NEW YORK – Researchers from the Massachusetts Institute of Technology working on computing using cellular DNA have taken a step forward with a new strategy that improves the precision and scale of operations.
Led by first author Fahim Farzadfard and senior author Timothy Lu, the researchers created a "molecular recording and DNA memory platform that uses genomic DNA as an addressable, readable, and writable information storage and computation medium in living cells, much like a hard drive." They described this DNA-based Ordered Memory and Iteration Network Operator, or DOMINO, in a paper published today in Molecular Cell. They also described how DOMINO could be used in logical operations.
"It opens up a lot more than what we've been able to do previously," Lu, a professor of biological engineering, said in an interview. "We can capture information about sequential events." The work has potential applications in cancer biology and environmental monitoring.
DOMINO builds on previous work from Lu's lab that used CRISPR-Cas9 and single guide RNAs that targeted their own genomic sequences in order to record cellular events in DNA.
But those methods created unspecific mutations. "It was like burning a candle," Lu said. After enough use, the sgRNAs petered out. "And with CRISPR deletion you can't control how quickly you're burning it."
DOMINO still uses CRISPR, but a modified form that flips single bases — cytosine to thymine or guanine to adenine. This specificity makes it so "you can make the writing conditionally dependent on the previous one, and therefore you can capture sequential information," Lu said.
Lu said he envisioned using DOMINO in biomedical applications, such as researching how diseases like cancers develop over time. "Cancer develops not due to a single event, but a multitude of events and order is also important," he explained.
Farzadfard suggested that, generally, DOMINO can help with readouts from cell-based computers. The control it affords enables the use of fluorescent reporters. "You basically don't need sequencing anymore," he said. And because the cell doesn't need to be destroyed to get the information inside, it could be placed back into its environment, enabling continuous monitoring.
The type of computing enabled by these operators is limited. "We are not close to doing what we can do in silicon," Farzadfard said. "It's not fast enough to do high-throughput computation."
But it can record lots of events in parallel. "If you have a population of cells, you might be able to record information from many of them, and use that to infer information about the environment," he said.
And Lu said there are lots of areas where biology is "uniquely suited to solve a problem."
"Even a small amount of computation could be very powerful," he said.