High-precision technique stores cellular ‘memory’ in DNA

Engineers program human and bacterial cells to keep a record of complex molecular events.

The ability to process and store information in living cells is essential for developing next-generation therapeutics and studying biology in situ. However, existing strategies have limited recording capacity and are challenging to scale.

MIT scientists have recently developed a technique called DOMINO to precisely edit DNA bases to store complex memories in the DNA of living cells, including human cells. The technique is robust and scalable for encoding logic and memory in bacterial and eukaryotic cells.

Scientists reported that the technique can potentially record intensity, duration, sequence, and timing of many events in the life of a cell, such as exposures to certain chemicals. What’s more, it’s storage capacity can make it useful for complex circuits in which one event, or series of events, triggers another event, such as the production of a fluorescent protein.

Fahim Farzadfard, a Schmidt Science Postdoctoral Fellow at MIT and the lead author of the paper said, “This platform gives us a way to encode memory and logic operations in cells in a scalable fashion. Similar to silicon-based computers, in order to create complex forms of logic and computation, we need to have access to vast amounts of memory.”

The new DOMINO system uses a variation of the CRISPR-Cas9 enzyme that makes all the more well-defined mutations since it directly modifies and stores bits of information in DNA bases instead of cutting DNA and waiting for cells to repair the damage. The analysts demonstrated that they could get this system to work precisely in both human and bacterial cells.

To get a higher level of precision, scientists attached a version of Cas9 to a recently developed “base editor” enzyme, which can convert the nucleotide cytosine to thymine without breaking the double-stranded DNA.

Guide RNA strands, which direct the base editor were to make this switch, are produced only when certain inputs are present in the cell. When one of the target inputs is present, the guide RNA leads the base editor either to a stretch of DNA that the scientists added to the cell’s nucleus, or to genes found in the cell’s own genome, depending on the application. Measuring the resulting cytosine to thymine mutations allows the researchers to determine what the cell has been exposed to.

Farzadfard said, “You can design the system so that each combination of the inputs gives you a unique mutational signature, and from that signature, you can tell which combination of the inputs has been present.”

Using the system, scientists performed logical calculations including AND and OR gates, which can detect the presence of multiple inputs. They also generated circuits that can record cascades of events that occur in a certain order, similar to an array of dominos falling.

Wilson Wong, an associate professor of biomedical engineering at Boston University, who was not involved in the research said, “This is very innovative work that enables recording and retrieving cellular information using DNA. The ability to perform sequential or logic computation and associative learning is particularly impressive. This work highlights novel genetic circuits that can be achieved with CRISPR/Cas.”

During the study, scientists designed their own circuits so that the final output would activate the gene for green fluorescent protein (GFP). They then measured the fluorescence level and estimated ow many mutations had accumulated, without killing the cells.

Scientists noted, “The technology could potentially be used to create mouse immune cells that produce GFP when certain signaling molecules are activated, which researchers could analyze by periodically taking blood samples from the mice.”

Applications for these types of complex memory circuits include tracking the changes that occur from generation to generation as cells differentiate, or creating sensors that could detect, and possibly treat diseased cells. Another possible application is designing circuits that can detect gene activity linked to cancer.

The study is published in the journal Molecular Cell and funded by the National Institutes of Health, the Office of Naval Research, the National Science Foundation, the Defense Advanced Research Projects Agency, the MIT Center for Microbiome Informatics and Therapeutics, and the NSF Expeditions in Computing Program Award.

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