Ying Lu
Description: Ying Lu is an Assistant Professor in the Department of Systems Biology at Harvard Medical School. His work combines physics, biochemistry, and quantitative methods to understand the fundamental mechanisms of biological processes, particularly protein degradation. In this episode, we discuss why curiosity is the most powerful engine for scientific breakthroughs, from the discovery of CRISPR to modern weight-loss drugs. We explore the cell’s sophisticated quality control system, where a "barcode" tag called ubiquitin marks unwanted proteins for destruction by a nanoscale "shredder." Professor Lu explains how failures in this system are linked to diseases like Alzheimer's and cancer, and how his research could lead to new therapies that either inhibit or boost this process to restore health.
Websites:
Department of Systems Biology Profile
Publications:
Episodic Transport of Protein Aggregates Achieves a Positive Size Selectivity in Aggresome Formation
HUWE1 Amplifies Ubiquitin Modifications to Broadly Stimulate Clearance of Proteins and Aggregates
Principles, mechanisms and functions of entrainment in biological oscillators
Mentions:
Care Equity - Private Equity Firm Professor Lu Advises
Ozempic Literally Came from a Monstera
Video Explanation of Ubiquitination of Proteins & Protein Degradation
Show Notes:
[0:07] Introduction
[0:49] The Power of Curiosity in Research
[5:34] From Physics to Systems Biology
[7:46] Understanding Mechanisms in Science
[10:31] The Balance of Mechanism and Big Picture
[15:15] Protein Degradation vs. Synthesis
[21:59] Ubiquitin's Role in Cellular Processes
[24:22] Autophagy and Its Selectivity
[32:15] Environmental Influences on Protein Degradation
[34:16] Translating Research into Human Health
[40:04] Inhibitors vs. Activators in Drug Development
[44:13] Current Status of Pharmaceutical Applications
[47:51] Future Directions in Research
[48:07] Bridging Academia and Industry
[56:00] Final Thoughts and Advice for Young Researchers
Unedited AI Generated Transcript:
Brent Valentine:
[0:00] Welcome back to Discovering Academia. We are two college students who travel the world talking with academics about their research, passions, and current events. Today we talk with Ying Lu, a professor of systems biology at Harvard Medical School.
Keller Kramer:
[0:13] His work combines physics, biochemistry, and quantitative methods to understand the fundamental mechanisms of biological processes, particularly protein degradation. In this episode, we discuss why curiosity is the most powerful engine for scientific breakthroughs, from the discovery of CRISPR to modern weight loss drugs. We explore the self-sophisticated quality control system, where a barcode tag called ubiquitin marks unwanted proteins for destruction by a nanoscale shredder. Professor Liu explains how failures in the system are linked to diseases like Alzheimer's and cancer, and how his research could lead to new therapies that
Keller Kramer:
[0:45] either inhibit or boost this process to restore health. We hope you enjoy.
Brent Valentine:
[0:49] Welcome, Professor Ying Lu. Thank you for coming on today.
Ying Lu:
[0:53] Thank you. So thank you for this opportunity and also thank you for organizing this wonderful webinar series. It's terrific to bring people in academia and to more audience. Thank you very much.
Keller Kramer:
[1:09] We'd love to start off by hearing why has it been so important that curiosity be the main driver behind all of your research?
Ying Lu:
[1:16] Yeah, so this is a wonderful question. I think throughout my career, most of my work, most of my research has been curiosity-driven. And so there are many important reasons. So I would like to just start from some recent examples, for example, CRISPR and also this popular drug, a GLP-1 agonist. In CRISPR, we all know that that was originated from the study of bacteria immune system, that antifage immune system. It does now, that did not appear to have a strong connection with the applications, but it turned out to completely revolutionize the way people do research, and then in gene therapy, in cell therapy, etc., etc., such a big impact. And I mean the JLP1 drug, the development of that drug actually originate from the study of a lizard, how that lizard actually would withstand extreme drought and famine.
Ying Lu:
[2:16] So that doesn't seem, I mean back to that day it's not seem to be strongly connected with application but it turns out to be another amazing sort of thing that comes to being. So in summary I dare to say that the most influential impact for people, findings in my field originate from the curiosity-driven research. So I think this is one important reason to summarize. I think the curiosity-driven research likes to explore unknown territories, just simply the reasons. For example, if you imagine a well-trained person, if you find a question which is completely unanswerable, curious, so that usually means that this is sort of uncharted or unexplored territories in people's knowledge and then sometimes that's also a gateway to the entire new world like the world of leading people to Naniya so this is completely a different thing so that I would say the gravity driven research sometimes can lead to a breakthrough discoveries I think that's actually have a strong impact and benefits so another also important reasons for that is probably the.
