Human Cell Atlas

26 February 2018

Interview with

Sarah Teichman, Sanger Institute

One of the largest biological endeavours of recent years was the human genome project that mapped and sequenced all 3 billion of the genetic letters in our DNA code. Now scientists are embarking on an even more ambitious initiative. Speaking with Chris Smith, the Sanger Institute's Sarah Teichman...

Sarah - We're setting out the goal of mapping all cells in the human body, through an international effort that involves cell biologists genomics experts computational biologists and the medical community to collaborate on creating an atlas of the human body at the level of individual cells.

Chris - I'm gobsmacked, Sarah, this doesn't exist already. I mean, cell biology has a history going back hundreds of years. So why are we only doing this now?

Sarah - So it's really thanks to high resolution and high throughput technologies that have been evolving over the past five to ten years that we can now see cells in terms of their entire genome's transcriptomes at the level of tens and hundreds of thousands of cells at a time. And so what I'm talking about in a nutshell is the resolution revolution in genomics. This coupled with also spatial methods that are microscopy based to map cells in their two and three-dimensional context has meant that we can now grab hold of cells at a completely different level.

Chris - It's almost like multi-dimensional then this atlas, in the sense that yes, you can say "that's what a liver cell looks like," but one can zoom inside the liver cell and say "and this is what it's transcribing. That's these are the proteins it's making."

Sarah - That's right. So you're basically describing the entire molecular fingerprint of that cell rather than the morphology of the cell the way we've been doing with conventional microscopy methods.

Chris -  Sounds like a huge undertaking though because it's not as simple as just saying "I'm going to take a snapshot of an adult now," because obviously, cells go through phases during the day, they go through phases during the week, an immune cell can turn from one type of cell to a completely different type of cell as it matures for example, and we'll start life as an egg which then turns into all these different cell types so, how were you going to do this?

Sarah - That's a great question, and it really gets the bottom of asking what is a cell type or what is a cell state. And as you mentioned there are, sort of, developmental dynamics so the human cell atlas will encompass human development, and also at different ages in the human lifespan. Although in the short term the aim is to build a first reference initially so this is a project that we envision will run for five to ten-year term.

Chris - I was going to say it does sound like it's going to be an extremely long term undertaking. It's huge, and potentially bigger than the human genome project because you're going into all these different dimensions?

Sarah - That's right. It's also more complex at the level of the samples. So basically acquiring tissues from different organs in the body and as you said different developmental stages. That sample acquisition part is certainly more complex than the Human Genome Project.

Chris - I suppose is some of the challenges that had to be surmounted for the Human Genome Project, 13 years ago when it finished. Before that, obviously, when it was running they must be informing or helping with this because marshaling massive amounts of data was a big challenge then and it helped to actually change the world in the way that we process data so you must be to build on some of that?

Sarah - Yes. I mean the human genome project is certainly a template for collaborative efforts in biology and for building a resource. And it's also as you're saying, the data challenge is similar, although I'd say we're in a new era of big data and biology now where we really are talking serious big data. It's not just a software engineering and database challenge, it also becomes a data mining and statistical and computational challenge, with sort of very sophisticated machine learning and artificial intelligence methods that we're developing to make sense of the data and to mine the data and to get the biological knowledge out of it.

Chris - This is a quite provocative question which I want to put to you because I think there'll be people listening to this who will think "well that sounds wonderful but I don't understand why it matters" why does having this cell atlas that tells us what's where in the body but in many dimensions at many levels what's going on in those cells how they're changing and so why does this help us do science better.

Sarah - To me there is a sort of curiosity argument, we want to know what's inside our body and how it works. But there is also a very clear relevance for medicine in the sense of new diagnostics that can be developed based on markers and molecular patterns that we find in the healthy reference body immediately it provides a template for saying okay what are the cell states that we need to probe that are indicators of disease tumour mapping learning about cancer cell states essentially having the healthy reference atlas is a very obvious kind of framework for the tumour biology. So there's the basic curiosity about ourselves. But there's also medical applications.

Chris - And just in case anyone isn't completely across how massive this undertaking is, put some numbers on it for us. How many cell types? How many different ways of looking at those cell types are you going to have to go across? I mean what's the scale of this project?

Sarah - Well we don't really know how many cell types there are, conventional estimates on Wikipedia and so on say there are 200-300 cell types but we're seeing thousands essentially now with these high-resolution technologies. There are 37 trillion cells, probably, in the human body and we're not going to sequence all of them but by sampling in a strategic way from different tissues in the body, we hope to learn about the vast majority of the cell space that's out there. My estimate is that we will sequence billions of cells and we will discover thousands of cell states over the next five years or so.


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