Dr. Seth Grant (3:18)

Great. Nice to be here, Ginger. Thank you for having me.

Dr. Ginger Campbell (3:21)

Okay, so today we are going to talk about the results of one of your recent papers that actually builds on the work we talked about the last time you were on back in 2020, which was episode 176. But before we do, I want to talk a little bit about why molecular biology has become such an important tool in neuroscience.

Dr. Seth Grant (3:45)

It's really quite a fascinating question and I've had the great good fortune to get involved with the molecular biology revolution in neuroscience really at a very early stage. And back in the 1980s, I was a postdoc at Cold Spring Harbor Laboratory working on oncogenes. And that was an incredibly exciting period of time. The first cancer genes were discovered in the 1980s. And I went to Cold Spring harbor and worked with Douglas Hanahan on using transgenic mice, which was also a brand new thing, to see if cancer gene could create cancer by themselves in mice. Now this was a wonderful area of molecular biology because oncogenes and cancer genes really transformed completely our understanding of cancer. And we know cancer is a genetic or genomic disorder caused by different mutations in growth control and other aspects of the cell. And transgenic mice were also new. So for the first time you could put a gene into a mouse and see what it did, as opposed to sort of old fashioned genetics where you just look at hereditary patterns in types of mice or something like that. And this was a tremendous time. And I realized as it accelerated along in late 1980s that this could be applied to really great questions in the nervous system because to understand the genes and find the genes involved with behavior and learning and memory was a completely open area. And I went in to see Jim Watson of Watson and Cricket Bain. He was a director of Cold Spring Harbor Lab. His office was about 20ft away from where I was as a postdoc. And I told him my ideas about doing this work and I told him I had some ideas about creating transgenic mice to look at how genes control learning and memory and synapse function and synaptic plasticity which I know is something we will talk about today. And he just said to me, much like the sort of Nike commercial, he said, just do it. He recommended that I meet Eric Kandel, who was at Columbia University. Professor, very prominent individual. And this was in 1989, this particular year. He introduced me to Eric, and I met with him and presented my ideas to him about doing that. And he was supportive. And he said, why don't you come in and do that work here in Columbia? Which I did in his laboratory. And we published some important papers in 1992, which were the first knockout mice, where you had mice that were engineered for gene mutations and studied their impact on synapses and learning and memory. Susumu Tonegawa's lab in MIT did it in the same year. And so that was really the beginning of what was sort of the mouse knockout. In other words, gene manipulation, behavior learning, and memory revolution. And it just exploded after that. So now we started to collect information about how genes were involved with behaviors. And it really was a tremendous transition. Because up until that time, the whole field had been dominated not by molecular biologists at all. It was all electrophysiology and anatomy and pharmacology. And I might just say that many of the pharmacologists and anatomists and others were actually rather put off by all of this molecular biology stuff. And I think many of them felt quite threatened and said all sorts of disparaging things about the work. Nevertheless, work has completely transformed the field.

Dr. Ginger Campbell (7:19)

Right. And I think I first became aware of it when I read Eric Kandel's wonderful autobiography, In Search of Memory. It's the kind of book that's my favorite because it combines his story with the history of the science and some explanation of the science, which I think is a really great way of sharing this with people. So you've got to write one of those someday.

Dr. Seth Grant (7:46)

Maybe after working on it.

Dr. Ginger Campbell (7:48)

Yeah, maybe when you get your Nobel Prize, then you can write one. I'm sure that's what got him off the sidelines. So one more thing. Since your paper that we're going to talk about today is about the lifespan of a scaffolding protein that's called PSD95. Would you just explain what this is and why it's so important?

Dr. Seth Grant (8:11)

Yeah. Let me just try to sort of unravel this for the listeners here. Winding back the clock to that period of time I mentioned earlier. The beginning of the 1990s. If you went and asked any scientist the following question. How important are synapses? And what do they do. Everybody would have said they are incredibly important because that's the locus of learning and memory. And the way memories work is because when you learn something, a synapse might become more efficient or stronger in the way it transmits information. And that idea, incidentally, was put Forward in about 1889 or 1891 by Ramoni Cajal. Very ancient sort of simplistic sort of idea. And there was some indirect sort of support for that at the time in a variety of different ways. But if you also ask the people at that time, the following question is, what are synapses actually made of? What are the. And the answer is, of course, there's proteins in them. Because proteins make up everything in the cell. But what do we actually know about those proteins? How many are there? You can almost count them. On one hand. At that time, there were some molecules involved with the release of neurotransmitter. On the presynaptic side, there was a lot of study of that going on. And then on the post synaptic side, that's where the neurotransmitters act. And that's where information first comes into the neuron. It was known from pharmacology experiments that there were some receptors there, very important receptors for the neurotransmitters. But the genes were only just starting to be cloned in 1989. That the sequence of the DNA for those genes at the very first time then. And that was at the time when I joined Kandel's group. And so we almost knew nothing about the molecules then. And interestingly, scientists with those very few count on one hand set of molecules, scientists posited that those few molecules were sufficient to explain how synaptic transmission worked and how learning and memory worked. And oddly enough, there are some scientists still today who actually still believe that idea. Well, what I can tell you is that in the intervening years, there was a massive increase in the number of molecules that were known. And much of that work is work that we did which was using mass spectrometry. And it's now routine for scientists to report that in synapses there's actually thousands of different proteins that are in them. Not a handful, thousands. So the numbers went up hundredfold since then. So now if you ask the question that you would have asked back then says, what is a synapse made of? Now you list off these great numbers of proteins, different types of proteins, receptors. And then there's a type of protein called the scaffold protein, which is this PSD 95, which you've introduced. It's a particular kind of protein. It's an interesting protein because like all proteins, they wind up from their amino acid sequence and have protein domains and those domains do things. Everybody knows about enzymes, one metabolite to another or digest something or have some activity like that. But these scaffold proteins, they don't have any activity at all. All they have are these binding domains which allows other proteins to bind onto them like a Lego block, other proteins can attach onto them. And that's actually very important. It's because proteins don't just float around all by themselves as monomers, as individual proteins. Proteins are all assembled into what's called multi protein machines. We scientists call those complexes or multi protein complexes. And a good example of such a thing is the ribosome. That's the machinery that translates messenger RNA and makes proteins. It's got a large number of proteins. Many dozens of proteins are in a ribosome. And so inside synapses are also these multi protein machines. And one of the key proteins that is very abundant and is found in the sort of excitatory types of synapses is called PSD95. And it assembles very important protein machines which have the neurotransmitter receptors attached to them, plus all kinds of other enzymes and other sorts of proteins. So it's a very versatile sort of Swiss army knife kind of molecule.