Ying Lu:
[3:38] Motivation for doing curiosity research actually lasts longer because science is hard and the experiment fails the funding, could be rejected and so on so there are a lot of frustrations but the curiosity, people's curiosity tend to last longer than that so that actually it could be quite important to help people, for them to get enough motivations to even to overcome those transitory difficulties and then to at least to them to say to true understanding or to eventually getting the problem solved.
Keller Kramer:
[4:22] Is that curiosity something you always had or is that something you developed when you were doing your studies?
Ying Lu:
[4:29] Yes, that's also, I think, I think curiosity is a fundamental human nature, right? Everybody has curiosity, even our kids, they are very curious. And they want to know how things works and how things happens. And they are intrinsically curious about, I would say that curiosity is a basic human nature. But also as we grow up, there are so many other things that we have to care about. And sometimes the curiosity will not be placed as the top priority in our work. And so one advice that I would have to young people is probably try not to let this curiosity go away. Just try to intentionally foster or cultivate this curiosity. I think they all benefit the people, either in academia or outside academia, in one way or the other. So this is really a valuable character that nature deals with.
Brent Valentine:
[5:34] Could you walk us a little bit through your background from physics and then eventually ending up in systems biology?
Ying Lu:
[5:41] Yes. So it's a long story. So I was originally trained as a physicist, and then I studied constant matter physics. And then at that time, I have a limited sum, a limited explorer to biology. But I'm very curious because I have a family tradition. So both of my parents work on health care. And then I get used to that environment and the knowledge since I was an early age. Then I did my PhD in Belfast program at Rockefeller University. And then I started to get more explore to biology or more systematic education and training to biology. But I'm still thinking about how can I possibly combine physics and biology or apply what I learned in the past into solving some challenging biological questions. And so to deepen my, education and training so I moved on to Harvard Medical School and to study biochemistry and microbiology and then I stayed at Harvard Medical School in the Department of System Biology as a, assistant professor and then to continue my research.
Ying Lu:
[7:06] So there have been gradual transitions of my work going from almost entirely physics modeling driven to somewhere in between, half and half. And then now is more sort of focusing on solving biological questions, but using physical methods and tools. And then, thirdly, we also create new methods and new tools based on my quantitative background and then try to apply that to solve the most important biological questions.
Keller Kramer:
[7:46] Could you explain kind of the role that fundamental science has in our broader understanding of science and kind of with that, the important role that understanding mechanisms plays in biological processes?
Ying Lu:
[7:59] Yeah, I think that's a very good question. And then I can explain that. I can probably, I can say, explain that using different ways or from different angles. I think one thing that our department of system biology that really focuses on is to try to identify what are the things we call mechanism. Mechanism will call different... You can also call that deep understanding of how things happen. So this is very important in almost any subjects or almost any...
Ying Lu:
[8:48] Research areas, and I think in particular for biology, you know, you are typically a biological discovery that begins with a correlation. For example, we find there are some diseases that occurs, correlates with the, for example, the change of temperature or, for example, the change of people's diets, so on and so forth. So this is a correlation, right? So we don't know whether this is really, there's a causality between or this is just simply correlation, right? Maybe in many cases, it's simply correlation. So, but in order to translate that, transition that into a therapy and then try to, or to try to understand whether this X actually leads to Y. And so we need a mechanism. So we need to know how things work, and then we'll then provide the changes of people's diet, eating behaviors, which somehow cause a certain type of disease, whether there's any causality. So we have to understand what part of our human body, if it goes wrong, will cause that type of disease, like diabetes, obesity, so on and so forth. And so this is because of mechanism so essentially it's seeing how it's basically the interpretation fundamental interpretation of how things work or how things could happen.
Ying Lu:
[10:17] And so this is an important part of our research and try to understand how things work or in particular in my own lab is to understand how the protein degradation system works,
Ying Lu:
[10:30] yeah and.
Brent Valentine:
[10:32] Then do you think the focus on mechanism can ever go too far
Ying Lu:
[10:36] Where researchers.
Brent Valentine:
[10:38] Get siloed into a certain way of thinking and they lose track of the larger picture
Ying Lu:
[10:46] Yes, that's also a question or I think an issue that many people brought up. Yes, I think you are right. That if this, study a mechanism, probably there's never going to be an end. There could be a mechanism, and then there could be a mechanism of mechanism. There could be a mechanism of mechanism of mechanism. The things could be very deep and could be very detailed. And if a researcher, a magnetist researcher like myself, want to go into that route so I can spend decades on a single question become deeper and deeper and deeper. And then, as you said, unfortunately, a sad effect of that will be losing the big picture. I wouldn't know how my research would be able to translate or be able to benefit the society. Although, I think it does probably solve the fundamental questions, but it gets a penalty of that. It gets detached from the society, which is not good, I think, for the well-being of one research lab and also not for good well-being of the entire research society as well.
