Science Friday - 3,000 Types Of Brain Cells Categorized In Massive Brain Cell Atlas

Episode Date: January 18, 2024

In October 2023, an international group of scientists released an impressively detailed cell atlas of the human brain, published in 21 papers in the journals Science, Science Advances and Science Translational Medicine.The human brain has roughly 171 billion cells, which makes it a herculean task to categorize them all. Scientists collected samples from different parts of the brain and have identified 3,000 different types of cells. Each cell contains thousands of genes and each cell type only expresses a small fraction of those. Cataloging cells by their gene expressions, paves the way for scientists to tailor disease treatments to target only the affected cells. This human brain cell atlas is only the first draft, but it could signal a paradigm shift in how we understand and treat neurological diseases.Ira talks with one of the researchers who helped put together the cell atlas, Dr. Ed Lein, senior investigator at the Allen Institute for Brain Science, and takes listener calls.Transcripts for each segment will be available the week after the show airs on sciencefriday.com. Subscribe to this podcast. Plus, to stay updated on all things science, sign up for Science Friday's newsletters.

We're one step closer to understanding the complexity of the human brain. Instead of characterizing cells on the basis of their shape or who they connect with or their firing properties, instead one can characterize them on the basis of the sets of genes that they use. I'm SciFRI producer Shoshana Buxbaum. It's Thursday, January 18th, and we've got our brain cells firing on all cylinders because today is Science Friday. Late last year, scientists released an impressively deep, detailed map of human brain cells. Considering the human brain has a little over 170 billion cells, it's a monumental task made possible by an international group of scientists. They've identified

3,000 different types of cells. Ira Flato and sci-fi producer Kathleen Davis talk with one of the scientists who worked on the project and take listener calls. Dr. Ed Lean, senior investigator at the Allen Institute for Brain Science based in Seattle. Welcome to Science Friday. Good afternoon. Thank you for having me. Dr. Lean, just how big in advance is this cell atlas for the field of neuroscience? Are we talking about a human genome project level paradigm shift here? Yes, I believe that's a really good analogy for the events made through this work as the first installment, really. One of the problems with neuroscience is the extreme complexity of the brain. And it's just very different.

to study for the human brain, the scale and the inaccessibility of studying the brain are serious barriers. And so we really needed a technology breakthrough to be able to handle this complexity. And the breakthrough, very appropriate for the genome reference, has actually come from the field of genomics, where instead of characterizing cells on the basis of their shape or who they connect with or their firing properties, instead one can characterize them on the basis of the sets of genes that they use. So every cell in the body has all genes in their DNA, but any given cell only uses a subset of those genes. And that molecular fingerprint of a cell is a really strong way to be able to classify cells. And so as the field of genomics has events, what's happened is that

sequencing has become cheaper and cheaper and cheaper, and it's been miniaturized to be able to analyze individual cells, and now it's possible to analyze all the genes being actively used by millions of cells. And this now lets you take a much broader scope of trying to categorize the complexity of the brain. And so this first installment was really trying to get a first draft by sampling about 100 regions of the brain, and then ask how many types of cells are there. And, you know, I think for really over a century, we've understood that the complexity is high, quite this high. You know, there are thousands of types of cells. So 3,000, as you mentioned here, even since the time of that publication, a comprehensive analysis of the smaller mouse brain has come out

describing 5,000 cell types. Dr. Lean, we're going to get into that after the break. We have to take a break. So stay with it. So, Dr. Lean, there are, as you were saying before the break, there are 171 billion cells in the human brain. How do you possibly go about categorizing all of Yeah, so it's true that there are that many cells, and about half of those are neurons, but they don't come in that many different types of cells. And so the key advance here is to be able to categorize the cells into groups of cells that live in different parts of the brain that have different properties and make a catalog of these and a map of these.

And so these new technologies, as I was describing, are allowing us to create these. so-called cell atlases. And on the one hand, this is a classification of the types, where we can define how many types of cells there are, what their relative proportions are in different parts of the brain. We can describe their spatial organization now, how they're organized in local areas and also globally in the three-dimensional structure of the brain

and begin to characterize in their properties and their function. And so in many ways, you know, this is really like the genome project in the sense of the genome characterized all. of the genes and their locations on the chromosomes, here we're characterizing all the cells in their locations and eventually their function in the brain. One of the surprises of the Human Genome Project was just about how many genes there were, a surprising less number than people thought. Are you being surprised by how many different types of cells you're finding in the brain?

Most definitely. These sort of molecular approaches to classify cells are revealing a whole different level of complexity, probably, you know, an order of magnitude more than we had realized before. And importantly, one or two orders of magnitude, so 10 to 100 times more complex than any other organ in the body. I was just going to ask, I mean, how does this compare to other parts of our body? I can't imagine that, like our biceps, for example, have 3,000 different types of cells. No, nowhere near as many types of cells. So the complexity is really very high. But importantly, actually, these techniques by using genes as the way to define

cells, this technology can be applied to any organ system. And so in addition to the brain, in parallel, there are efforts happening in these same technologies in every other organ system, and even being compiled, for example, in a project called the Human Cell Atlas to try to put all of this together.

