Scientist Stories: James Williamson, Understanding Biological Factories to Fuel Drug Discovery

Hello there and welcome to the new season of Front Row, and a Happy New Year to all of you. My name is Drew Dougland. If any of you do recognize my voice, that's because I'm the host of the Institute's podcast, Science Changing Life. I'm actually part of the communications team here, but prior to that, I was in fact a postdoctoral researcher at Scripps in the world of circadian rhythms. So if any of you tuned into last season's lectures, we had Professor Katja Lamia give a talk, and I actually used to be in her lab. Anyway, there's a very special reason why I'm your host today for the lecture, and that's because our regular host Jamie Williamson is of course today's speaker. And Jamie, we get, you know, lots of questions from viewers wondering, you know, what does Dr. Williamson do? What science is he involved with? So it's very exciting for all of us that you're kicking off this new season of lectures. And so with that in mind, before the kickoff, we thought we would actually just spend a few minutes on a bit of a get-to-know Jamie, you know, not just our host, but also the scientist, because that is who you are first and foremost. So, you know, Jamie, could you briefly throw us back to those earlier days and tell us, you know, what was it that lit that spark for science in your mind? Where did that initial passion come from?

Yeah, it's hard to say, but I always really just liked having things organized into sets., and the periodic table of elements was, you know, one of the things that just blew me away that really attracted me to chemistry at a very early age.

Right, so it was chemistry, and then sort of taking that background and now thinking of all the things your lab does, so from chemistry all the way to now structural and computational biology, so a real interdisciplinary lab. And I know today's talk will be more focused on the ribosome, but could you give us a broad overview then of what your lab does in sort of its totality?

Let's see. You know, the thing that initially attracted me to chemistry was, was almost the alchemical nature. You could just transform things into other things, and then as I was trained more and more, and once I got to graduate school, I became much more interested in all of the physical techniques that you use to observe molecules rather than the transformations of molecules. And some of the most interesting molecules are the biggest molecules. So, you know, over the course of my career, I've tried to use almost every imaginable physical technique—spectroscopy, X-ray crystallography, NMR, electron microscopy—to look at the structures of RNAs and RNA-protein complexes. So it was really an evolution, but chemistry is what got me into it in the first place.

Right. And so, you know, there are so many different routes in science and possible careers. So, you know, what was the attraction then to becoming a professor and now having your own lab?

Well, I think it was the freedom to operate, right? You basically could follow your own inquisitive, you know, ideas and turn them into reality. And so that was really the attraction, was being your own boss and building a team to work on ever larger problems. Got it.

Yeah. And, you know, thinking of you, just your role as host, you know, you've been the Front Row host for multiple seasons at this point, going on 40 lectures. And so, you know, I don't want you to be picking favorites here, but just broadly, what are some of the general areas of science that really excite you sort of now and kind of looking ahead into the future?

So, you know, it really, it really is a great opportunity to not only see what's going on at Scripps, but all around the world. And it forces me to kind of get out of my comfort zone of my, my defined research program. And so, you know, especially during COVID that was, that was remarkable because we were right in the middle of all of the vaccine development and understanding how the virus worked. And we were, we were, you know, the genomics and evolution of the virus that was all going on right at Scripps. That was just really fun to learn about and then help, you know, broadcast that to the community. But I think, you know, when I look to the future, the thing that really kind of excites me as big opportunity is application of artificial intelligence. And it's— AI needs a lot of data in order to function effectively, but all of the genomic methods that are being developed and techniques that, you know, that we and others at Scripps are working on generate a lot of data. And it's, it's going to be really amazing to see how application of AI transforms the way we do science.

Yeah, definitely. It's really just branching into everything now, isn't it? So yeah, really fascinating stuff. You know, and I just end before we get to your lecture, I would just say you're not just our host and a scientist, but you're also our esteemed DJ here for these lectures. So I've got to ask you, what is the inspiration inspiration behind your music choices for the Front Row Lectures. And I was going to ask you, do you play any music yourself? But I believe today's choice also was a personal one.

So can you tell us about that? Well, yeah. So first, that was Beethoven's First Piano Concerto in C. That was the first movement. I dug out this old recording. That was me playing the piano. And you probably heard a few mistakes. But that was 1978. I played the concerto with my college orchestra. So I was really into music, and I had to make a decision when I was a freshman if I want to be a music major or a chemistry major. So I obviously chose chemistry. But, you know, the thing that I try to choose a song that's very upbeat and that has a lot of harmony. Those are the kind of songs that I like and drawing from diverse backgrounds. So if you like music, Great. If you don't, sorry, you're going to hear more.

