As the modern world produces ever more data, researchers are scrambling to find new ways to store it all. DNA holds promise as an extremely compact and stable storage medium, and now a new approach could let us write digital data directly into the genomes of living cells.

Efforts to repurpose nature’s built-in memory technology aren’t new, but in the last decade the approach has gained renewed interest and seen some major progress. That’s been driven by an explosion of data that shows no signs of slowing down. By 2025, it’s estimated that 463 exabytes will be created each day globally.

Storing all this data could quickly become impractical using conventional silicon technology, but DNA could hold the answer. For a start, its information density is millions of times better than conventional hard drives, with a single gram of DNA able to store up to 215 million gigabytes.

It’s also highly stable if properly stored. In 2017, researchers were able to extract the full genome of an extinct horse species from 700,000 years ago. Learning to store and manipulate data using the same language as nature could also open the door to a host of new capabilities in biotechnology.

The main complication lies in finding a way to interface the digital world of computers and data with the biochemical world of genetics. At present this relies on synthesizing DNA in the lab, and while costs are falling rapidly, this is still a complicated and expensive business. Once synthesized, the sequences then have to be carefully stored in vitro until they’re ready to be accessed again, or they can be spliced into living cells using CRISPR gene editing technology.

Now though, researchers from Columbia University have demonstrated a new approach that can directly convert digital electronic signals into genetic data stored in the genomes of living cells. That could lead to a host of applications both for data storage and beyond, says Harris Wang, who led the research published in Nature Chemical Biology.

(Read more)

You may also like

There is something wrong with Feed URL