So we finally have a common language to talk about the basic units of life, the cells that make up every organ in the body. But the complexity factor is much higher in the brain. How many new kinds of brain cells have you discovered that we didn't know existed? And the second part would be, how many more do you think are out there? Yes, so these are somewhat difficult questions to answer,

because we have a new way of looking at these cells. And so when we describe 3,000 types of cells, in those parts of the brain that we understand well, we can see that this actually maps very well to what was known before, but adds another level of resolution on this. And so maybe, you know, you might have thought that there were 50 types of cells in the part of the neocortex. You know, now we see there may be 150 types of cells.

But in other parts of the brain that we don't understand as well, you know, a lot of this is brand new knowledge. And so we don't really know what this means yet. But we have the framework now where investigators across the whole community can come and begin to add information to this. And so, again, very much like the genome where first the genes, map and then function was laid on top of that, this is what's going to happen now. Now that we've defined a blueprint of the cell types, now we can start to understand what they

are and what they do. Great. That's great to hear. Allison in Erie, Pennsylvania, welcome to Science Friday. I'm inspired by the limits of things. I know Einstein saw things with thought experiments, and lately I've been appreciating how we can go farther when we acknowledge what we don't. My metaphor to start is just if we smash open a radio, of course, the machine parts don't necessarily give us all of the answers as to, you know, the content that's coming through the radio, for example.

I just wondered what this inspires in you and you're thinking about neuroscience. And I know we're talking about the cells, but what are the implications for you? I've heard that this is paradigm shift. I'm just curious what this inspires you, whatever you found, how it's inspiring your creativity in the space in neuroscience, what it's inspiring you to think about or consider. And it might be a sensitive question because you're a scientist, so often you're not going to talk about things until they're proven, but I kind of wanted to challenge you to talk about that. What are some things that this inspires you to think about or even consider? Again, not to challenge the science of what's proven or not proven, but I know it's important to be creative in the space,

and metaphors help me a lot. But, yeah, it's exciting what we don't know and just curious what it's inspiring you to consider or think about. Good question. Let's get the answer to that. What do you say to that? Yes, that's a very interesting question. So, first of all, you know,

let me acknowledge that this is really a reductionist approach to the brain. So in your analogy of a radio, we take it, we deconstruct its parts and we try to understand its parts. And very much like that analogy, this is just the beginning, right? So now we know that the brain, the neurons of the brain form circuits, complicated circuits, which are by definition the connections between the different kinds of cells. And so what this really sets the stage for is beginning to take the next step. You know, if we don't understand the basic components, we can't understand how they connect together. So, but now that we understand that part of it, we can move to the next stage.

Now, even that may not be the end of the day. You know, there may be software sort of on top of that, that it actually dictates the function of this. So, you know, I think that this is really just the beginning, but it is an essential component of the process here and one that we haven't had before. If you don't understand the basic building blocks, you can't understand how it all fits together to work. And, you know, I think that what's important to consider here is that we've had this sort of dearth of understanding of the fine, detailed structure of the brain, and that's dramatically hampered our understanding of disease. And this type of resource can now allow us to bring this level of resolution to understanding exactly what happens in disease. And so to give a concrete example and something I'm quite passionate about is with this information,

we can think of cells as things that are affected in disease that may in fact be targets for treatment of disease. So we have another project focused on Alzheimer's disease called the Seattle Alzheimer's Disease Brain Cell Outlis or CAD, where the idea is let's now look at the brain of individuals that have Alzheimer's disease and try to understand what kinds of cells are affected in disease. And we can map against this reference and then ask questions about what the real basis of disease is. Whereas in the past, one would think about pathological proteins, plaques and tangles that everyone knows about, that just haven't worked as a way of treating disease. And what we find is that we can find all of these types of cells and individuals with disease,

we can then see that certain types of cells are differentially affected or vulnerable. And so, you know, this is a kind of a different way of thinking of things. It's thinking of the brain as a cellular organ where specific components do different things. They're differentially affected by disease, and they become actual targets themselves. And something else that comes from these atlases is the ability to develop tools to target particular cells and potentially deliver genetic therapies to them. So I view this as it's not a stamp collecting exercise. This is really foundational work that defines the system so that we can use that knowledge to then understand and treat disease.

So how would that work practically if you are trying to treat something like Alzheimer's? I mean, how would that treatment potentially work with this knowledge? Yeah. So Alzheimer's is maybe a difficult example. It happens to be one that I know a lot about. But let me give a more easy example, perhaps, of epilepsy. So epilepsy is, of course, an imbalance of excitation and inhibition, and often affects the inhibitory cells. So there's not enough inhibition, and you get runaway excitation. That's a seizure activity.

