Biotechnologist Andrew Adey developed a high-throughput method for mapping the genomes of single cells. The advance, reported in January, allows for the identification of diverse cell populations in tumours, and so paves a path towards precision medicine. To develop it, Adey, now at Oregon Health & Science University in Portland, relied on HeLa cells, a prolific cancer-cell line biopsied in the 1950s from Henrietta Lacks, who had cervical cancer, and used widely in biomedical research without her consent.
How has single-cell biology advanced?
In the mid-2000s, next-generation sequencing was just starting, so today's version of single-cell biology was non-existent. Today, researchers can look at genome-wide properties or other aspects of single cells.
How did you use HeLa cells?
I knew nothing about the history of HeLa, just that it was a cancer-cell control line that grew really well. We wanted to understand how different copies of chromosomes influence cells. Once we developed technology to do this in normal cells, we set out to see how those copies act in cancer cells, and so applied it to HeLa. We learned more about HeLa — notably, that multiple copies of a genome can act differently — and worked out the genomic changes that enable an aggressive cancer to reproduce so readily.
What was your role in the privacy debate over publishing HeLa sequence information?
As we were readying a paper in 2013 (207–211; 2013), we didn't know how we were going to publish genetic information that could have consequences for Lacks's descendants. Ultimately, the US National Institutes of Health reached an agreement with the Lacks family that accompanied our paper, and that granted researchers access to the cells while maintaining the Lacks's privacy. HeLa is a unique case — one not only at the forefront of medical advances but also about the ethical informed consent that is crucial to medical practice. et al. Nature 500,
Can you explain the technique put forth in your January paper?
Initially, our platform could fully sequence only the portion of the genome that regulates gene expression in single cells (302–308; 2017). We wanted to progress to whole-genome sequencing from single cells. But when you target regulatory elements, you typically have access to only 1–4 et al. Nature Meth. 14, % of the genome. We had to work out how to free up the DNA to convert the entire genome into sequenceable molecules.
What were the main obstacles?
At one point, it seemed like we were playing 'whack-a-mole'. Every time we altered one fixed property of the protocol, something else that had been working fine would stop. It was challenging, because the genome is packed nicely into nuclei. We needed to destroy the proteins that packaged the DNA inside the nucleus, without destroying everything else. Most of the time, everything would just explode and we'd lose the ability to look at single cells.
We've already improved our method from what we published in January. It's even more reproducible, and we can get more data from single cells. Half of my lab does technology development; the other half applies those methods to answer questions of interest. This method was the first step to examining other aspects at the single-cell level. We're now using these technologies to explore cell identity. For example, how does a cell respond when treated by a cancer drug?
How will your method affect cancer treatment?
With a single-cell focus, we can start to profile an individual's tumour and identify molecularly distinct subpopulations in a tumour. If we can then profile large cohorts and tumours at the single-cell level, we can learn how certain subpopulations will respond to specific drugs to better home in on effective treatments.
This interview has been edited for length and clarity.