Biotech

A technique for repeatedly encoding, storing and erasing digital data within the DNA of living cells, using natural enzymes adapted from bacteria has been developed by Stanford University scientists in the Department of Bioengineering, a joint effort of the School of Engineering and the School of Medicine. The method essentially has created the equivalent of a genetic bit.

Bioengineers attempting to turn microbes into manufacturering stations have longed for a kit of components as regular and predictable as those used by electrical engineers.

Now a group of engineers at Stanford University say they’ve managed to make one such component—the genetic equivalent of a reliable memory device. In a report published this week in Proceedings of the National Academy of Sciences, they detail how they developed rewritable DNA memory that works in living cells and can keep its data even as cells divide and multiply.

“It took us three years and 750 tries to make it work, but we finally did it,” said Jerome Bonnet, PhD, on his latest research.

DNA memory already exists but has been limited to write-once versions that can record only as many cellular events (such as cellular divisions) as there are bits. But the reversible storage system the Stanford researchers have created is capable of being expanded to record a potentially huge number of events—2n events, where n is the number of bits.

This improved biological memory could enhance the study of how we age and how cancer grows.

In the future lies the possibility of reprogramming cells to slow the aging process or to act as sentries that prevent cancer’s uncontrolled cell division. The rewritable recombinase addressable data (RAD) module created by the Stanford bioengineers is a segment of DNA that switches between states when the bacteria carrying it encounters specific proteins.

In practical terms, they have devised the genetic equivalent of a binary digit — a “bit”. “Essentially, if the DNA section points in one direction, it’s a zero. If it points the other way, it’s a one,” graduate student Pakpoom Subsoontorn explained.

“Programmable data storage within the DNA of living cells would seem an incredibly powerful tool for studying cancer, aging, organismal development and even the natural environment,” said Endy.

In the computer world, their work would form the basis of what is known as non-volatile memory — data storage that can retain information without consuming power. In biotechnology, it is known by a slightly more technical term, recombinase-mediated DNA inversion, after the enzymatic processes used to cut, flip and recombine DNA within the cell.

A class of proteins called “integrases” scan DNA sequences until they find two specific sequences (attachment sites called attB and attP) and bind to them. The integrase then cuts out the DNA strand between those sites, flips it over, and reattaches it so that string of base pairs reads in reverse. This chemical process, which the researchers refer to as “setting,” also changes the characteristics of the attachment sites attB and attP. (They become attL and attR, respectively.) This upside-down state, says the Stanford team, is the equivalent of a 1 in an electronic memory device.

Drew Endy, a Stanford assistant professor of bioengineering, who led the research, says that the major technical hurdle the group had to overcome was avoiding what’s called “bidirectionality.” That is the tendency for some recombinase proteins (the respective versions of integrase and excisionase that the researchers chose are two of many) to cause the RAD module to flip, and then to cause it to flip back to its previous state before the change in state is recorded. But in the end, say the researchers, they created a system of DNA registers that switch when, and only when, they’re in the presence of the protein-based inducers.

As important, they note, is that the states can be switched repeatedly with no performance degradation. “Developing biological systems, especially those based on DNA and cells, that ‘compute’ like digital computers has been challenging,” says Steven Benner, a distinguished fellow at the Foundation for Applied Molecular Evolution in Gainesville, Fla. Benner explains the nature of the challenge, noting that “biological molecules, like all molecules, intrinsically do ‘analog’ computation better than ‘digital.’ [The Stanford researchers’] latest work is a big step toward getting digital behavior from structures that are, fundamentally, not digital.”

Asked how much data the device they demonstrated is able to store, Endy proudly reports that it is currently capable of storing 1 bit, as in roughly a hundred billionth of the amount of data that can be stored on a key-fob-size USB flash drive.

Though the DNA memory device’s capacity is relatively minuscule, “its purpose is not to compete with silicon, but to get access to data storage in places where silicon doesn’t work,” says Endy.

For Endy and the team, the future of computing then becomes not only how fast or how much can be computed, but when and where computations occur and how those computations might impact our understanding of and interaction with life.

“One of the coolest places for computing,” Endy said, “is within biological systems.” His goal is to go from the single bit he has now to eight bits — or a “byte” — of programmable genetic data storage.

“I’m not even really concerned with the ways genetic data storage might be useful down the road, only in creating scalable and reliable biological bits as soon as possible. Then we'll put them in the hands of other scientists to show the world how they might be used,” Endy said.

In fact, says the Stanford researcher, 8 bits is more than enough to keep track of changes in any replicating biological system. With that capacity, he envisions applications such as a fail-safe element in cellular therapeutics. When, say, a cancer patient is injected with living cells reengineered to attack a tumor, the RAD module could be set to control the rate and number of cell divisions so that the cure doesn’t morph into a curse.


SOURCE  Stanford School of Medicine

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