Dr. Ginger Campbell (12:32)

Right. And can I interrupt you just a second to ask or remind us that its relationship to you remember the time that we talked about the gene duplication and that study that you did with the mice and the genes that we know are duplicated, the DLG genes, is one of those, the one that codes for PSD 95?

Dr. Seth Grant (12:56)

Yes, it is. And what you are referring to there, and I'll just mention it in briefly for the listeners, is that PSD95, this protein which binds with these other molecules to make this very particular molecular machine, is very similar to three other proteins. In other words, the sequence looks extremely similar, not the same, but very similar. And you might ask the question, how do you get four genes that look very similar? Well, the answer is it's a kind of a cut and paste job that was done in this case about 500 million years ago. There was an ancestral organism which is a sort of a thing like a Lancelot. It's a sort of a very simple worm like creature which had a notochord. And this type of creature had only just one copy of PSD 95 and lots of other molecules in its genome. Just had one copy, but by virtue of the biggest kind of genetic mutation of all, it had an offspring which had an entire extra genome. So it had twice as many of every gene. And then one of its offspring later, about 50 million years later, also had another genome duplication. So altogether, its offspring had two whole genome duplications compared to its ancestor. That means it went from one gene. First duplication gave two, the second duplication went two times. Two is four. And so it had four copies. And that's how some ancestral organism about 500 million years ago had these four copies. And then over the intervening period between then and now, each of those copies have got slightly different. They've accumulated little point mutations and subtleties that give it differential functions. And that's what happened in this particular family of molecules, PST 95, and in that work that you referred to, what we did was to describe this family of molecules had expanded in the vertebrate. And by the way, I should say for the readers, this is all happening in the vertebrate lineage. And this is what makes vertebrates very special compared to invertebrates. Invertebrates didn't have these whole genome duplications. And so as a result of that, the vertebrates have very big toolbox of genes and then can produce all sorts of diverse functions. And that's one of the reasons why we're so very clever. And that's not just a supposition. We did experimental genetics. We published these two papers back to back in Nature Neuroscience in 2013, where by virtue of doing gene manipulation experiments, we could demonstrate that these extra copies, these extra pieces of molecular machinery that we vertebrates have actually gave us our more complex behavioral repertoire that we have.

Dr. Ginger Campbell (15:29)

Right. And as I recall, one of the genes is absolutely essential. The animal can't live without it. So that's probably the original. And one just causes really severe disabilities, and then the other two seem to have a balancing effect on each other. And you showed that the PSD 95 and the gene that it relates to, it affects behavior and learning, which is one of the reasons why you're so interested in it. Right?

Dr. Seth Grant (15:58)

Right. And in fact, we had shown in a paper back in 1998, when we made the first mutation in this PSD95 gene, that the mice have a very severe learning impairment, those mice, and they're profoundly affected. And oddly and interestingly, and in a way, it challenged the sort of central dogma of learning and memory. We found that those mice were actually super duper at strengthening their synapses, yet they had a severe Learning impairment, that sort of went across the grain. And so we had to, in our discussion of that paper, fit a square peg into a round hole and try to talk our way out of why we didn't think that was such a big problem. And some of the more recent work we've done is offered actually new explanations for how learning and memory might work. And that's part of the discussion that I know we'll have today with respect to our recent paper.

Dr. Ginger Campbell (16:46)

Okay, I got one more question before we do today's paper, and that is most of your work is done in mice. Can you talk a little bit about these genes, how similar they are or are not to humans?

Dr. Seth Grant (17:00)

Indeed, we actually have two areas of work in our lab. It's work on the mice and work on humans. We've done a lot of analysis of synapses in human brain and in mouse brain and compared them. One area of investigation was to isolate all the proteins out of the synapses of a mouse and out of the human. In other words, to simply ask the question, are they made of the same stuff, the same proteins? And indeed they are. And not only are they made from the same proteins, but when you look at the genes that encode those proteins, you can tell by looking at the nucleotide sequence in a gene how frequently it has received a mutation or a variant with time. And you can ask questions about did that occur as frequently as you might expect, just by chance, or was there some reason, if you look at this from a statistical point of view, you can say, gee, actually this gene didn't accumulate many mutations, and that must maybe because it's very important. And if it did accumulate a mutation, that animal didn't survive. And what you do when you do that kind of analysis, what you discover is that the genes that encode these synapse proteins are super highly conserved, meaning they just don't tolerate mutations well. And organisms, in other words, that get those mutations presumably have a reduced fecundity, their offspring don't do well. And incidentally, it's this set of molecules that cause about 130 or more brain diseases. That's something we showed in 2011. These are a super important set of genes for brain diseases. So there's a link there, you see, there's the link between the evolutionary structure of the genes and their function and why there are so many psychiatric and neurological diseases.

Dr. Ginger Campbell (18:47)

Right. And that's why you do so much work with this one particular gene and its protein. And one of the things that confuses me sometimes When I'm reading is the tendency of molecular biologists to use the gene and the protein names interchangeably that, you know, you probably don't even see it because you're so used to it. And that can be confusing to the non biologist. But anyway, the paper that we're going to talk about now, which was published I think in the fall of 2022, is called a Brain Atlas of Synapse Protein Lifetime across the Mouse Lifespan. And it was published in Neuron and you can get it free if you go to PubMed. There is a free version. You don't need to have library access or anything. Okay, so is there any other additional. You've done a great job of giving us backgrounds, so there may not be, but is there any other additional background information that my listeners will need to appreciate this particular paper?

