Spectrum IEEE – Bioengineers looking to turn microbes into manufacturers have longed for a kit of components as regular and predictable as those used by electrical engineers. But biology is a lot messier. 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.
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 ginned up is capable of being expanded to record a potentially huge number of events—2n events, where n is the number of bits.
Diagram: Drew Endy Rewritable DNA Memory: When patches of DNA whose endpoints are the attachment sites attB and attP encounter the integrase protein [Int, in the red box], they’re flipped upside down, changing the DNA memory’s state from the equivalent of a “0” to a “1”. When they subsequently encounter integrase plus another type of protein called excisionase [Xis, white box], the DNA patches reset to “0”.
The use of synthetic biological systems in research, healthcare, and manufacturing often requires autonomous history-dependent behavior and therefore some form of engineered biological memory. For example, the study or reprogramming of aging, cancer, or development would benefit from genetically encoded counters capable of recording up to several hundred cell division or differentiation events. Although genetic material itself provides a natural data storage medium, tools that allow researchers to reliably and reversibly write information to DNA in vivo are lacking. Here, we demonstrate a rewriteable recombinase addressable data (RAD) module that reliably stores digital information within a chromosome. RAD modules use serine integrase and excisionase functions adapted from bacteriophage to invert and restore specific DNA sequences. Our core RAD memory element is capable of passive information storage in the absence of heterologous gene expression for over 100 cell divisions and can be switched repeatedly without performance degradation, as is required to support combinatorial data storage. We also demonstrate how programmed stochasticity in RAD system performance arising from bidirectional recombination can be achieved and tuned by varying the synthesis and degradation rates of recombinase proteins. The serine recombinase functions used here do not require cell-specific cofactors and should be useful in extending computing and control methods to the study and engineering of many biological systems.
Atypical architecture for an 8-bit synchronous counter capable of recording a series of 256 input pulses (36) would require 16 recombinases recognizing distinct DNA sequences or the multiplexing of recombinase activity across repeating DNA recognition sites.
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.
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.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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