We'll have to get the full playlist off you at some point. Okay, well, I think on that note, we should get— let you get off to the topic of today's talk.

Okay, so it's a real pleasure to have the opportunity to, uh, to talk a little bit about what, what, what we're interested in and, uh, and, and what we've been working on basically my whole career independently. So I want to start with Crick's dogma. So this is, this is the basic paradigm for gene expression in all cells. We have DNA that encodes the genes, it's copied into RNA, and that RNA is translated into the protein. And this is true for every gene that happens in every cell type. And so there are these processes that happen So the process of converting RNA into a DNA— DNA into an RNA copy is called transcription. And the process of turning RNA into a protein is called translation. And each of these processes has an associated cellular machine that carries out that function. So in the case of transcription, there's RNA polymerase. And then in the case of translation, it's the ribosome. And this is my favorite molecule, and I've devoted most of my career to trying to understand expand the ribosome. So let's see a little bit more about this. So on the left is actually a cryo-electron tomogram of a cross-section through an E. coli cell. And you can— so, you know, a cell is about a micron across, and all of these big dots are ribosomes. So E. coli is essentially a bag full of ribosomes. There's about 70,000 ribosomes for every cell. And this is an electron micrograph of a ribosome. It's a very large, big, complicated machine. I'll describe more about it. And this is the product of a very nice collaboration I've got here with Danielle, who's an assistant professor in our department. And we're working together to try to visualize ribosomes in cells. Now here, this is a beautiful image. This is from our colleague David Goodsell, who is a scientist and an artist, and he specializes at rendering of molecules. So the molecular weight of a ribosome is 2.7 million. So, you know, aspirin is maybe 100. This is 2.7 million. It's 100 by 200 angstroms, so they're very large machines, and there are two big subunits. They come apart. We call them large subunit, that's shown in blue, and small subunit shown in green. This machine synthesizes all cells in— synthesizes all proteins in the cell. So how does it do that? Well, the messenger RNA that codes for the protein slides through the interface between the large and the small subunit, and that serves as the binding site for these transfer RNAs, and they deliver deliver amino acids that are specified by the mRNA to the growing polypeptide chain that emerges from this exit tunnel. So there's sequential binding and recognition of the codon and the anticodon chemistry that happens. And the small subunit is responsible for the decoding. It sees the tRNA binding to the mRNA, and the large subunit catalyzes the chemistry of peptide bond formation. So this is basically a really big enzyme. Now probably everybody listening has taken one or more times in their lives antibiotics, and probably about a third of the commonly prescribed antibiotics actually bind to and inhibit the ribosome, and they inhibit synthesis of protein for bacteria. Again, this is 2 images from David Goodsell, and this little red bit is tetracycline bound to the small subunit. And then down in here, you can just see a little tidbit in the active site of the ribosome of chloramphenicol bound to the large subunit. So all of these classes of drugs, if you've ever taken a Z-Pak, you've got azithromycin in there. All of these drugs bind to and inhibit the ribosome. And the reason we can take antibiotics is that human ribosomes are slightly different. And we might talk about that a little bit more later, but there's enough of a difference between these types of ribosomes that the antibiotics will kill bacteria without interfering with your own ribosomes. Okay, so what are all the pieces that go together for the ribosome? So the large subunit has two big RNA molecules. About two-thirds of the mass of the ribosome is actually RNA. And then there's a whole set of small proteins that kind of decorate the outside. The same thing for the small subunit, it's a large RNA and then a set of proteins. So we have 3 RNAs that are big, and then we have about 50 proteins that, that bind to this. Now, so the fundamental problem we study is how do you put this together? So, so here's, you know, an analogy that I like to use a lot is from the automobile industry. So you can lay out all the parts on the floor for a car, but how would you actually put it together? And so one of the things, another analogy I like to use is a big box store. So you go to a big box store and you bring back this box and you take it out and there's all these parts and there's hardly any words in the instructions. They'll say things like you need tools, but you lay out all the parts lists. So here's the parts list for the ribosome, here's the 23s RNA, here's the 16s, 5s, and then 50 proteins. And you need some tools. Well, it turns out you need some assembly factors that help to bind this, but we're basically at a complete loss for what's the instructions. So a major goal of my program has been to try to understand the instructions for how do you put this machine together. So we know what it looks like, we know what it does, but it's a huge cellular undertaking to actually assemble all these ribosomes. So I would say this is a fundamentally important biological problem. So they're essential for all cells. About a third of the energy for rapidly growing bacteria is spent on making ribosomes so it can divide. And so it's really important, especially for bacteria, that you have rapid growth. Bacteria need to outcompete each other for nutrients and resources. So you have to have efficient ribosome assembly. It also turns out that cancer cells need to efficiently assemble their ribosomes. So in order for a cell or a tumor to grow rapidly, it has to upregulate its rate of ribosome synthesis. And ribosome synthesis is also really important for things like hematopoiesis, which is the development of your red blood cells, or immune cell differentiation. So anytime where there's this developmental change or differentiation of the cells, you need to make a lot of new proteins, and you got to make sure you have enough ribosomes to do it. So the fundamental question that we're interested in is, how do you, how do you make ribosomes? Okay. I want to take a little bit of a detour and give some kind of context and background for why this is important. And so I'm going to show you an electron micrograph of Tetrahymena thermophila. This is a ciliated protozoan. It grows in fresh water. Thermophila means it likes warm water. And so it grows around 30 degrees centigrade. And it's, it's a pretty voracious feeder. These are little flagella. It swims around and eats other things like bacteria. Now, why would you want to study Tetrahymena thermophila? Well, it turns out it has a very unusual genome. So all human cells have 23 chromosomes. They're really giant, big, long chromosomes, and we're diploid. So there are 2 copies of each of those. Tetrahymena has a very different genome structure. It's got 200 chromosomes, and it's