The go-to sequencing machine with very strange results
The Go-To Gene Sequencing Machine With Very Strange Results
When biologist Rahul Sinha started his first independent research project at Stanford last January, he had a single-minded goal. He had just completed his post-doc in the lab of Irv Weissman, the Stanford biologist who helped launch the field of stem cells. They study the stem cells that form blood---the bone marrow-derived cells that help cancer patients recover after chemotherapy destroys their immune systems. Sinha wanted to find a true blood stem cell: one that hadn’t already started turning into a red blood cell, or a platelet, or an immune cell. A universal blood stem cell could reveal the path to all its progeny, helping scientists custom-make any blood cell a patient needed.For decades, researchers had been using molecular techniques to narrow their search, but that approach had stagnated. To find his unicorn, Sinha would have to dig deeper, into the proteins that would eventually define the cells. That would require him to sequence the RNA of thousands of seemingly identical stem cells from a collection Weissman had built. And like most geneticists working today, the machine he turned to was from Illumina: the San Diego-based company whose products sequence 90 percent of all genetic data.But instead of a true stem cell, Sinha stumbled onto something very different. Inconsistent results led him to identify an issue with the underlying operations of Illumina’s newer sequencers---an issue that could have contaminated the results of similar high-sensitivity data produced on the machines in the last two years.Sinha’s research used Illumina’s HiSeq 4000, a fast system that cuts costs by sequencing hundreds of samples at a time. It also uses a proprietary technology, called ExAmp, that makes genetic signals clearer, even very faint ones. That makes it possible to sequence very small amounts of genetic material---like, say, a single cell’s worth. For those reasons, the HiSeq 4000 is a workhorse for geneticists who sequence in bulk. Scientists who manage the sequencing core facilities for the University of California system estimate that the system, introduced in January 2015, handles 90 percent of its sequencing requests.Sinha and other academic researchers aren’t the only ones who need that kind of needle-in-a-haystack sensitivity. Precision medicine---like spotting a piece of tumor DNA in a drop of blood or finding a rare variant among the 3 billion base pairs in the human genome1---also requires high-resolution sequencing. Clinical researchers and biotech start-ups that need that kind of resolving power are increasingly using Illumina’s ExAmp chemistry and the machines that employ it, including its newest line, the NovaSeq.Illumina itself is heavily investing in its sequencers’ medical applications. In the last few years, the biotech behemoth has acquired, invested in, partnered with, and spun out companies that can use its aggressively-patented sequencing tech to address disease. At an unveiling in January 2017, Illumina’s CEO Francis deSouza said that Grail, the company’s liquid cancer biopsy spinout, would soon be one of Illumina’s biggest customers. Grail and others are using the sensitive machines to search for shreds of tumor DNA in blood samples---a screening tool that could lead to earlier detection and better patient outcomes. At the time of the announcement, Illumina had 49 NovaSeq orders, and since then machines have been installed in medical centers and precision medicine biotech companies around the world. Getting these sequences right is more than just a matter of academic integrity: Money and medical progress are at stake.Biological BarcodesSinha started his search with a library. Not like one full of paper books---this one is built on a small glass plate with depressions, called wells, that separate genetic material from different cells. After converting his cells’ RNA into DNA and chopping it into small pieces, Sinha tagged each cell’s DNA fragments with a row identifier and a column identifier, coordinates that would trace each fragment back to the well (and therefore the cell) it came from. Once all the fragments were barcoded, he dumped them into a single test tube, washed away the extra barcode-containing molecules, and sequenced them. Like a librarian would use a Dewey Decimal number to return books to their shelves, Sinha would use the barcodes to match each piece of sequenced DNA to the cell it belonged to.Sinha got his results in August, and they looked amazing. Gene expression had revealed 41 distinct subpopulations of blood-forming stem cells, including a group of cells that seemed capable of transitioning into any of the other ones---his true stem cell. “It fit with every hypothesis we had ever generated in the past 10 years,” says Sinha. “It was really exciting stuff.” That fall, the group started preparing their work for publication.But meanwhile, Stanford grad students using the same Illumina machines to do similar work were beginning to warn each other to prepare their libraries more carefully. It seemed there was an uptick in tales of cross-contamination, genetic material from one sample jumping into another.