One of the things that's come out of this cell atlas work is that we can not only understand what genes are active in what cells, but how they're regulated to be active only in those cells. So we can identify the regulatory regions of the genome that are responsible for turning on a gene and only a certain kind of cell. That regulatory element can actually be put into a virus as a means of gene delivery that commonly used in gene therapies now, such as adenosecated virus. These regulatory domains can be put in to turn on expression, of a particular gene, say a gene replacement of a genetic epilepsy. And so you can infect cells in people and deliver a gene just to the right kinds of cells

that may be able to correct those seizure phenotypes. And this is just one example. Many types of brain diseases will affect specific kinds of cells. And what I'm trying to convey is we can now harness this information of this descriptive Atlas to build a tool to target the right cell type and hopefully correct a genetic deficiency of some sort without having side effects or off target effects that happen by hitting the wrong kinds of cells. Really interesting technology.

Let's go to the phones to Rye in Houston. Hi, Rai. Yeah, how are you, Ira? Thanks for taking my call. Yeah, you're welcome. Go ahead. Yeah, so my question is, has there been any study of the connection between the gut and the brain. And is there any genomic similarities that might, you know, create a relationship

or suggest one? Our microbiome, our favorite topic here on Science Friday. Good question. Yeah, that is an excellent question that I'm afraid I'm somewhat ill-equipped to answer. But let me just say that I think that the data are now becoming available to allow that kind of question to be asked. For example, in this human cell outlets that I was mentioning earlier, there are efforts to profile all the cells in the gut and the immune system. And so by virtue of using these same types of technologies to look at genetic similarities among different kinds of cells, anywhere in the body, it will be possible to do this. And we can begin to try to see where these functional links may be.

But I have to speak in generalities because I'm not aware of a study that's done that to be. I mean, sometimes big projects like this raise more questions than they answer. How much of this project helped you better understand the brain versus just opened up more questions? Oh, this is a huge advance in understanding the brain. You know, as I mentioned sort of before, you know, this really forms a scaffold. It forms a cellular framework. But at the moment, these are cells that are defined by genes with these kinds of methods. And that's a very powerful way of understanding a cell because the set of genes that are selectively used by a cell.

cell are the genes that are responsible for the properties of those cells. So this is much more information than simply saying, you know, here's the shape of a cell. And we're going to categorize based on the shapes. You can't do very much with that information. But if you have all of the genes being asked, now you can use this in a thousand different ways, what drugs might act on molecules that are expressed only in certain kinds of cells, for example. What about cells that are not actually in the brain. For example, I've heard that your retina is really part of your brain. We have neurons that go through our spinal cord. We talked about the gut a little bit, solar plexus. Will those cells be included in this catalog?

So at the moment, this particular effort is focused on the central nervous system, minus the retina. So the retina is actually part of the central nervous system, but it's not being included. However, it does profile or characterize any kind of cell that's present in the brain, whether or not this is an actual brain cell or a circulating cell in the vascularature, for example. And so actually, one of the things to come out of this is that there's a greater diversity of cells that aren't neurons that are in the brain as well. And so it really does give you a very comprehensive view of the overall makeup of the organ.

And I'm sorry, I've neglected to complete my answer on the last days about whether we understand the brain. With this scaffold, now you can have a very targeted approach to start to characterize the properties of all these cells. So the gene expression part of it is very informative, but the next stage is what do these cells look like? Who do they connect to? What are their firing properties?

What are their functions? And so now that you are able to pin identities on these cells, you can make very targeted inquiries to start to annotate this or interpret your functional experiments in light of what kinds of cells are actually active in a behavior. If you could, I'm going to give you my blank check, if you had an enormous amount of money to do or buy or create some kind of tool to study what you want to know, what would it be?

I think that I would actually invest in the utility of creating these tools to target particular kinds of cells that can help to understand the brain and treat disease. I think there's an enormous new field of precision medicine that's being opened up by this information. And this has already actually become, it has become a huge priority for the NIH that has investing in another program

as part of its brain initiative that's called the armamentarium or sort of an arsenal of tools to be able to genetically target and manipulate different kinds of cells in the nervous system. I think this is going to be enormously important for medicine,

we now get a cellular understanding of different diseases and can actually target and try to correct those diseases. Wow. Wow. This is certainly exciting for personalized medicine. Thank you, Dr. Aline, for the work that you do. Thank you very much. That's it for today. A lot of folks help make the show happen, including Jordan Smudjik, Charles Bergquist, George Harper, John Dancosky, and many more. Tomorrow, a roundup of the top science news of the week. I'm SciFar. producer Shoshana Bucksbaum. Catch you next time.