got about 45 copies of each one. Now, telomeres are the ends of chromosomes. Our chromosomes are linear, and so the cell does something very unusual in order to make sure the ends are kept intact. So if you want to study telomeres, you could study human cells where there's 46, or you could study Tetrahymena where there's 9,000 telomeres. Well, it turned out this was a good idea. So basic research on how DNA is replicated was possible using Tetrahymena thermophila, and the Nobel Prize in Physiology or Medicine was awarded in 2009 for understanding how cells use telomeres to protect the ends of the chromosomes and the enzyme telomerase that replicates those. Now, some of you might be familiar with our colleague Liz Blackburn, who was president of the Salk recently, and she and Carol Greider did a lot of their work in Tetrahymena thermophila. Jack Szostak did his work in yeast. But this, having Tetrahymena thermophila is what allowed people to find this enzyme telomerase. And it's been, I know all three of these people, they're wonderful human beings and scientists. It's been a privilege to know these people. So there's another thing that came out of this. And there's one particular chromosome in Tetrahymena that was of interest. It only had one gene. And it was very, very short compared to all the others. And there were an especially large number of copies. So we, you know, there was 900,000 copies of this one enzyme. And so studying the transcription, so the making of RNA off of this little mini chromosome, led to the discovery of catalytic RNA. And the Nobel Prize in 1989 was awarded to Tom Cech and Sidney Altman. But Tom studied synthesis of RNA from that chromosome in Tetrahymena thermophila. So there's two Nobel Prizes that came out of studying this little pond organism. Now, there's— I'm telling you this for another reason. There's two connections. So this is a lab photo taken of the Cech lab, the day after he won the Nobel Prize, and there I am. So now, I had nothing to do with the Nobel Prize-winning work, but it was well appreciated that Tom was a major innovator, and if you wanted to learn about RNA, you went to the Cech lab. So I and a group of other people went there to study RNA, and we were thrilled that he deservedly won the Nobel Prize. And the other connection is that that Tetrahymena chromosome that he was studying, the RNA that was being synthesized, that was a catalytic RNA, turned out to— it was the ribosome. So the RNA from Tetrahymena had a self-splicing element in it, but it codes for the RNA component of the ribosome. Small world. Okay, so why did I tell you this? So Tetrahymena is just, it's an unusual organism, and studying it is just what we call basic research. People are curious, you know, you're interested. Why does this work this way? And it's not primarily directed at solving some kind of disease. So 2 Nobel Prizes, there'll probably be more that come out of studying ciliated protozoans, but the point is that basic research sets the stage for all work on human health. That's why we study ribosomes. Okay, so that's the end of the detour. So let's get back into ribosomes. Now, here is an electron micrograph, and it's— we call this a Christmas tree for kind of perhaps an obvious reason. But this is what happens if you take DNA out of a bacteria, you spread it out on a carbon surface, and then stain it with uranyl acetate, uranium ions, so you can see So you can see the long strands of the DNA. Okay. And this particular structure right here is actually the ribosome assembly line. And you can see this is from a paper, and it's one of my favorite papers. It was 30 years ago, I was just starting my career. And all along this DNA strand here is RNA polymerase. And it's transcribing the ribosomal RNA, and these little bits that are hanging off are the ribosomes that are in the process of being assembled. Now, the problem with this image is that you've just completely— it's like you took the factory and you ran over it with a steamroller, and then you're trying to understand what, what's going on by looking at the crushed wreckage of the factory. That's basically what this is. So we'd like to know what are the structures of all of these things that are hanging it off before they got splatted down. So the basic idea is we have the DNA that encodes for the ribosome, and the RNA is transcribed, the RNA emerges and starts to fold up and bind the proteins, and what we would like to see is the order of events. So what is the manual for assembling this structure as it goes along. This is just a, a sketch of the RNA structure. So every RNA folds up, and there are lots of base pairs. There's— this is the 23S RNA, which is part of the large subunit, and the active site which catalyzes peptide bond formation is right here in what we call Domain 5. But this— looking at this diagram doesn't tell you anything about how you would fold it up and assemble it into a three-dimensional structure. So here's the RNA, and I've colored these domains according to the previous diagram, but they all interdigitate. They really just go in, and so it's not like it's an onion that you can just peel back all the layers and then say, oh, you start with the center and fold it up. It's— there's no clue from just looking at the finished product how you would actually put this together. So we're— how can we get that? So it turns out it's hard to find these things in cells. So the— I told you assembly was very efficient, so it's fast, 2 minutes in E. coli. The intermediates are transient, they don't live very long, and they're not very abundant. So it's really hard to just look in cells and find them and use all of these amazing biophysical techniques to, to get at the structure. So the approach we've taken is that we disrupt the process of assembly in such a way that the intermediates accumulate, and then we get to look at them and try to infer the order of events. So I'm going to give two examples today. The first one is We take a protein that's essential for making the ribosome. They all have their boring names. They're numbered, large subunit number 17. So we limited the production of L17, and that throws a logjam into the assembly process. And now we can see what's happening and try to infer the order of events. But why did we choose L17? Now, this is a really complicated diagram. That summarizes a whole bunch of information that was done in the 1970s. So you can make ribosomes in vitro, and there's a— Knud Niehaus was a brilliant scientist. They figured out what order you had to add the proteins. Now, in the '70s, we didn't know the sequence of the RNA. Nobody had figured out how to sequence anything. We didn't know anything about the structure, but Niehaus showed that certain proteins could be added first and then other proteins would bind later. So he kind of got this cascade of events that must be a key to understanding assembly. So for, for decades, this was the Rosetta Stone for understanding ribosome assembly. So we chose L17 because it was right in the middle and it was, it was one of the first things that would bind. And we figured if, okay, if we can, you know, disrupt an early step, we'll have a good likelihood that we can actually see something stalled. Okay, so how do we look at ribosomes in cells? This