Dr. Seth Grant (19:54)

Yeah, I'm going to join the dots a bit more and just pick up on where I was a moment ago and try to bring you over to the present paper that we're going to go into in detail about. So picture this again, putting it into a sort of time perspective. During the sort of the 2000s and early 2000s and so on, we had been doing a lot of characterization of all those proteins in the synapses. And as I said before, it became extraordinarily complex. Vast numbers of proteins, when people used to think there was hardly any. And so a question arises, are all of those proteins all found together in the same synapses? Now, by and large, we used to think that it seems naive in retrospect, but we made sort of models of how the synapse worked and we thought of biochemical pathways and all kinds of things like that, which of course do exist in synapses. But our models we made, we were using them to try to explain why mutations cause behavioral defects. So for example, we'd say, look, I mutate gene number one and it affects protein number one and it's in the synapse. And I now make a mutation gene number two. And I look at protein number two and it's. And assume it's in the same synapse. And we think, gee, maybe protein one and protein two work together to control burning in a biochemical pathway. And that's the sort of way we were thinking and that's the way everybody was thinking. But as it now turns out, and where we transitioned, our work is that we discovered that there is a vast and possibly limitless diversity of molecular types of synapses. And that was in a paper that you And I discussed back in around 2018. And so the trickery that we did to uncover them was to modify the genes that make these synaptic proteins by taking this PSD95.1, for example, and sticking on the end of it a fluorescent green protein. And then this other protein, this one called SAP102, with this sort of sister molecule, and we stuck a purple protein on the end of that, and then we made mice with those. So when you look in the mouse brain, you see all the synapses glowing up with these colors. And if you breed these mice with the green synapses and the pink synapses together, you get pink and green synapses. Some are only green, some only pink, and some with both, and suddenly say, wow, look at all that diversity. There's a lot there. And then using very clever sort of computational methods, we imaged individual synapses, millions and millions of these things, and in every single one of them, quantified the amount of fluorescence coming out and thereby could say how much protein there was. We could have the size and the shape. And so we could generate for the first time a catalog of synapses of a particular. These are called excitatory synapses, I might point out, but a catalog of synapses in the mouse brain. And we found this tremendous diversity of. In their protein composition.

Dr. Ginger Campbell (22:51)

And that was just by just looking at two of the possible proteins.

Dr. Seth Grant (22:54)

Indeed it was just by looking at two. And if you take two proteins, you can have, we call them molecular types. You can have some synapses only have one of the protein or the other one, or you might have some with both. That would be three types. But then when you look a bit more closely at the synapses, which we do with a microscope and using our computational methods, we can see that they vary in the amount, the intensity, the size and the shape. And using statistical methods, you can more or less ask the computer, and there's very sophisticated machine learning methods and so on. You can say, show me how many subtypes there are. And we generated 37 of these subtypes from just those two proteins. So if you had 10 proteins, and you just make these very simple assumptions from that, you could generate 10 proteins instead of 37 subtypes, you'd generate 10 to the power of 11. I choose that particular number, 10 to the power of 11 for a good reason. And it's because that's the actual number of synapses in the mouse brain. So if you wanted to have every synapse in the Mouse brain different to every other synapse in the mouse brain, all you need is 10 proteins. But I just told you a minute ago that in the synapses, thousands of proteins.

Dr. Ginger Campbell (24:06)

Yeah.

Dr. Seth Grant (24:06)

And not only are there thousands of proteins, but there's also splice variants and post modification modifications. So it's possible that every synapse is completely different. Now, I don't actually think that to be true. This so called combinatorial explosion is constrained and we know a lot, quite a lot about that. But nevertheless, there is a massive diversity. So in that paper in 2018, we described what you call the compositional diversity. In other words, which proteins are in there and how many different types and synapses do you get? And then you get this astonishing architecture where these different types and subtypes all have a particular pattern and distribution across the brain. And then in our next paper that led up, it was in 2020, published in Science, we use this methodology to ask how do synapses and areas of the brain and the synapses in the areas of the brain change across the lifespan from birth all the way through development? Extremely interesting. There's lots of theories about what synapses do in development, in childhood, young adults and so on, and then also in aging. You know, synapses are lost in aging, this sort of thing. And so we systematically and comprehensively went from birth until old age in the mouse across the whole brain and made complete synapse maps across the whole brain, across the lifespan of this species. And it's the first time it's been done for any species. And we discovered that there's what you call a, we call it a lifespan synaptome architecture, meaning that the spatial distribution of all these synapses changes continuously across the lifespan. There's all sorts of fascinating changes during development and during aging. And I could talk more about that, and I think I probably did with you before. But all of that work, those two papers, tell us that there's this extraordinary compositional diversity that's called the synaptome. We call the synaptome the diverse set of synapses, and we call these synaptome architecture the spatial distribution of all those types of synapses. And that was that previous work. But then by virtue of again, molecular trickery, we were able to use all those fancy methods that I've just told you about to tackle a really basic question, again, a very fundamental question. The question we just asked a moment ago is simply this. What are those individual synapses made of? And as I Just explained, it's made up of combinations of proteins. Another really basic question to ask is if you make a protein and put it in a synapse, how long does it stay there before it's degraded? And if you just think about it, every protein in the body is made. And once it's made, it sits there and gets used. And during the time it's being used, it can be modified, it can be damaged, and then it is ultimately removed and it's replaced. So there is a normal mechanism for all proteins for the replacement. It's called proteostasis. Anyway, so this is a really interesting question for synapses because in 1984, Francis Crick had proposed a big dilemma in the models of learning and memory as they were understood then. Okay, now remember, that's 1984. This is before any genes are cloned. We hardly know any of the molecules in synapses. But he reasoned the following argument in a small article published in Nature. He said, and I'm paraphrasing him here, I don't have the article in front of me, he said, we accept that when learning occurs, proteins, there's activity in the brain, electrical activity. And when that electrical activity goes into the synapses, it causes chemical reactions that modify those proteins that are found in the synapses. And those modifications of those proteins cause their function to change. And as a result of that, the synapse function changes and therefore the electrical properties of the synapse change. And that would be a way of changing how the brain responds to electrical activity. And that could represent how learning is written into the brain by the modification of those proteins. And it was indeed, it was Eric Kandel and others who provided lots of evidence to support that general idea that the modification of proteins is a mechanism for the initial writing of the memory. The question becomes then, how long does the memory last and how long do the proteins last? And so the simple idea would be this, that if you modify a protein for a memory, then maybe if the protein is removed, then you should forget the memory. Now what? Crick reasoned, he said, look, many memories last a lifetime. And he assumed that proteins in synapses did not. And he said, look, proteins are going to be removed and replaced in the brain. And therefore there must be some other mechanism for how long term memory works. And this actually stimulated a tremendous amount of interest. And people like Eric Kandel again went to look at how there might be the expression of new genes when you stimulate neural cells and as a result of that, you form so long term in The Kandel and sort of the classic model now is when a long term memory store is made, a new synapse is born and new proteins are made that go into that synapse and that's what you need these new proteins for. That new synapse lays down a new memory trace. Now there's a lot of questions which we can come to later on about whether or not that's actually true. But in any case, this assumption was made by Crick that proteins didn't last for very long. But the problem was Ginger simply this, nobody had made any measurements at all about the duration of synapse proteins and certainly at not individual synapse level. So then we had to wait couple of decades in the 2000s and more in the last decade using methods where you can label a protein and ask how long it lasts with this special label. That can be done using an isotope. For example, you can feed an animal an isotope or you can put it on neuronal cells and then gets incorporated into the protein. And then you can just every day, hour, week, month, you can take sample of those proteins and see how long the isotope has lasted. Is it still there? Because if it's lost, it means the proteins disappeared. And when people do that, they find that the vast majority of proteins in the brain actually turn over or removed and only last a matter of weeks, sometimes days, sometimes weeks, sometimes a few of them a bit longer. There's variation. But again that was data that was obtained by taking great big chunks of the brain or vast numbers and millions and billions of synapses all at once. So all you're getting is an average for those.