Ying Lu:
[12:09] And so that's why I think that may connect to your following questions that I think having experience and having knowledge in life science industries actually helped tremendously in connecting my own research and connecting my mindset, lines of thinking. With how our research could better benefit society, could translate. So why people are being sinking into very tiny details to just keep the, as I said, keep the big picture in mind.
Brent Valentine:
[12:45] Do you think enough fundamental researchers keep their potential translations in the back of their mind? Do you think that area is too focused broadly speaking or do you think they have they do a decent job of being like this is why i need to understand this mechanism for like these broader applications
Ying Lu:
[13:08] Right i um so my experience is this um um so in this environment where i was trained i would say since my undergrad and my phd uh, almost everyone around me. They're all very great scientists. And so their research is, I would say during that period, the academia and industry is somewhat independent. So they are moving with their own pace. So they don't really have a lot of overlap, at least in visiting the environment that I got trained in.
Ying Lu:
[13:50] And then usually the people around me those great scientists when they try to ask questions and then they try to define their research areas, they tend not to think too much about whether this is going to be important, whether this is going to translate into important therapy, but you know what, very often these things can be translated eventually into, important therapy or some kind of medical device but this may not be done but this lab per se were maybe done by some other labs that happened to read their publications and then find oh this is so interesting to me I would continue working on that, so but the people around me are mostly focusing on the basic questions as we call them curiosity driven research so they would search around and then they find whether there is important unknown territories as there has been uncharted research areas that have not been explored before, then let's just go into it and see what we can find. And then, interestingly, this is how science works. And very often, this seemingly trivial and then just completely curiosity-driven studies actually can be translated into something very important.
Keller Kramer:
[15:15] Then diving into your work specifically, you mentioned protein degradation. Could you compare and contrast protein degradation and synthesis?
Ying Lu:
[15:24] Oh, yes. Protein degradation and synthesis is like the yin and yang of the two sides of the same coin, I would say that. Because in order to precisely control the protein levels, right? So they need both the precise control of the synthesis rate and also the precise control of the degradation rates. And I think the synthesis system and protein degradation system are also strongly coupled, and then they talk to each other. And they are both intimately connected with human diseases. So there was estimation roughly 40 or 45% of human diseases due to failure were malfunctioning of the decodation system, those machineries, which is not surprising because those quality control and then decodation systems is indeed quite important roles in almost all aspects of cell biology, human biology.
Brent Valentine:
[16:34] So how does, just for like maybe the audience that might not fully understand biology, what do the processes look like at a high level?
Ying Lu:
[16:45] Yes. So how this degradation works is typically what we talk about is we call them regulatory degradation or precise or precision degradations, simply speaking. And so we are not talking about this protein degradation which is non-selective, for example under stress conditions, cells may undergo, autophagy process that degrade a whole chunk of cell cells, so it's non-selective, but under the normal conditions, the proteins need to their levels, their stability needs to be regulated so usually the beginning of this degradation process is the cell would recognize what things need to be removed and then there's a demand.
Ying Lu:
[17:35] So, and then how the cells tell the degradation system which protein to be removed is by putting a tag. This tag is called ubiquitin. Ubiquitin is a small protein.
Ying Lu:
[17:47] So this ubiquitin gets covalently coupled to the target proteins but this ubiquitin can form a chain and then there are usually multiple chains The chains could have different topology. So they have a variety of different forms, a large number of different forms. So there's some people who have called that built-in code. So you can see this as a barcode that the cells put on the protein target that needs to be removed. So this barcode contains the information that tells the degradation system how this protein needs to be degraded and when it needs to be degraded and what rate needs to be degraded. So presumably all the information is out there. It's just that the degradation system, for example, the key degradation machinery is the protein cell, which is a nanoscale. So you can see that it's a nanoscale machine or nanoscale robot in the cell that consumes energy. And then they recognize this barcode that's put on the protein targets. And then every second, there are hundreds of millions of protein molecules in each cell that need to be removed or recycled by this machine. So it's a large number of different molecules need to be done.
Ying Lu:
[19:05] And then they all go through this protesame system and then this nanoscale machine will recognize that barcode and then engage these protein targets unfold them translocate them into the central chamber just like a shredder and then cut them into pieces and then those pieces get released, from the protesame eventually and then that gets recycled back into new assays, So this is a brief overview of how the degradation actually works.
Keller Kramer:
[19:38] And you mentioned that there's different, I guess, like ways that it gets degraded. And you said, you know, removal and recycling are at the end of the day. Is it all or the amino acids all end up being recycled or do some of them just get removed fully from the system? Or do we what do we know about like those distinctions so far?
Ying Lu:
[19:58] Yeah, yeah. That's actually a very interesting question. It's also active research areas. And so there are multiple ways this things could work. And I think by a bulk...
Ying Lu:
[20:16] In the ballpark, so most of those proteins that are degraded, and then their amino acids get recycled back into the system to build more materials. But there is a small fraction of those peptides that's cleaved by the proteasome from those target proteins play a very important role. So what they do is they get presented to the immune systems, right? So we all know this T cell receptor, how those things work. And then those T cell receptors, and then, sorry, the MHC complexes on the cell surface, and then almost every cell, and then those MHC complexes would present pieces of the proteins inside the cell and tell the immune system, okay, this is, am I in the normal state or in the abnormal states? And the immune system would deal with that dysfunctional cells. So this is how those things work, has been simulated very well. And then, so that piece of peptide presented by the MHC complex are actually from, mostly from the protosomal degradation. And there's a tiny fraction of those peptides gets translocated to ER and then they bind to MHC and then presented to the cell surface. So without the protosomal degradation, there's essentially, you can say there's no immune presentation.
Brent Valentine:
[21:38] So on that, if we think about ubiquitin getting tagging internal organelles for degradation, some of those going out to be presented to the T cells, would that be how the larger cell as a whole would get degraded if it needs to?
Ying Lu:
[21:59] Oh, yeah, to some extent. Right, to some extent. So this is a part of the immune recognition. And then, so this peptide presented, degraded by the proteome and then presented on the cell surface. You can think about this as a barcode of the cell itself, right? For example, if there's cancer cells, you know, cancer cells, there's a chaotic state. and then the degradation machinery sometimes behave very differently from the normal cells. You know, there's also a creation of cancerous fusion proteins that does not exist in normal cells. So those created, we call the neoantigens, which means the antigens that's not there in the normal cell, but in the cancer cells. And then on the cancer cell surface, so those can be recognized sometimes by the T cells. and then if they recognize that as a new antigen, they will kill the cells. So that's actually an important mechanism as our natural defense mechanism to prevent cancer from occurring.
Keller Kramer:
[23:06] You mentioned that 45% of the diseases we know are related in some fashion to degradation. I know that maybe isn't specific to protein degradation, but within protein degradation, do we know if there is a failure in the degradation system, how much of that is coming from ubiquity versus... Proteasome?
Ying Lu:
[23:31] Right, right. How much of that was from your building or proteasome? So this could be, yeah, I think the answer is hard to give a general answer, but usually there are two main degradation machineries. One is the proteasome, and then the other is autophagy degradation system. So both degradation systems are controlled by your pecuniation, although there are some ubiquitin code, bar code leads to autophagy adaptation. But they are controlled by ubiquitin. They're both controlled by ubiquitin. And also as well, there are diseases, human genetic disorders, for example, that mutations cause which is more associated with autophagy system.
Ying Lu:
[24:20] And then they are also more associated with perisome system. So we can find both examples. And then they cover a broad spectrum of human disorders, like neurodegenerative diseases, even neurodegenerative disorders, type 2 diabetes, for example. So there's a variety of different human disorders that people can find a root in some problem with the calculation machine.
Brent Valentine:
[24:49] So is autophagy always the entire cell, whereas proteasome would just be specific targets within the cell?
Ying Lu:
[24:58] Not always. So there are several types of autophagy. So there's one traditionally known autophagy called microautophagy. So that usually means the removal of a chunk of the cellosolid. Content without much selectivity. So even that micro-autophagy, they're not entirely non-selective, so there are some evidence that may be partially selective or partially non-selective. But there are also branches of autophagy that are very specific, very selective. For example, ribophagy, or ribophagy means the removal of ribosome, defective ribosome by autophagy and or mitophagy which means the removal of defective mitochondria by mitophagy so those kind of by autophagy so this process are controlled by inclination and then they are very specific they only remove the defective content, so yeah as I said so autophagy can be selective and which probably not surprising most of the selective autophagy also controlled by inclination.
Brent Valentine:
[26:13] And then if we're thinking about proteasomes breaking down the protein similar to like a ribosome building a protein, is there an analogous structure in autophagy that's breaking down the targets?
Ying Lu:
[26:30] Autophagy autophagy works a little bit differently because autophagy the yeah that's actually an interesting question so the proteasome and, ribosome, the protein creation and there's actually quite a lot of similarities. The structures are very different but if you're talking about the physical principles behind this or the we call that design logic behind this machine erasers. There are some similarities. But autophagy, interestingly, seems to work by different rules. And I think it has been less studied, but usually autophagy is the initiation is a high density of your building chains on the targets. And usually those targets are hard to be removed. They're big, they're hard to be removed by the protocol. And then that triggers a series of downstream reactions, events, that eventually cause that target to enter the endosome and lysosome, and then they are degraded by the protease inside lysosome. And so this is typically how the autobody works. But proteasome and protein synthesis are controlled by protein machines.
Ying Lu:
[27:52] So they are the machineries, they are the nanorobots in the cells that control this process. Certainly, the question is why the nature actually designed or actually evolves those kind of machine-like entities to carry out these important tasks. So that's, I think, a deeper question. So there are many answers to that. I think one is those machine-like entities in contrast to, for example, 10 or 20 separate enzymes carrying out the same reactions, why the thing doesn't work that way. So this assembly line like protein machines, I think they are either to achieve, we call them, control precision. So, they are good for ensuring this process happens precisely. Because like the protein synthesis or protein translation or transcription, so there is a proofreading steps. So, if things go wrong, then the ribosome and the polymerase could backtrack and correct the mistake. And then there is also similar steps as the proteasome. So I think the all probably engineer has been involved to make sure that this important process actually happens reliably.
Keller Kramer:
[29:16] Do we know what role genetics or epigenetics play in protein degradation?
Brent Valentine:
[29:22] Yeah.
Ying Lu:
[29:23] Yes. Yeah, this is... I'm not aware of any direct role of genetics, certainly genetics and epigenetics, everything. And then they close the synthesis or creation of the machineries, proteins involved in protein degradation. You know, all those things we mentioned, and then the proteasome, ribosome, they come from the genes that needs to be transidated proteins. And then, so in that respect, this epigenetic and the genetic regulations are very important. So eventually, this whole thing is a feedback, right? So, and then, yeah.
Brent Valentine:
[30:09] And then are there environmental factors like fasting per se that cause more ubiquitization or cause more protein degradation than other things or like maybe heat,
Ying Lu:
[30:22] That type of thing? Yeah, this is a little bit outside my field. I think mostly what I read or what I know is, so I have not directly looked into the effect of nutrient or heat in this degradation system, but I think the short answer is definitely. So the nutrient levels and fasting and the stress conditions play a very important role in controlling there's multiple pathways like mTOR pathways like AMPK signaling cascades that are very important in controlling the rate of protein turnover which could be both protein synthesis and protein degradation and then to help the cell to maintain a homeostasis but you can ask how the proteasome system actually play a role, in response to nutrients levels, starvation. I think this is actually an excellent question. It's actually an active research area at this time.
Brent Valentine:
[31:27] The reason I asked that was, I know in the health space, a lot of people talk about fasting, causing autophagy after a few days. That was kind of the impetus on that. I didn't know if we understood any of the mechanisms beyond just we can see that there's less cells. like,
Ying Lu:
[31:47] There's some understanding, but I think there is still a lot of important basic questions that remains. Probably not surprisingly, the cells have evolved a very complicated machinery to sense the nutrient levels. The cells require so many different nutrients, right? Neuro-ensate levels, sugar levels, nutrient levels, ATP levels. So they all have defect sensors. You should have different sensors.
Ying Lu:
[32:16] But all those information needs to be integrated a cell's like computer they have to integrate all those information and make a decision what to do I need to keep dividing or do I need to enter different lescence states or die or whatever so all those decisions are made and how those decisions are detected how the cell actually cope with a change of nutrient levels I think is very interesting important questions but need more study.
Brent Valentine:
[32:43] And then, kind of on that, I know you guys have made a simulation of the ubiquitin-proteasome interaction and degradation of proteins. Has there been a simulation of an entire cell completely functioning?
Ying Lu:
[33:01] Yeah, there have been some studies like that. There is a study for example there is a several years ago there is a study, I think at Stanford called virtual cells or silico cells something like that so people as you said they aim to simulate every pathway that's available in a bacteria or euterotic cells and then they put them together so there are hundreds if not thousands of pathways and then, put those pathways together and then to see whether this actually could recreate from bottom up and to regenerate the behaviors of bacteria or cells that normally behave. I think there are some success of that. I think it's a very interesting area. So if we can simulate, if we can predict how a complicated logical system actually works, that would be quite important, quite beneficial for both research and also for, industrial applications.
Brent Valentine:
[34:12] You're soon with AI?
Ying Lu:
[34:14] Yes.
Keller Kramer:
[34:17] We talked about the role of translational research earlier. What are some of the ways you imagine your work might translate to human elk?
Ying Lu:
[34:25] Yes, I can imagine. This is also an important question that we are thinking about right now.
Ying Lu:
[34:33] Fundamentally, there are many ways that our studies could be directly or indirectly translated into human health. So one example is, you know, one research we have been doing previously is to study how the prorosome works. And one particular question we have been thinking about, and also other people have been thinking about, is, for example, there are hundreds of different human genetic disorders can be mapped to proteasome mutations, transmutations on the proteasome. So certainly there is a cancer aspect but even beyond that, and then those mutations map to different subunits on the proteome and a lot of those are neurogeneral disorders or autoimmune diseases and so forth so in most cases we have no idea how those single amino acid changes cause these tools such a traumatic detrimental effects so this is and then we try to understand how the proteome machine works and then maybe we have they have a way to understand the disease mechanisms and then find a way to actually to treat those diseases. And the other way, for example, we have been thinking about is...
Ying Lu:
[35:57] One area that we have been currently actually working on is this concept. We call that difficult substrates. And then because we realize that the cells contain targets of the proteasome that are degraded by the proteasome, but not by the proteasome alone, it needs some help. So unlike perhaps most targets that the proteasome can handle it, but those difficult substrates, some of those are membrane proteins, some of those are protein irrigates, Some of those are pretty complexes. So the proteasome can degrade them, but it requires assistance factors. And interestingly, many of those difficult subjects have a connection with diseases. My example is the protein aggregates that occur during aging and during neurodegenerative diseases. So proteasome is an important factor that keeps those misploidal toxicity proteins in check. But that process is not 100% reliable. People get old, and then the protein activity decreases, which may partially contribute to the accumulation of those aggregated proteins. And then we have been interested in what the cell has been evolved.
Ying Lu:
[37:16] The system that helps the person to tackle, to degrade, or to disarrigate those protein aggregates, toxic protein aggregates. And then, so once we identify those factors, and then we can find a way to see how can we boost the activity of those difficult substrate degradation machineries, and then so which may be able to help with certain conditions that is associated with the accumulation of those toxic proteins.
Brent Valentine:
[37:47] Would one of those be like the amyloid beta plaques for Alzheimer's?
Ying Lu:
[37:53] Amyloid beta is one example. Although amyloid beta, most people will think this is mostly occurring outside the cells. But there is a counterpart of amyloid beta. It's called tau protein. And then that is mostly in the inside neurons. And yes, you're right. So, for example, it's a major factor that degrades tau protein ergase that contributed to a variety of different neurodegenerative diseases like Alzheimer's disease, and so on and so forth. And then this is actually one of the direct areas that we are studying right now. So we want to see whether boosting this difficult sub-degregation system could help the cell to get rid of tau-perlid aggregates. so let's see what happens.
Brent Valentine:
[38:47] Yeah because it's the idea that the tau protein aggregates then become like amyloid beta plaques like outside the cell
Ying Lu:
[38:55] Tau and A-beta are intimately connected. Tau dysfunctions could lead to changes of A-beta processing and expressions and also vice versa. They could also seed. They could cross-seed the aggregation of either one. But the exact mechanism that whether this is Tau or A-beta is still active, research areas in Alzheimer's disease field. So I think fundamentally there's very strong evidence that tau and A-beta aregates occur simultaneously. There's a high decarrelation of those two aregates. It's just that A-beta is mostly outside the nucleus, sorry, outside the neurons, outside the cells, some inside cells. But tau is mostly inside the neurons.
Brent Valentine:
[39:57] Boom.
Ying Lu:
[39:58] Yeah.
Brent Valentine:
[39:59] And then you've also talked about the ubiquitin-proteasome system being a popular drug target. Could you explain when you'd want it to be an inhibitor versus an activator?
Ying Lu:
[40:11] Activator, yeah. Right. I can give you examples. One example is cancer that we have talked about. I mean, cancer you can think about as a ruling society. There is no regulation, right? And the production and recycling basically happens in sort of chaotic, random fashions. So certainly this society can be invasive, can be really crude from outside because nothing can control them. They don't listen to anything. And then they're also fragile inside because those things that maintains the well-being or the mere existence of that society is sort of in a kind of disordered fashion, both the protein degradation and protein-assisted machineries. So this, we call them vulnerabilities of cancer cells. And as one can expect that, the proteasome is one of those vulnerabilities of cancer cells. For example, in melanoma cells, and then in normal cells, the proteasome or the brain degradation system has some capacities.
Ying Lu:
[41:26] It's not entirely occupied or overloaded, so they have some capacity to deal with. And for conditions like stress conditions, things like that. But in the cancer cells, this degradation machinery can be just overloaded. And so that makes them sort of more vulnerable compared to normal cells to prism inhibition.
Ying Lu:
[41:48] And then, as expected, one of these great applications of this proteasome inhibitor that was pioneered by Dr. Fred Goldberger at Harvard is to treat myeloma and lymphoma cells because those cells, those cancer cells, are very sensitive to proteasome inhibition. So, a slight inhibition, normally the normal cells can tolerate, but those tumor cells will undergo apoptosis or die. And so this is one example of using how to explore these selective vulnerabilities in cancer cells by targeting the degradation of machine risk who leads to important therapeutic outcomes. I think on the other hand there are conditions associated with aging and neurogeneralizations and also sometimes it could be diabetes that is caused directly or indirectly by a failure or the reduction of the activity of the degradation system. So in that case and then we may think about can we actually boost the activity of the proteasome or autophagy machineries to demo using the Protag, Market Glue, this is my example.
Ying Lu:
[43:06] But there are also examples of drugs that can activate the proteasome globally. So that has been shown at least in animal models that could ameliorate the phenotype of Alzheimer's disease by increasing the activity of the proteasome. So there are many examples like that. I think clay, in summary, this degradation system activity must be carefully controlled. It cannot be too high. It also cannot be too low. But there are also pharmaceutical interventions we can implement to tune the activities so that we can use those to treat different conditions.
Keller Kramer:
[43:48] Are any of those pharmaceutical applications developed or close to development yet?
Ying Lu:
[43:56] Sorry. Any of those? Yes. The proteasome inhibitors, for example, bultosimide has been FDA approved for a long time, and they have been used to treat a variety of different cancers. And there are also other drugs like confusimide, which is different versions of proteasome inhibitors.
Ying Lu:
[44:14] A more resume which is a brain penetrable prism inhibitor has been under clinical studies right now and for prism activators there are, I think it has been mostly in the research stage so there has not been approved any drug approved but in the animal models I think from the early evidence and I think this is a look like promising that there is some way if we can activate the prismal declarations, it could help people. It may be able to, I hope, to help to trace certain conditions. Yeah.
Brent Valentine:
[44:49] And then, just taking one step back, I want to clarify the inhibitors. So if we think of cancer as an overactive growth, right?
Ying Lu:
[44:59] Right.
Brent Valentine:
[45:00] Wouldn't we want to degrade more proteins? Or would we want to degrade the entire cell? Why is it an inhibitor on that one?
Ying Lu:
[45:12] Oh, why in the cancer is an inhibitor? Okay, so I think simply put, I'm not entirely sure about the question you asked, but I think simply put is the cancer cells, they tend to synthesize a lot of proteins that they don't need. And then they need to degrade it, so which results in the degradation system is overloaded. And then, so if we inhibit it, for example, maybe 5% or 10% inhibition, minor inhibition of this degradation system will lead to a detrimental effect, collapse, of the entire cells, and then either make them not able to divide, or make them to undergo a programmed cell death. But this minor inhibition somehow can be buffered or sometimes it's heart rate hit by the normal cells. So this is fun, yeah.
Brent Valentine:
[46:14] So if a cancer cell is growing too fast and the proteasomes are working too hard, then it kind of stays at the level where it can continue to grow and populate. But if you inhibit the proteasome, you let it grow too much where then it kind of gets overloaded and then it has to kind
Ying Lu:
[46:31] Of kill itself. Right, right, right. Exactly.
Keller Kramer:
[46:35] I think we might have already answered this in the discussion, but looking into the future of your research, what are some of the biggest questions you're hoping to answer?
Ying Lu:
[46:44] Yeah, there are several interesting research directions we are following up, and then certainly we are still very interested in how the purge zone works, and we want to understand how this nanoscale protein machines could recognize the barcode of ubiquitins on the subtrates and then precisely execute their job of protein degradation. So this is sort of deeply mechanistic questions that we try to pursue. And then, but we are more, we are also interested in this thing called difficult subtrates or this machinery is either the factors or additional steps in the cells that helps this program to be able to handle other challenging targets but not be able to degrade otherwise. And one of the reasons is that this mechanism has been poorly understood. And the second is many of those, we call them difficult subjects,
Ying Lu:
[47:49] has close connection with human diseases. I think hopefully that through these studies and I think our research will be able to find a room to benefit the society.
Brent Valentine:
[48:04] I think that gives us a pretty good overview of a lot of your work. And I know we wanted to touch on one other thing is in the last few years, you started to work as a scientific advisor with a private equity firm.
Ying Lu:
[48:16] Right.
Brent Valentine:
[48:18] What is it like being a scientific advisor? How did you get pulled into that? Because I think that's a role that not a lot of academics always talk about.
Ying Lu:
[48:28] Right, right. Yeah, I can give some thoughts and because I was pulled into character by a friend, so initially she was asked me to give some advice about operations, mostly scientific advice about the operations of the investment firm and then to help them to answer some scientific questions. And then after a trial, I find this is quite interesting. So I would perhaps want to get more engagement with the operation of the form. So they sort of decide to stay and then to establish this scientific advisory role inside the form.
Ying Lu:
[49:15] And I think so far it has been quite interesting. It's a mutually beneficial process. I think on one hand they can get my opinions but often the topics are quite diverse so very often it's outside my expertise in that case I could refer them to people that have this knowledge could help them to answer questions, but also for me this is also a quite important learning experience because I think on one hand they help me to sort of motivate me to study, to learn the areas that I may not be able to do that without this kind of experience.
Ying Lu:
[49:59] And I think on the other hand, it sort of motivates me to think.
Ying Lu:
[50:05] What our society really needs and then how I could somehow translate my basic research into something that could impact, that could benefit the society. So I think eventually it's a mutually beneficial process.
Keller Kramer:
[50:22] Yeah. Earlier in the conversation, you mentioned that the traditional model with academia is that academia and industry were independent. Could you shed some light into kind of your interpretation of the modern context now and the relationship that academia and industry have with each other?
Ying Lu:
[50:39] Yes, I think there has been a lot of changes since I was trained, since my training stage. And there are still lots, there are perhaps even more bigger changes going on at this time. And I think in general, I can see the trend that the border between academia and industry become blurry. So there's more communications, there's more interactions between research and academia. It's happening right now.
Ying Lu:
[51:20] And then I think this is probably going to be the trend. And I think this is also going to be beneficial probably for both parties because the industry really just benefits a lot by having open-ended, inquisitive research activities and then help them to navigate any kind of their specific goals. But academia, on the other hand, by collaborating or interacting with industries, would benefit by, for example, receiving better support or advice from the industry. And then all those things ultimately would translate into a stronger impact of their research and then the stronger translational potential stronger impact or strong applications of the research from academia and I think this is a good thing to see I want to see more collaboration or interactions between academia and industry in the future.
Brent Valentine:
[52:29] And then I think nowadays in the era of fake news or conspiracies, people always get worried about, oh, the science is going to get manipulated by industry and profit motives. Do you think that's an overstated fear? And do you think maybe industry partnering with fundamental scientists, that fear is a lot more? There's a lot less likely to have a negative influence because if you're trying to understand the fundamental mechanisms, that can't be a drug that they're going to profit off of or something like that. Right.
Ying Lu:
[53:07] I think the question you brought up is very important. I definitely see examples. I read examples of that. I think the industry would somehow influence the academia, the research, or manipulate the outcome of the research in some way that would not be trustworthy. And I think those kind of things happens, unfortunately.
Ying Lu:
[53:37] And I think this kind of things may still happen even without collaboration between industry and academia. Because ultimately academia, in order to keep moving forward, they have to be funded somehow, right? By most likely not entirely by the government. And then there have to be some funding agency. So I think those kinds of things are hard to avoid. It's not going to, even if we stop the collaboration between academia and industry, it's not going to stop this from happening. So that's, I think, in order to minimize this potential thing, potential downside, and then there has to be more regulations, perhaps, unfortunately. And then, but also, so that's a whole different topic I hope to touch on if there's opportunity last time. But I do feel like for academia, you know, there are many, many, there are countless number of papers published every year, right? So the applications of the research, at least in biology.
Ying Lu:
[54:46] Is one of the ultimate exam of whether that knowledge is useful or is called true. Because some of this, or perhaps many of these models that we created are not wrong, but it could be incomplete, or it could be, you know, it could be sometimes it could be misleading. So the question is, how do we know that? Unfortunately there's not many ways that we should know whether, knowledge, our knowledge about the biological system has already been completed or there may be still part of the missing links there, unless we put those knowledge into real applications, which means we need help from industry to translate our knowledge, into drug or into a device that to put them into the most strict test, which is the clinical studies, right? And then so if those drugs work, that means, okay, yes, I think our knowledge is most likely to be correct because it translates to something very useful.
Ying Lu:
[56:01] But on the other hand, I think that indicates that there may be something important that's missing in our understanding, and then we should work harder to get better knowledge.
Keller Kramer:
[56:11] I think that's a really good way to conceptualize that relationship. As we wrap up, do you have any advice to the listeners?
Ying Lu:
[56:19] Oh, yes. I think there are many things I want to say, but especially for the young fellows, I would say just keep following your original motivations and then try to find opportunities to boost or to foster your creativity or inquisitiveness. And then please don't be afraid of working on basic research. So there are a lot of interesting things going on. There are a lot of opportunities. So try to keep going. Try to follow your own instinct. Don't be afraid that this is basic work, so I think this is not the right thing to do. And then we need more people. then we also need more support and people joining the basic research studies. You know, even for a short period but even for a few years it will probably be really beneficial for one's career if you look like, regardless whether this person is going to industry or study academia in the future I think have some experience in basic studies it's going to be very, very beneficial.
Brent Valentine:
[57:31] Right. We appreciate you coming on today. Thank you.
Ying Lu:
[57:34] Oh, thank you so much for the invitation. okay very very good conversations thank you for the great questions alright thank you bye.