is what we call a ribosome profile. So we take E. coli, we crack them open, and then we put the cell lysate into an ultracentrifuge and we spin it at 100,000 Gs., and things separate according to size. And so in a normal cell, you see 3 big things. We see the small subunit, we see the large subunit, and then we see the intact ribosome. And we can easily observe them because they absorb ultraviolet light, and it's easy to track them. They're very abundant. This is a great way to purify ribosomes. So what happens when we limit L17? So we now have perturbed cells. So the red trace is now what we see. Well, we see a lot of 30S subunits, small subunits. We don't see so many whole ribosomes, and then we have this huge other peak. What is this? So we think that these are the ribosomes lacking L17. It's a new kind of particle, and so we want to characterize that. And so how do we do that? Well, we use cryoelectron microscopy. So Scripps has a fantastic cryo-EM facility. We have some of the best cryo-EM researchers in, in the world here. We have a world-class set of instruments, and we use a very powerful Titan Krios electron microscope. And this— what you do is you put the particles down on a surface and you take a lot of images of them. We collect many, many images, like a million images. We sort them out and they all give different views of the ribosome, and you can use very sophisticated computational algorithms to generate an electron density map from, from all of those images. Now, we were not an expert at this, and so we collaborated with Dmitry Dmitry was a graduate student here at Scripps. He's now associate professor at the Salk, and we've collaborated with him for many years. Improvements in the hardware and in the algorithms have led us to be able to purify many, many different structures out of the same sample, and it's been an extraordinary experience. Okay, so what did we see? Here's the first kind of thing that we saw. We found 4 major kinds of partly assembled ribosomes, and I'm coloring them, so the electron density map is colored, and then when you see a ribbon, that's the final structure. So if you see the ribbon, it means that part isn't made yet. So we see things that are almost completely done on the right, and then on the left we see things that are about half done. So you can see the whole front face of this particle is, is just missing. And, and so that's a 50% assembly. And then we see a couple of other different things, but the, the main takeaway from this was that we see a branched pathway. So presumably we make this first, and then we can make either red— sorry, either yellow or green, and then both of those can convert to blue. So that was a real surprise. First of all, this was the first time anybody had seen an intermediate. What did it look like? And second of all, we learned that there were complicated branched pathways. So how do we organize this information. I showed you this diagram before. We also call this the roadkill diagram. So this is— you can imagine taking the structure and just steamrolling it and you splat it out on the road, but it allows you to diagram things. So here are the domains 1, 2, 3, 4, 5, 6. But when we look at the structures that came out of the electron microscopy, for L17-deficient ribosomes, what we see, there are certain blocks. So block 1 is that early thing that I showed you, and then you can add block 2, which has 2 different regions, block 3, and then block 4, and finally block 5. So we were able to deduce the order in which these sequences folded into the final ribosome. Okay, so here's 3 different views of that kind of information. I'm showing you the roadkill view, and then layered on this— so these lines are where there's base pairs between remote regions. So the reason this blue and this blue happen at the same time is because they actually interact in the 3-dimensional structure, and you can see that over here. This is the blue Okay, and likewise the red. So there's distant regions that come together in space and interact, and that forms this red region here. We can also organize all of this information onto this Nearhouse protein binding map, and everything that we learned was completely consistent with what had been found in the '70s, except now, I mean, that was only looking at the proteins. Now we can see what's the RNA doing. The RNA is folding up and we make this whole domain first. Okay, so let's, let's take another look at perturbations that tell us something. So I told you that we have a parts list and that you need some tools in order to help assemble the ribosome. Well, these tools are actually proteins that that assist in the assembly in some ways. And in E. coli, there's about 35 of these different proteins that participate. There are proteins that modify the RNA, introduce methyl groups at specific places, but there's, there's about 5 helicases. These are enzymes that modify RNA structure using the energy of ATP to help chaperone folding. So we picked one of these, and we used a genetic knockout of the helicase DEAD. And again, here's this ultracentrifuge separation. And what we, what we looked at when we delete delta DEAD is this peak at the center. That's a new peak. And then we use cryo-EM to see what happened. And this was, this was quite remarkable. This is all hot off the presses where this work is pending review to be published. But we were able to see a whole new set of structures. So the very earliest things, and this is actually Domain 1, it's the very 5' end. And we see all kinds of other intermediates. So we're really getting snapshots across the whole assembly process. And between the DEAD and the L17, we've pretty much spanned the entire assembly process. Okay, now how do we organize this information? Now, I don't expect you to remember this diagram, but I think I'm showing it for a reason. It's complicated. And you can imagine if I gave you the assembly instructions for a car, it'd be about 6 inches thick. And you, you know, there is such a thing, but how do you actually distill it down into a single picture? Well, it's challenging. So what I've tried to do is say, okay, here's one end of the RNA and here's the other, and it's synthesized over here, and you make each domain in succession. And what we see on the right are the structures and the blocks that we've inferred from all of this electron microscopy. And then all of these boxes are those proteins that Nierhaus found, you know, 50 years ago that are binding. And what we can tell is that it actually starts at the 5' end and gradually assembles all the way to the 3' end. And the intermediates that we're seeing from all of these structures are completely consistent with this paradigm of making one end first, and you assemble in the direction, okay, in the direction of RNA synthesis. So this is a remarkable thing to see. And, you know, we literally— I've been working on this for 30 years, and it's just really thrilling to sort of see that we got— we almost have the instruction manual down. Okay, let me, let me make a, a couple of comments. So why does it work this way? Uh, I've used the analogy to the automobile assembly line several times, but you— there, there's a problem with an assembly line. So everything has to move from one step to the next, and if