DNA ‘printing press’ could quickly store mountains of data
Inspired by ancient invention of movable type, researchers use blocks of DNA to dramatically increase writing speed
The invention of the printing press and movable type—metal letters that can be arranged and inked—led to the Renaissance and an explosion of information that continues to this day. Now, researchers report applying the concept of movable type at the molecular level to dramatically speed up the ability to encode data in strands of DNA, an incredibly high-density medium for storing information. Although only demonstrated in the lab so far, the new approach, reported today in Nature, could energize the emerging DNA data storage industry by making it cost effective to archive vital information for decades and beyond, independent researchers say.
“It’s a really nice proof of concept and a significant improvement over previous DNA data storage approaches,” says Kun Zhang, a genomics expert at Altos Labs. “It gets around a barrier of DNA data storage that requires synthesizing DNA from scratch,” adds Jeff Nivala, a biophysicist at the University of Washington.
The allure of DNA data storage is immense: A single gram of DNA can store up to 215 petabytes of data, enough to store 10 million hours of high-definition video. At that rate, a few pickup trucks worth of DNA could store all the data humanity has ever recorded. And unlike conventional electronic hard drives, which degrade in years or decades, DNA can last for millennia.
Moreover, reading out data encoded in DNA’s four-letter alphabet is straightforward and relatively fast these days with DNA sequencing machines. The problem is writing the data, which typically requires synthesizing custom strands of DNA one letter at a time. Today’s fastest DNA writers can synthesize about 320 million bytes of DNA data per day. At this speed, writing a single gram’s worth of DNA would take nearly 2 million years. “It’s unaffordable compared to hard drives because the writing speed is quite slow,” says Long Qian, a computational biologist at Peking University.
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