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The hackers teaching old DNA sequencers new tricks

In a basement storeroom at Stanford University in California, the guts of a dozen DNA sequencers have been uncovered – cameras and lasers, optics and fluid controllers worth hundreds of thousands of dollars, all cleaned up with a late-model, next-generation Illumina DNA sequencer is. Called GAIIx. On the floor, the shell of an old instrument sits empty, raised like a dead body. “I sound like a hoarder,” says Stanford biophysicist William Greenleaf.

But over the past 6 years, the collection has fueled an effort that has involved nearly half of Greenleaf’s 18-member lab team. While most researchers use DNA sequencers to sequence, well, DNA, Greenleaf’s team is one of a small number that has repurposed the tools for an entirely different goal: macromolecular interactions and proteins on a larger scale from RNA and protein. Folding for enzyme function to study nucleic-acid biochemistry.

“It’s a revolutionary technology,” says Stanford biochemist Dan Herschlag, who uses it to study the interactions between RNA and other molecules.

This provides “deep and comprehensive quantitative information,” he says, “which allows researchers to build more accurate biophysical and cellular models for molecular interactions, and which leads to a truly predictive understanding of biological systems.” An important step in that direction”.

Broadly speaking, the work demonstrates what is possible when scientists look at the guts of their hardware – evidence that the device isn’t necessarily because it’s old or out of date.

But there’s a reason this kind of technology development is called the bleeding edge: Things often go wrong. Sarah Denny, a biophysicist who graduated from Greenleaf’s lab this year, asked whether her devices offer ‘plug-and-play’ simplicity.

“Many times after you’ve done an experiment, something will break and you have to figure out how to make it work again,” she says. But considering the amount of data she could extract, the reward was well worth the pain. In Denny’s case, his team gained a better understanding of RNA folding. Such is life, do it in yourself.

Biophysics on a chip

When GAIIx dropped in 2008, it was a hot commodity. Some sequencing centers had dozens of devices, costing around US$600,000; In 1 week, a machine can pull out the 30 billion letter bases that make up DNA. But by 2011, when Greenleaf set up its lab at Stanford, the industry rapidly shifted to hardware—such as the Illumina HiSeq 2000—that was more efficient and user-friendly, and people were giving their old machines away. “They’re basically big paperweights,” Greenleaf says.

Illumina sequencers automate a sequencing-by-synthesis process. A DNA library is randomly arranged on a device called a flow cell, and stretched in place to form small groups of approximately 1,000 molecules, each representing a single piece of genetic information.

The building blocks of DNA, or nucleotides, are then transferred onto a chip, each with a unique fluorescent signature and a reversible chemical modification.

This process ensures that only one nucleotide can be added to each cluster. The sequencer then images the array, and ‘calls’, or reads, based on the color at each position, which base was added. Then the modification is removed, and the process is repeated, allowing the entire sequence to be identified by base.

At their core, these devices are high-end microscopes with liquid handlers that help move reagents around. Some of their components – notably cameras, lasers and moving stages – can cost thousands of dollars. In 2009, Christopher Burge, an RNA biologist at the Massachusetts Institute of Technology in Cambridge, realized that it might be possible to rearrange that hardware to do something else.

Basics of hacking

“GAII is basically a pumping system that pumps things onto a flow cell and then to a fancy imaging system,” Burge says. “We realized that, well, maybe you can pump other things onto the flow cell.”

This, he says, is because GAIIx was an ‘open system’, controlled using editable configuration files called recipes and loaded with reagents that could be replaced by simply substituting one tube for another.

Could have done. From the inside, the machine was evenly spaced, with off-the-shelf, third-party components held together with cable ties. “In retrospect, this looks like a high-school science project,” says Gary Schroth, a biochemist who directs the genomics-applications group at Illumina in San Diego, Calif., and who in his early studies Collaborated with Burge.

The new Illumina equipment, by contrast, is more polished with custom hardware, hardwired control software and barcoded reagents – features that improve the user experience but deter hacking.

Jacob Tome John Liss, a molecular biologist at Cornell University in Ithaca, New York.

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