there's a problem, everything halts on the assembly line. So if, if there's a problem at this step then everything has to wait until you resolve that problem, and then you go forward. So that's, that's maybe not the best way to design things. Equally bad would be if you just put things in any, any random order. So what if, you know, what if the assembly floor was just people trying to put hubcaps on before the wheels were there, and steering wheels in before the chassis is there, the doors on it before there's the frame? That doesn't make any sense. You can't just have a random order for things. So stepwise has problems, random has problems, and so what biology has done is to use parallel assembly. So there's some flexibility. Well, you can do a couple of things and then you can do a couple of other things. Probably no one ribosome goes from here to here by the same pathway, and you know, if this step's a little slow, the other ones might go this way. Okay, so this parallel and sequential balance gives you some flexibility in how things go without having just total chaos. You know, this is sort of the Southwest Airlines hub model, and this is United Airlines. Okay, maybe that's a different way to put it. So one of the things we've learned is that biology has adapted to have some flexibility and not an exact order of steps, but there is a trend. Okay, let me come back to this, this micrograph, and this was again work done in the 1990s, and each of these little pendant chains off the central DNA is a partly assembled ribosome. And over the course of several decades of work, what we've been able to do is identify the structures of what each of these things looks like and the rough order in which they're, they're put together. Now, the last thing that we want to do in this process is— this, this is the steamroller picture of this. How is this organized in 3 dimensions in the cell? And so we're, we're now collaborating with Danielle. I mentioned her right at the beginning, but we want to go in and find this assembly line in the cell and see how is it organized in 3 dimensions. It has to be a very special place in the cell to do all of this at such a high speed with high efficiency. So that's for us the next frontier. Okay, now I've showed you all of these images. But this is a continuous process. I mean, this is happening, new ribosomes are being made and it just goes from stage to stage. It's very dynamic. All we can do is take snapshots of it. And so I wanted to just illustrate this with a point, which is you can't tell exactly the dynamics from looking at these beautiful pictures. And this is a surf trip that I had last fall. A sharpshooter was on the beach and I managed to get this photo, but it really illustrates that there's stuff happening. The waves moving, I'm moving, it's— everything's changing, but all we have is this picture. And so what happens next and how do you see that? And so integrating this striking series of images that we've been able to have is one of the goals that we also have to achieve. Okay, I made a pitch for the role of basic research in medicine. So at Scripps Research, we have amazing faculty, we have amazing facilities and instrumentation, and we have amazing administration. And it's, it's a, it's a, it's a hive of activity. And what we do is we bring in young scientists, graduate students, and postdocs, and we generate resources through federal grants or philanthropy. And we attack important problems in biology, and the output of all of that is really 3 kinds of things. First of all, we publish papers, we disseminate our results, we publish the papers so that everybody else can read them and build on our work. We add to the base of human knowledge. The second thing we do is we train people, and we produce scientists that go off and do other science at other places. And we also, and you know, there we've had some tremendous successes in making medicines here at Scripps. We have some amazing faculty that have produced new medicines, but most of the faculty at Scripps are either trying to make medicines or just doing basic research. And it's really important to understand that has a key role in supporting the whole enterprise of medicine. So I'll illustrate. Here's 4 people that trained with me. Joey Davis was one of the principals that did our first electron microscopy work on, on the ribosome. He was the first author on our 2016 paper that I briefly mentioned. Joey's now an assistant professor at MIT in the biology department. He's working on his own stuff, and that's arguably one of the best biology departments in the world. Phil Zamore, another trainee, he was a postdoc in my lab. He's now the chair of the biochemistry department at the UMass Medical Center. Phil is also a bit of an entrepreneur. He was one of the co-founders of Alnylam, which was one of the first companies to develop RNA therapeutics, and it's an extraordinarily successful company. And then the last two guys, Pat was a graduate student in my lab and Dan was a postdoc, and they co-founded a company right here in San Diego just in the past couple of years called Recludix. So these are the next generation of entrepreneurs. All of these people trained in my lab studying RNA, basic research, and they've all gone off to either academia or industry. And one of the best things that we do at Scripps is train these scientists to go off and do their own thing. So it's a multiplier. It's not just what they did, it's what they're going to do next. So let me just close and say a couple things about ribosome assembly and disease. So some— there are some well-known diseases in humans that are defects in ribosome assembly. So if you have a genetic defect that's really bad for making ribosomes, then it's just lethal. And so these diseases of ribosomes, they're called ribosomopathies, are very subtle defects in making ribosomes and in protein synthesis that lead to some very serious medical conditions. And these are 3 syndromes that are linked to ribosomes. A bunch of anti-cancer drugs actually inhibit ribosome assembly by inhibiting the transcription of ribosomal RNA. And the same thing with— I showed you all the antibiotics that work on the ribosome. But all of these drugs were discovered by random screening. So nobody said, I think I want to inhibit ribosome assembly, and so I'm going to, you know, find a drug that does that. So these were found after the fact as really potent ways to interfere with cell function. And so I'm hopeful that the kinds of things that we're doing will give the opportunity to find specific inhibitors that block ribosome assembly in bacteria or in cancer cells, and that the basic research that we're doing will serve as a platform for for us and for others to make some new medicines that have a new mode of action. Lastly, I need to thank the people. This is my current lab, wonderful group. All of the EM work was a combination of people, Jessica and Kai and Shi Yu, have all done the electron microscopy work that I showed you. And we have a whole bunch of other projects that I didn't have time to talk about, all based on RNA. And it's just a terrific environment to do science here at Scripps. So with that, I'm going to conclude. Thanks for your attention. I hope you found the ribosome interesting.