Dr. Ginger Campbell (30:54)

Right.

Dr. Seth Grant (30:54)

You're not actually finding out what's happening at the individual synapse level. So when you have an average like that, there's obviously some that could be turning. Some synapses might be turning over the protein very fast and others might be turning it over very slow. So you need a way to look at individual synapses. And that's what we did. And I'll explain to you how we did it now. Because when you learn about it, you'll realize it's in a way surprisingly simple. We have this gene which makes the protein PSD95. And it's the important protein that sits inside the postsynaptic terminal of these excitatory synapses. We modify the gene, the genetic engineering, so we stick on a little protein domain on the end. Last time I told him we put on a nice fluorescent green protein, but this time we put on a different Thing, it's called a halo tag. Molecular biologists use it quite a lot. What it is is it's a very small protein domain that sort of folds up into a little ball, but it has a groove in it or a little pocket in it. And in that little pocket there is a binding site. If it were that you were to give a synthetic small molecule, it would bind into that binding site. And one of the interesting things it does when it binds in that binding site, it doesn't just sit in the pocket, it actually forms a covalent bond with the halo tag. Now, covalent bond means a permanent molecular link. And so if I now have a mouse with my synapse protein PS2 95 with a halo tag sitting on it in the synapses, and I inject into that mouse this little small molecule which incidentally I have made fluorescent, because I put a fluorescent dye on it, right? It goes into the mouse brain, it shoots in there and goes into the brain and binds to PSD 95 and never lets go.

Dr. Ginger Campbell (32:40)

That's the key, right? It never lets go.

Dr. Seth Grant (32:41)

That's the trick. It never lets go. And so you inject the mouse and suddenly boom, all the synapses all light up. You look at em under the microscope, can see them all. And then what you do is you take a snapshot every few days and you just watch the signal disappear.

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Dr. Seth Grant (33:30)

And once you fall in, it's really quite remarkable and obvious. Just look at the pictures. You find that the vast majority of synapses lose all of their label within a couple of weeks. That's the first point. The second point is you see that in some parts of the brain, the synapses are still retaining some of the synapses, not all of them, some of them are retaining that label. Now let me tell you why those two observations are so super interesting. The first one is I told you five minutes back that there's amazing synapse diversity and it's all spatially organized and you look at that map and you say, wow, that's a very amazing map. And now what I'm telling you is that the brain basically rebuilds that map in the mouse every couple of weeks. It's as though you took a city like Manhattan or something and said, look, I'm just going to rebuild the thing every three months or something like that. You know, we won't change anything. It's all going to be the same. I'll just replace every brick and every girder and every tile and every piece of tarmac or whatever it is, and I'll just get on with it and just replace the whole thing, you know, while you're getting on with yourself. So that's what the brain's doing, it's replacing everything, but it's not doing it at the same rate. Synapses, and that's the second thing we found these synapses that have these very long protein lifetimes. Strangely enough, they're in that part of the brain which is the most recently evolved part of the brain, which is the superficial layers of our cortex or the mouse's cortex. And that's where you find them preferentially stored and also in a certain part of the hippocampus. And that is a very interesting place for them to be found because that's where long term memories are stored. So what we did was to then look at how long those synapse molecules can last, and they can last for months or more. Now, an adult mouse, if you look at the literature on this, and there's a very lovely ancient sort of literature, when I say ancient back to the 1930s and the 1940s, there's a literature that tells you what's the natural lifespan of a mouse. In the lab, you can have a mouse sit on the shelf in a little cage there. If you look after it every day, it'll live for two, sometimes three years in some cases, depending on the strain of the mouse. But in the wild, a mouse typically has a lifespan of about six months. So if I now take an adult mouse and I have synapse proteins in an adult mouse that lasts for a month or so, then that's plenty long, time enough for it to store some sort of long term memory. So although we do not know that this long protein lifetime synapse is a method for storing long term memories, I'm not saying it is at this point. It certainly is an interesting new candidate mechanism. But there's another flip side to the whole thing, which is a very interesting thing. If you look at where the proteins with the shortest protein lifetime live. So we think, okay, the memory centers have these other areas which have long protein lifetimes. Let's take a look at the short protein life. Where are they? It turns out that they are heavily enriched and populated. In those parts of the brain control innate behaviors.

Dr. Ginger Campbell (36:42)

The ancient parts.

Dr. Seth Grant (36:43)

Yeah, the sort of ancient parts of the brain and the stuff that you rely upon to do all those basic bodily functions and all those key activities that if it were that they were modified or changed, you might have a problem. So it makes a lot of sense and I'll try to explain it so everyone can understand it. If you have synapses that are involved with feeding functions or reproductive functions or some other really basic biological functions, you don't want those to necessarily change as a matter of every experience that you have. You want those to be robust, resilient, in a way, non plastic or minimally plastic. But if you look inside those synapses, they've got all that molecular machinery that can actually be changing. That is to say, in response to activity, the molecules can be changed, but rather conveniently, those synapses are the ones that are turning over and replacing those proteins quickly. So if a protein is modified, this rapid turnover or short protein lifetime could erase any particular modifications and thereby keep it in a sort of what I would call genetically programmed, innate, instinctive way. So these are the couple of little points that come out just by looking at something really basic, that is protein lifetime, you suddenly get a whole new insight into not only synapse diversity, because now synapses are diverse not only because they have compositional differences, but they also have protein lifetime differences, again producing even more diversity. But also you find that their synapses with different lifetimes have a very interesting geographical distribution in the brain.

Dr. Ginger Campbell (38:19)

Okay, so just for a review point, what's the sort of difference in scales between ones that have short lifespans, the proteins that have short lifespans, and the.

Dr. Seth Grant (38:30)

Ones that are considered long, about a tenfold range.

Dr. Ginger Campbell (38:34)

So like the difference between hours to days to months, I'm sure it will.

Dr. Seth Grant (38:38)

Depend on the different protein that you look at. But in the case of PSD 95, which is the only protein we've studied so far. Right. And by the way, it's going to be obviously very important for us to do the same type of thing on lots of other synaptic proteins. And I'll explain why in just a moment. But in this particular case, it goes for days to months kind of range. Okay, the reason I'll just jump on that point it's interesting to look at other proteins is because there's many different classical types of synapses in the brain. People will have heard of dopamine synapses or serotonin synapses, all very important in various disorders and mood and used by pharmaco. You know, drug companies target them in all sorts of interesting ways. But it might be that those synapses, or inhibitory synapses, those types of synapses, we want to understand if the same principles apply in those as well. I'm optimistic and pretty confident that will in fact be the case because these molecular regulatory principles of combinations of proteins and protein lifetimes are so fundamental that they will almost certainly apply to these other sorts of synapses. But it will be important to show that and it will also be important to compare those other types of synapses with the excitatory synapses, because it might be that in one part of the brain, all of the synapse types are turning over really fast, the proteins are turning over fast. Or it might be that we're up in the superficial layers of the cortex. Or maybe the dopamine synapses and the inhibitory synapses, maybe they turn over quickly, but the excitatory synapses turn over slowly, which would mean that the memories are held in those synapses, but not the dopamine synapses or something like that. So these are very, very doable things which we are planning to look at in the coming years.

Dr. Ginger Campbell (40:26)

So I know that we've talked in the past about how the distribution of the proteins that you study so far change through the lifespan to the extent that you can actually use it as a calendar and look at a, an animal and even predict from the distribution what its age was. And we've talked about why that's important in the past. How does the lifespan of the proteins change the. You know, how long. Yeah, I'm getting my lifespan.

Dr. Seth Grant (40:57)

How does the lifetime change the life change?

Dr. Ginger Campbell (41:00)

Yeah, that's what I'm trying to say.

Dr. Seth Grant (41:02)

You thought it was difficult to say. You should have tried writing this stuff anyway. Yeah, the lifespan is a very interesting issue in general. And one of the things from our earlier compositional study, that was our science paper in 2020, we found that the synapse composition and distribution in brain areas continuously changed across the lifespan, but it didn't do so at the same rate the whole time. That during this developmental period, which is up to about three months of age, when a mice is sexually mature and capable of reproduction, there was a huge expansion in synapse diversity. And all these different areas of the brain were suddenly populated with all these different types of synapses. But then there was a period of stability. You might think of it as adulthood from the sort of would be the equivalent from 30 years of age to, you know, 45 or something like that. Pretty human. It was already very stable. But then there was a third epoch, which meant as progressive changes out into older age in the mouse. And so simply by looking at these synaptome maps, we could see these three classic periods of the lifespan, which we can all relate to as humans. But there was continuous changes at different rates and different things changed at different times. Now, we wanted to ask in this new paper here, whether during the lifespan was the protein lifetime changing or was it in any way different? And we found a very clear picture. We looked in some very young mice, about two or three weeks of age. We looked in some mature adult mice, and then we looked in some very old mice. So they represent those three periods of time that we'd seen before. And what we found was clear. In the young mouse, there's very few of these long protein lifetime synapses. All the synapses are all rapidly turning over. And in the old mouse there's very few. You lose a lot of the rapidly turning over ones. You have a lot of the long protein lifetime ones. In other words, you accumulate the protein turnover rate slows down as you get older and older to progressively throughout their lifespan. So synapses have different. In an old animal, you have very slow protein turnovers and lots of these long protein lifetime synapses. Now, I might point out there was a beautiful connection between Our Science Paper 2020 and this present study, because we answered a fascinating problem. Again, going back to the 2020 paper, where we found composition changes with age of all of those 37 subtypes. We looked at all of them, how they change with age. We found some that were really resilient to aging. They remained, I should say the total number of synapses gets lost in old age. People know that. And we saw that in the mouse too. But we saw that subtypes of synapses were resilient to aging. Now, that's a fascinating class of synapse. And then conversely, there was another set of synapses which were lost much more frequently. So suddenly you had some that were what I would call age resilient. And age is sort of vulnerable. And we didn't know what, you know, why they did that, what was the difference we thought that was a really interesting problem in our analysis of the protein turnover and protein lifetime. It just fell out because what we found was that those age resilient or age resistant ones, the ones that hang around, they're the ones with a very long protein lifetime. Those ones that are all stored up there in your cortex and so on, they're the long protein lifetime ones. And the ones that preferentially get lost are those short protein lifetime ones, the ones that are rapidly turning out. So that was a very beautiful pattern that came out of that. So that tells us that these protein lifetime staff the duration that proteins last in synapses, probably very important to the sort of adaptability of synapses, to the resilience to aging. And we believe they're very important in disease. And we did some work to actually show that was the case.

Dr. Ginger Campbell (44:59)

So let's talk a little bit about the implications of this. Let's start with what does it possibly mean with regards to aging? Before we talk about disease, let's just talk about normal aging.

Dr. Seth Grant (45:13)

Yeah, I find this to be an increasingly interesting and tractable question with respect to synapses, as I already sort of alluded to, there's been a long history of people saying, look, with aging you lose synapses. People have looked at them and said, ah, you tend to lose smaller synapses than big synapses. But what we're seeing with the molecular biology work, and in particular the single synapse work that I've described to you today, is that your brain has these populations of different types of synapses and some are being lost with aging and others not. Now this is the first time, and that those ones that are not have these very long protein lifetimes. So this is giving us a completely sort of new way of thinking about how the brain changes with age. Now, what we need to know, and this is definitely a very important area of research for the future and there's a lot of work to do. And at this point I'd say we're just really opening the door on this problem as opposed to solving all the unanswered questions. We need to know what are the molecular differences between those synapses in far more detail than what we already know. I told you there's thousands of proteins in synapses. So we'd like to be able to isolate those so called long protein lifetime age resilient synapses and find out what are all the proteins are that are inside them and ask in what way are they different to those short protein lifetime synapses, which generally are lost and see if that gives us a clue as to why they are in fact resilient to iag. Another thing we want to do is to try to determine whether or not they have different memory properties. Now this could be very interesting because there is very well described literature, psychological literature that describes how different aspects of memory change with age. Everybody knows as they get older that their ability to retain short term memories, working memories, those sort of day to day things, you know, where did I put my keys? You get less good at that and, but nevertheless you can remember some stuff from your childhood. And we postulate and speculate that could be because those long term memories are stored in those very stable age resilient, slow protein turnover synapses, whereas the rapidly turning over ones are those that you store short term memories in and you lose a lot of those as you get older. Therefore your ability to store short term memories diminishes. Now that's actually testable and we're thinking about how to, you know, get on and do that kind of thing. So I think from the basic aspects of memory, that's an information storage, there's some quite key questions to ask there.

Dr. Ginger Campbell (47:47)

Right. And having them be long lived, it's not all to the good. Right. Because you talked about in the paper how maybe you also have more of a buildup of toxins or whatever words you want to use at the same time. Why would that be?

Dr. Seth Grant (48:06)

Yeah, in all things in biology there's a sort of a trade off. You know, you get something might be good on one hand but bad on the other. And let me try to explain that, as I've already made very clear, we think, and this is something we need to again study in more detail, that all of the, in those proteins where we saw PSD 95 have this very long lifetime, we suspect that's like a sort of a sentinel or a flag which says actually all the other proteins also have a very long protein lifetime as well. So that would mean that any protein that was in that synapse would hang around for a long time. And conversely, those synapses with short protein lifetimes, any protein that was there would all be cleared away very quickly, take out the garbage quickly. The long protein lifetimes keep the garbage in the house. Now that could be a problem because there are many, in fact, a large number of neurodegenerative disorders have in common the fact that, that they produce these aberrant protein accumulations, toxic proteins, they're often referred to. And so those proteins Are also known to find their way into synapses. And that would mean then that synapses that can clear those proteins out quickly would be less likely to suffer damage. But those synapses that don't clear those toxic proteins quickly could be more vulnerable and disabled by those. And that could explain why one starts to lose certain types of memory associated with these neurodegenerative disorders. So, again, that's going to be a very interesting question is to ask how do these toxic proteins get cleared differentially by these different types of synapses?

Dr. Ginger Campbell (49:51)

So what happens when you have the mutations that we know are. Are associated with autism and schizophrenia and you put those mutations into the mice? What happens?

Dr. Seth Grant (50:03)

Yeah, so that's been a very key area of interest of ours for more than 20 years now. And the history of that goes back to year 2000, when we isolated lots of these synaptic proteins in the synapse. We thought that could be relevant to schizophrenia because there was certain clues around at the time that a drug called ketamine actually, which is now a major subject of drug of abuse, it actually interacts with glutamate synapses. And therefore, we thought it might have something to do with these proteins. And I wrote a big grant application to study the genetics of these proteins in humans and ask the question, are they involved with schizophrenia? And over the course of the next 10 or 15 years, we showed plenty of evidence for that and collaborated with lots of big psychiatric genetics groups who used our protein lists to show that the genes involved with schizophrenia very much are concentrated in the proteins that are found in synapses. We now know that schizophrenia is essentially a synapse disorder. And indeed, many autistic syndromes are caused by mutations in synapse genes as well. So it's a common problem. But I just want to emphasize that what that does is means the synapses have, you know, don't work so well. But here's the really interesting question. Now, in light of what I've just told you, if you have a mutation in one gene, it's not going to affect all synapses. It's only going to affect some of them, because each synapse protein is only found in some, but not all, synapses. So we're very interested in using these brain maps that we've discovered to act like a roadmap for understanding how your gene mutation changes your brain. This gene expresses a protein in that synapse. This gene expresses a protein in that synapse. And so if you have a disease Here, it'll affect those ones. So this is a really interesting thing from the point of view of disease. Very simplistic, but interesting because it means that you might be able to develop ways of targeting drugs to particular types of synapses that you haven't thought of before, or you might have ways of stimulating the production and increasing the number of one type of synapses if it's lost and that kind of thing. But we have actually this protein lifetime story, I just want to say, about autism there. We measured schizophrenia and autism mutation, which is in this pro PSD93, again, another sister molecule of PSD95. And individuals with those mutations can have schizophrenia or in some cases, autism. And what we found was that mutation had really quite a profound effect on the lifetime of the PSD95 molecule. And we thought that was a very interesting thing because it suggested that the PSD 95 now stayed around even longer than you'd expect. And if that was the case, and you thought that was important for memory with our hypothesis, then you'd expect the animals to become less flexible. In other words, their synapses have now changed and they're not going to be able to forget things as easily. In fact, that's what you see in these mice. And in an earlier study, we'd shown that these mice which have this mutation have impairments in their cognitive flexibility. They're not so good at reversing or extinguishing something they've learned. So it fits with what we observe there. So I think the readers can take away these very straightforward messages, which is that there's basic molecular principles for the organization of this vast diversity of synapses, where you have combinations of proteins and ones with different durations of life, put them in all sorts of different combinations. In your brain, you have these amazing maps that change throughout the lifespan, and those will determine when a disease will occur and in what part of the brain they will occur.

Dr. Ginger Campbell (53:36)

So, Seth, what's next? I know you've developed this technique that any lab could reproduce, so hope you want other groups to work on some of the other proteins, since there's so many of them. One guy certainly can't do it all. But what do you want to work on next?

Dr. Seth Grant (53:53)

The human brain. We have, as I said before, we've been working on the human brain now for almost two decades. But what we specifically are working on, we have a project called the Human Brain Synaptome Project, and it's still in its nascent level. And those sorts of mouse brain maps for Us have allowed us in the mouse to establish all sorts of key principles. But what we want to do now is create maps of the human brain. We, in the year 2000, we published a sort of version 1.0, very limited, very simplistic mapness of this PSD 95 molecule in lots of different brain areas in a number of individuals, postmortem brain tissue. And we found that there's really great diversity of those synapses across the human brain. But we've been working to develop what you might call high throughput, large scale ways of doing this, such that we could survey large numbers of areas across the human cortex in many individuals, that is the brains for many individuals. And we would like to be able to ask questions about how that synapse diversity differs in those areas of the cortex that have these wonderfully different functions, such as language, vision and all these other functions. One of the great puzzles, understanding the function of our cortex in humans is that we know that there's functions that are regionalized in the areas of the cortex. You can, we've done that for ages just by lesioning or injuring the brain or by looking at brain imaging data. But if you actually go and look at the microscopy of the cortex and say, what is it made of in terms of cells? It all looks the same, it's a little different. And Broadman, a hundred years ago, a German neuroanatomist said, ah, the cells are all a little bit different in these different areas. And you call these Brodmann areas, we still talk about them today, but molecular scientists are now looking at gene expression in those different areas of the brain, brain and say, yeah, it looks like there's differences. So what we are looking at is gonna be the synaptome differences and the synaptome architecture. So we're very interested in that. And it's a very technically challenging thing to do because you can't do these gene manipulation experiments. You have to use different technical approaches for labeling the molecule. But we can use these very fancy imaging methods we've developed to analyze those images from the brain tissue. And we have it working and I think it's going to be very exciting.

Dr. Ginger Campbell (56:20)

So what do you think are the biggest questions for the future? And you can put that in whatever timescale you want, you know, this year, 20 years from now, whatever. What do you think is the burning questions you hope to explore?

Dr. Seth Grant (56:35)

I think neuroscience and brain science in general is full of what I would call micro theories. There's lots and lots of little tiny theories you know, a dendrite does this. Those neurons do act. There's a circuit for that, and the circuit for this. Learning and memory works by synaptic strengthening. We represent innate behaviors in circuits. You can just go on and on, and there's just large numbers of those. But it's my view that there are fundamental molecular principles which you could probably count on one hand. Maybe I'm exaggerating a little bit, but there's going to be a few key principles which can produce this extraordinary, functionally relevant architecture. And I think there's no better place to look for that than in the synapse, because the synapse is the hallmark of the brain. The brain is characterized by these vast numbers of them. And the molecules in the synapses are very ancient. We've talked about that before. The molecules of the synapse predate the brain in evolution. And when we came along and multicellular organisms developed neurons in the brain, all they did was to take these ancient molecules which had evolved in unicellular organisms, you know, bacteria and algae and things like that, and just put them into the synapses and then neurons, all they did was multiply them up a lot. Neurons are a very nice way to make lots more synapses. And synapses are immensely sophisticated in their molecular computational properties. They're not just simple connectors, like plugging a plug in on the wall. They are, in fact, like the computers and the wires and the cables and everything are just like the cables on the Internet. They're the uninteresting part. The interesting bit is the synapse. So what we're seeing by looking at these molecular properties of synapses, I think we're getting a little peek into some of these, what I would call general principles, which I think we already clear are profoundly important for large numbers of diseases and also profoundly important for how we have innate and learned behaviors. So I think those are the really big questions, because I think when you understand these general principles, you'll ultimately understand even bigger questions like consciousness and things of that nature. I think it will be reducible down to some molecular and genetic principles.

Dr. Ginger Campbell (58:52)

So, speaking of consciousness, you know, we've talked about how the vertebrate has those two gene duplications that allow vertebrates to have these complex nervous systems. And we've talked in the past how the synapse in an invertebrate is not as complex as the synapse in a vertebrate. What about something like the octopus? Do you think that it would be interesting to see what's going on in an octopus. Did it somehow get more complex synapses?

Dr. Seth Grant (59:22)

There's actually been some work on that. And the synapse proteome, they're certainly not as complicated as what they are in the vertebrate species, but they, you know, there's plenty of sophistication within their synapses. I think it's important to recognize that you can do an awful lot with a few molecules. Let me give you a very, I think, deep and profound sort of insight into that. I mentioned this protein, PST95, this scaffold molecule which binds together these molecular machines which are really vital for the way you and I have this conversation. And all of our innate behaviors and learned behaviors, we take all those molecules, all of our behaviors are messed up. If you look at the phylogeny of those molecules, as I mentioned to you, essentially those molecules and the domains that make up those proteins, they all evolved in unicellular organisms. And in fact, you can trace many of the synaptic proteins and their ancient history, including even the neurotransmitter receptor protein you, all the way back the most early forms of life, which we scientists refer to as the last universal common ancestor. And these bacteria, prokaryote like organisms, had in their surface, you know, these small versions and less sophisticated versions of our molecular machines, these signaling machinery that I just referred to. And it's known from studies in, you know, E. Coli and other bacteria today that those molecular complexes there, which are quite simple by comparison to ours, they have only two major components to them and some other enzymes and so on, they can control the spatial navigation of the E. Coli in a three dimensional space such that it can go toward things that it needs or wants, if I can use that term for an E. Coli food, or it can go away from things that might be deleterious to it, poisons. And that just shows you that the fundamental mechanisms of navigation in space can be done with very simple molecular apparatus in a tiny and simple organism. And then on the other hand, you have neuroscientists who spend a lot of time sticking electrodes in the brain saying, look, the hippocampus and other parts of the brain are important for spatial navigation. And indeed the synapses that are involved with that forms of spatial navigation are in fact the ones containing this ancient molecular machinery that I've just spoken about. So what that says quite simply is that this molecule and molecular stuff can do that spatial navigation, albeit perhaps in a more elaborate way. In the vertebrate but don't underestimate the computational power of these molecules. You don't need a big, fancy wired up nervous system to do some pretty sophisticated stuff. And there was a lot of beautiful biology done on unicellular organisms by Binet, with a guy who came up with the IQ test, amongst other things, and others in the late 19th century who described the remarkable behavioral repertoires of unicellular organisms which don't have lots of neurons, they have no neurons, in fact, and they don't have all these fancy branches and things. It's the molecules that matter.

Dr. Ginger Campbell (62:37)

Yeah. So we've talked often about advice for students and I'm not going to ask you to retrace that, except to ask if you have any particular new thoughts based on maybe how the situation is evolving. You know, I think back about when you were young and Watson and Kendale could say, go to it, young man. It's hard to do that now, isn't it?

