jJust under your skin lie entire watery worlds, where trillions of cells spark, throb, writhe, and secrete, performing all the intricate tasks of keeping you alive. They all share the same genetic code. But what they do with it is the difference between a neuron and a contracting muscle fiber.
About a decade ago, a group of scientists began taking a cellular census of every tissue in the human body to find out which cells actually live there, using a powerful new technology called single-cell RNA sequencing. It illuminates which parts of the genome a cell uses to perform its unique task. The international collaborative effort, called the Human Cell Atlas, has since grown to include more than 2,000 researchers from 83 countries. And on Thursday, they reported a major feat: creating detailed maps of more than a million cells in 33 organs.
Landmark tissue atlases were published in four studies in Science. “You can think of it like a Google Maps of the human body,” Sarah Teichmann, head of cell genetics at the Wellcome Sanger Institute and co-chair of the Human Cell Atlas, told reporters Tuesday.
In one study, his team sequenced the RNA of 330,000 individual immune cells from throughout the adult body, and in another, they cataloged immune cell development in prenatal tissues. They found that as infection-fighting T cells develop, they learn as much by talking to each other as they do from their parent’s tissues. Cracking this molecular code could allow researchers to better engineer T cells to do things like fight cancer. “The insights have implications for therapies that enhance or suppress an immune response to fight disease and for designing vaccines,” Teichmann said.
A third article, led by co-chairman Aviv Regev, one of the pioneers of single-cell sequencing who now heads R&D at Genentech, described how Broad Institute researchers created a cross-tissue atlas of 200,000 cells from frozen tissues . Using machine learning, they scanned the atlas to identify cell types associated with 8,000 genetic diseases. “We hope that by using maps like these, we can better understand the precise place in the body where the disease arises,” Regev told reporters. “That would allow us to develop more precise diagnoses and new treatments.”
Stephen Quake, president of the Chan Zuckerberg Biohub Network and a member of the Human Cell Atlas organizing committee, contributed an update from the Tabula Sapiens consortium, which unlike many of the other efforts, is collecting cell sequences from a single donor. So far, it provides a portrait of almost 500,000 cells from 24 organs of 15 people who have recently died.
STAT spoke with Quake about the science milestone and what’s next. Excerpts from the conversation are below, lightly edited for clarity.
The consortium has now mapped more than a million individual cells in 33 organs, a significant feat, a first draft, if you will, of the Human Cell Atlas. How you feel?
This is a great moment. Around 2011, 2012, there were four or five people in different corners of the world saying that we should build a cell atlas of the whole organism. So it’s good to see that now it’s all coming to fruition. But yeah, it’s absolutely a first draft. In that way, there is a good analogy with the Human Genome Project.
When the first human genome was published, it was a draft genome. There were all sorts of gaps and things missing, but it was incredibly helpful nonetheless. Now, 20 years later, we are seeing the first truly finished human genomes from telomere to telomere, which are adding value. And I think of these cell atlases in the same way. These are erasers. We’re not saying we’ve found every type of cell in the human body, or even every tissue, but it’s going to be very helpful.
How are researchers beginning to use them?
I have a colleague who wants to use it to study brain cancer. He was finding potential drug targets and wanted to look elsewhere in the body for unexpected toxicity. And I think a lot of people have been taking that approach. They have a drug target of interest for a disease and they want to know where else that protein is expressed (what other types of cells, what other tissues) because making a drug against that target can affect other tissues besides the one you want.
Another good example is an article that one of my students, Sevahn Vorperian, has already published in which he used the atlas to understand something about liquid biopsies. He realized that he could use Tabula Sapiens to decompose the cell-free transcriptome and the cell types of origin. And that has generated a lot of interest in the diagnostic community.
With the idea that you could look at the signatures of disease that come from the RNA circulating in someone’s blood and trace it back to the specific cells where that dysfunction occurs?
The Human Cell Atlas consortium has taken a kind of one tissue at a time approach, with different research groups working on their tissue of expertise. How is Tabula Sapiens different?
What we brought to the table was to figure out how to do these multi-organ experiments. Which has been a great collaboration in its own right. You know, the idea of taking all these organs from a single donor has never been done before. And because these are living donors, we really have to get everyone in there, as these people are being operated on. [The Tabula Sapiens project worked with an organ procurement organization to preserve tissues while surgeons were harvesting organs for donation.] And that is a great management challenge. Personally, it has been a big boost for me because I always run a small lab. I had to learn to do Big Science.
But a big advantage of looking at tissues from the same person is that you can control for all sorts of things, like genetic background, epigenetic effects, environmental exposure. That allowed us to do things like study joints. Each gene has different pieces that can be spliced in or out, depending on which piece is used. What has not been well understood is whether splicing is dependent on cell type. And we were able to map that here to find some very interesting variations in splice usage based on cell type and we discovered a bunch of new splices that have never been seen before.
The Human Cell Atlas is a successor to the Human Genome Project, which you mentioned earlier. How do you think you are carrying forward the tradition of Big Science as it was defined at the time, and how are you charting a new legacy?
It definitely shares some aspects of Big Science. It requires a lot of coordination between many groups, many people around the world. And you’re tackling a problem that really couldn’t be solved any other way, because we need all that expertise and diverse input. But it’s also different in a couple of ways.
It is more collegiate. The Human Genome Project was kind of famously acerbic.
What do you attribute that to?
It is probably a function of personalities. The genome project had some big personalities involved who really didn’t get along. Aviv and Sarah, the co-chairs of this project, and I have a much better relationship. Furthermore, in this case there is no private effort, so there is no public-private competition.
Another difference is the cost. The first human genome cost 3,000 million dollars. We made a strategic decision to wait until the technologies became a bit more affordable. If the genome project had waited even five years, it would have been much cheaper. I have spoken with Craig Venter [who led the private effort to sequence the human genome] about this, and I asked him if it was worth doing it before. “Oh, it was definitely worth it. We learned a lot,” he told her. I’m not sure I agree with that assessment. But all of the Human Cell Atlas teams have been on the same page about doing this when we felt the cost-benefit ratio was right.
And that’s important because I think what we’re trying to do is much more difficult than sequencing a genome. And the reason for that is that sequencing a genome is this incredibly well-defined chemical problem. Here is a test tube with some chemicals. Tell me what the chemicals are: the chemical is the DNA molecule. While understanding the nature of these cells is much more complicated. It’s not a chemical problem, it’s a biological problem. And it is more difficult to abstract it to a simple measure.
Because what you’re really doing is redefining the parameters of what it means to be this cell type or that cell type. It’s not just what a cell looks like or where it lives, but these genetic programs that each one is running. So how do you decide how far to dig? Where do you set these limits?
That’s a good question, and it’s been open for a long time. What is the difference between a cell state and a cell identity? From my perspective, I don’t think it’s a settled question yet. The community still struggles with it. We are still analyzing what the fundamental nature of these objects is.