It was very interesting. Thank you, Jamie. That was a wonderful talk and some, you know, just great visuals there of the ribosome assembly. So, you know, we've got some questions coming in. And I think I'll just start by sort of asking, you know, with respect to the different ribosomes there at the beginning, you know, you mentioned that human ribosomes are slightly different from the bacterial ones. So, you know, what is the difference there with the assembly process.

Right. So I mentioned the difference in the context of antibiotics. So if you look at a human ribosome, it's recognizably a ribosome. There are some parts that are absolutely conserved with bacteria, and there's some— the stuff on the outside has been changed a bit. So that's all well and good. And that serves as the basis for the differential effect of antibiotics on bacteria versus humans. What's really remarkable is that the whole process of ribosome assembly was completely re-engineered. It's nothing like what happens in bacteria. It's hyper-elaborated. It's almost like you gave Congress the the power to change ribosome assembly, and it came up with this incredibly arcane, budget-heavy system to make ribosomes. So there's all kinds of different factors, it's highly regulated, it's just incredibly complicated compared to what we see in bacteria. So, and we, you know, we aren't working on that. There's a number of really big labs that are working on human ribosome assembly. It's a fascinating problem., but it's completely re-engineered.

Wow, amazing to see that difference. And so sort of a follow-on from that, we've got kind of a question about the, this really interesting concept of the parallel assembly and this flexibility. So, you know, do bacteria have this kind of flexibility? Is that why some species might be so difficult to target?

Yeah, that's a really— so that's a rich question. So everything we've done has been in E. coli, and so we don't know if bacteria have sort of engineered ways to, you know, fly under the radar and assemble their ribosomes in some different way. You know, in particular, you know, you think about in that you got a microbiome in your gut, you have 100 different species, right? And they're all competing for resources. So if somebody can figure out how to inhibit somebody else's ribosomes, or if somebody can help figure out how to grow faster, they get more of those resources. So I imagine there are some surprises, and one of the things we want to start doing is looking at other species to see, okay, how much of what we saw is general and how much of it is specific to E. coli. We have a show about that. If you look at all of those helper enzymes, about half of them are conserved in all bacteria, and the other half are unique to E. coli.

Ah, so there's some hint that there's some real differences. So with respect to therapeutics, then, could we potentially be knocking out those little helper proteins instead of the ribosome itself in those specific species?

Yeah, and I think that's one of the strategies that could come out of this work, right? Is those helpers bind and do something and then come off. And if you can prevent them from doing that, that's a really potent inhibitor. And so it may be, you know, trying to bind to the RNA could be— that could be pretty difficult, but maybe inhibiting those specific factors for a particular pathogenic species. That's probably a strategy.

Sure. Yeah, I'm sure it's a great topic of interest because there's this growing idea now, isn't there, that we need to be not just nuking our own microbiome with these very broad-spectrum antibiotics, but trying a more narrow-spectrum approach.

Yes. Yes, indeed. Absolutely. And there's some particularly troublesome pathogenic bacteria that that are resistant to antibiotics, and we need new antibiotics. There's—

it's a never-ending war. Sure. And sort of a war with other sort of diseases. We got like a lot of questions here about cancer. So, you know, is there any difference in ribosome assembly actually as the cancer grows and metastasizes as well?

That's one of the questions. I mean, I don't think we know, I don't think we have a very clear picture about how the process of ribosome assembly evolves with different cell differentiation. A lot of work is done in yeast or in just human cells in culture. But, you know, there's a lot of complicated morphology to tumors, right? They're trying to get blood vessels, they're hypoxic, and there could be some really interesting physiology of tumor cells that that goes down to how do you make ribosomes under these stressful conditions for them? That I don't think we have a really good handle on that.

Right. Yeah, I mean, the cancer cell is just sort of an extension of us in many ways. So it's, it must be very tricky to, you know, block that and not be damaging our own cells.

Sorry, Drew, you froze on me for a second. Could you repeat that?

Oh, am I here now? Yep. Yep. So I was just thinking, yeah, you know, the cancer cell is an extension of us, so it must be very difficult to be blocking these cancer cells and not damaging our own tissue.

That's right. And so the basis for that selectivity would, you know, it would be targeting molecules to those cells and then taking advantage of the fact that they're trying to grow faster and they're, they're probably making ribosomes a little bit faster. So you want to tickle that. And I think, you know, also combination therapies are a good, good way to go. That, that, you know, if, if there's any— if you can impact protein synthesis in cancer cells by 10 or 20%, that could be huge in combination with other, uh, with other chemotherapies.

Right, right. Yeah, I think combination therapy is definitely the way to go right now. So, um, we do have a, uh, as kind of a question, is sort of the contrary to that, which is actually about increasing ribosome activity. So as opposed to blocking it in cancer, you know, do you think there's any way we could boost ribosome activity and maybe protein synthesis to fight off some of these problems with aging, like muscle loss?

Yeah, that would be great. Yeah. You know, I think, I think there's there's a good opportunity to understand how you could positively, you know, affect, so allosterically affect ribosomes, maybe not at the level of assembly, but perhaps at the level of protein synthesis. So, you know, these ribosomes hang around for a long time, they're really expensive to make, and once you have an inventory, you keep it. And so probably if you want to boost protein synthesis, you want to find ways to stimulate the ribosomes you already have rather than just make more, because that's actually taxing. I see.

So kind of wake them back up again. Pardon me?

Kind of wake them back up again. Yeah, right, right. And/or increase the rate of translation. I mean, everything is kind of balanced, you know, in the cell. You make RNAs at a certain rate, you make the proteins from those RNAs at a certain rate to generate the amount of protein you need for that particular cell type. So there's this balance of all of those things, and you could tweak that balance, right?

So you were saying, you know, how ribosomes are very challenging to look at. And thinking back to the earlier conversation with sort of digital medicine and AI, uh, you know, could you foresee any way of having a test for ribosomal activity and perhaps used as like a diagnostic for cancer or other other diseases?

Wow. You know, there are well-known mutations that locate to ribosomal proteins and some to the RNA. So there are, and in fact, some of those, I mentioned those syndromes like Treacher Collins syndrome, that's a perfect example where there's defined mutations that seem to give a problem in ribosome synthesis. So yeah, I think so. But I think, you know, the Cancer Atlas, so here's the funny thing about working on ribosomes. A lot, you know, somebody does a complicated experiment, and they find all this genetics that points to the ribosome, and they throw it out. They're looking for the transcription factors or the cell surface receptors that, you know, are drug targets or, you know, are regulating genes. And so ribosomes tend to go to the dumpster. And there's probably a lot of, you know, really amazing information about how making ribosomes or the activity of ribosomes is modulated in disease that's not really appreciated except for these very small number of cases that are syndromes.

So is anyone coming up with the new atlas of dumpster materials so that you can go dumpster diving for all these different ribosomal signatures?

I will say that one of the things I've learned over the years is that being the janitor of the literature is not a rewarding scientific endeavor.

That's fair enough. Fair enough. Okay. Well, we have a couple more questions, but I think we need to wrap up now. We're coming up on time. So we will have the transcript of these and we'll try to get back to to anyone here if we can by email after the talk. But yeah, we want to just thank you all for tuning in. And Jamie, thank you again for such a great talk. Well, Drew, thanks for hosting. Yeah, of course. It was great to see what you do on your day-to-day basis. And I will just say a final thing is our next Front Row lecture, rather, is next month. So in February, we'll have one of our premier neuroscientist, Professor Sandra Encalada, who is going to tell us all about the fascinating transport system in the brain and what this kind of means for neurodegeneration. And I will just say that Professor Encalada was in fact a guest on the podcast quite recently, and we have a whole new season of episodes rolling out at the end of this month. So be sure to sort of take a listen and kind of get to know more from the people, you know, who, who do these discoveries every day. So I want to thank you all again for being here, and we'll see you next time on The Front Row. So thank you and goodbye, everyone.