Dr. Seth Grant (63:01)

I don't know. I don't really think so. It seems very similar in many ways. I think the hard thing when you're a very young scientist is to know what's important to work on. And when you're a student, even a PhD level student, or even as a young postdoc, you think you know what's important to work on, but you're probably wrong. And you've really got to be always questioning that and looking at that because so many problems sound interesting. I often come across students, you know, give lectures to students and I ask them what they think is interesting and important and projects they might want to work on and they might be all psyched up about something. And I think to myself, you know what? That's not a good project. It's not going to go anywhere. And what I'm saying by that is something I, and I went through that myself. I thought things were great projects when I was young. I remember talking about it and some of the ideas were just not good ideas at all in retrospect. And I'm glad I didn't follow them up. But that's the really hard part. I know it's a cliche, but the hard part is to decide what's the right question. It's easy to answer any old question once you get going. You know, most scientists can do that. The question's the hard bit.

Dr. Ginger Campbell (64:10)

So I guess finding a good mentor is critical because when I think about the people that I've talked to over the years, almost all of them have stories similar to yours. That is the they've had mentors that gave them guidance, the right balance of guidance and freedom. And that's pretty tricky as a young scientist to find that person. Right. Because you don't want to get stuck in the lab of somebody who only cares about protecting his turf or his, or her, you know, pet idea. Right.

Dr. Seth Grant (64:41)

I think I worked in such a lab. Actually, you know, it's not a criticism to say this about, you know, Eric Kandel. He had a particular vision that he wanted to follow and he was very motivated and you know, want things to be on board with that. And I can understand that. I think that's really not so much as the issue. And, and I also, I think I, you know, this sort of freedom versus guidance, sort of balance or dichotomy, I think it can be quite bad thing to have too much freedom when you're a young scientist. Right, right.

Dr. Ginger Campbell (65:12)

And you already explained why that's true.

Dr. Seth Grant (65:14)

Really waste yourself a lot of time and do the wrong thing. Now I think the key question, the key thing is to keep looking at, be critical about your work or its weaknesses, of course, but also ask yourself, is this really important? Is this really fundamentally important? And just keep doing that. And I'm a huge believer in the importance of basic fundamental science. And I think one of the problems is today is that there's so much funding being channeled toward translational neuroscience.

Dr. Ginger Campbell (65:49)

That is right.

Dr. Seth Grant (65:50)

And that, and it's all well meaning because who doesn't want to cure all of those diseases or hear tomorrow that they can't all be fixed up? Everybody wants that. But I see lots of students and people going into these programs mainly because there's funding in them, they're doing very applied descriptive and things and they're not really going to work out. And whereas I, if you said, look, I'm going to try to treat schizophrenia, but I'm never going to try to bother working out what's in a, what's in a synapse, what are all those proteins or what are the genes that encode them. We wouldn't know what schizophrenia was today. Now that's not to say, you know, somebody might turn around and say, fine, we now know what causes it, but we now want to understand how to treat it. At least you have a whole new way of thinking about the problem, one that's based in an actual understanding of the etiology, the disorder. So there's a huge amount of understanding to be gained in basic neuroscience, which is I think absolutely crucial to this sort of endeavor. And I think it's important and there's just not enough funding going into that kind of thing, I don't think.

Dr. Ginger Campbell (66:50)

Yeah.

Dr. Ginger Campbell (66:51)

Seth, what else would you like to.

Dr. Ginger Campbell (66:52)

Share before we close?

Dr. Seth Grant (66:54)

I think we've covered all the main things. Thank you, Ginger. I just want to encourage people to think about the importance of synapses and those proteins and those molecules and the genes that underpin them and try to understand. And one little final passing comment, which I may have said once before, is don't forget that it is every organism has inherited its genome from its parents. And all of the molecules that are made by that genome allow that organism to survive and do its thing and ultimately pass on their genome to the next generation. And those things that genome does in in many of us is to produce a brain. And the purpose of the brain, if there is any at all, is for the genome. The genome built the brain for the genome. That's what it's for. It's not there for us to play chess or to watch the television or anything like that. It's there to protect the genome and all of these bits and pieces that we have do that. So if you really want to understand what's going on in the brain, you will never understand it unless you understand the genome and the importance of genome evolution. You will never understand it unless you do that.

Dr. Ginger Campbell (68:08)

Right? I continue to enjoy talking with you and to learn about these things. I still haven't gotten past my original amazement when I first read the first paper I read by you back in 2000 that I read back in 2008 about how complex the synapse is and the whole idea that these molecules are so, so ancient. It's really totally mind blowing. So thank you so much for sharing this with us today.

Dr. Seth Grant (68:41)

It's a pleasure talking to you, Ginger.

Dr. Ginger Campbell (68:43)

I'm going to share a few brief announcements before I review the key ideas from today's interview. First, please visit brainsciencepodcast.com for complete show notes and episode transcripts. You can also get show notes automatically every month. If you sign up for the free Brain Science newsletter, just text Brain science all in one word to 55444. That's brain science all one word 255444 and you'll get your free gift called five things you need to know about your brain. And do send me feedback at Brain Science Podcast. I try to answer all emails, though sometimes I don't answer right away. The Brain Science mobile app is now called Brain Science Podcast. It's available for all mobile devices and it's a great way to access both free and premium content. Basic Science is a marathon, not a sprint. It's too soon to predict all the implications of these discoveries about the synapse, but it does bring to mind an important theme that I haven't mentioned recently. The brain is not a digital computer. It is constantly changing, and these new discoveries about synapse diversity make current attempts to simulate the brain obsolete. Opportunities for research in this area are only limited by imagination and the stodgy habits of those who control funding. Although Seth Grant did a great job of summarizing his previous work, I encourage you to go back and listen to his earlier interviews. I'll put links to everything in the show notes I want to close by thanking those of you who support Brain Science financially via my Lipsyn Premium, Patreon or individual donations. If you go to brainsciencepodcast.com premium you will find a table to help you determine which option fits your needs. Even if you can't contribute financially, you can help by sharing the show with others. That's it for episode 211 until next month. I hope you like visit brainsciencepodcast.com and also check out my other podcasts, books and ideas, and Graying Rainbows. Thanks again for listening. I look forward to talking with you again next month.

Dr. Ginger Campbell (70:49)

Brain Science is copyrighted to Virginia Campbell, MD. You may copy this episode to share it with others, but for any other uses or derivatives, please contact me@brainsciencepodcastmail.com the.

Dr. Ginger Campbell (71:04)

Theme music for Brain Science is Mind Fire, written and performed by Tony Katrachia. You can find his work@syncopation now.com Introducing.

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