describes a new technique for using DNA to encode digital information in unprecedented quantities. We'll get to their novel storage method in the next section, but for now let's look at some numbers that help contextualize what Kosuri identifies as the two major advantages of DNA storage: information density and stability.
At theoretical maximum, one gram of single stranded genetic code can encode 455 exabytes of information. That's almost half a billion terabytes, or 4.9 * 1011 GB. (As a point of reference, the latest iPad tops out at 64 GB of storage space.) DNA strands also likes to fold over on top of themselves, meaning that, unlike most other digital storage media, data needn't be restricted to two dimensions; and being able to store data in three-space translates to more free-space.
DNA is also incredibly robust, and is often readable even after being exposed to unfavorable conditions for thousands of years. Every time researchers recover genetic information from a woolly mammoth specimen, or sequence the genome of a 5,300 year-old human mummy, it's a testament to DNA's durability and data life. Just try recovering files from a 5,000-year-old CD or DVD. Hell, try it with a 20-year old disc; odds are it just isn't going to happen.
That being said, DNA has its shortcomings. "It's not re-writable, it's not random access, and it is very high latency," explains Kosuri, "so really the applications are for archival storage (not to downplay the importance of archives)."
The (Practical) Solution
5.27-megabits probably doesn't strike you as a lot (that comes out to roughly 660 kilobytes of information, about what you'd find on a 3.5" floppy from the 80s), but it's impressive for at least three reasons:
One: It positively crushes the previous DNA-storage record of 7,920 bits.
Two: The novel encoding method employed by Kosuri and his colleagues allowed them to address issues of cost and accuracy, two long-standing technical hurdles facing DNA storage:
The major reason why this would have been difficult in the past is that it is really difficult to construct a large stretch of DNA with exact sequence, and make it cheaply. We took an approach that allows us to use short stretches of DNA (basically by having an address (19 bits) and data block (96 bits), so each short stretch can be stitched together later after sequencing. Using short stretches allowed us to leverage both next-generation synthesis [for writing data]… and next-generation sequencing [for reading data] technologies to really lower cost and ease.
Three: It offers a compelling proof of concept that DNA can be used to store digital information at remarkable densities. "What we published in terms of scale is… obviously small compared to commercial technologies now," explains Kosuri, but "using our method, a petabyte of data [one petabyte = 1,024 terabytes] would require about 1.5 mg of DNA." Since that genetic information can be packaged in three dimensions, that translates to a storage volume of about one cubic millimeter.
Both articles can be viewed via the following links: