Rama Ranganathan
Big Brains podcst

Nature’s Design Secrets with Rama Ranganathan (Ep. 4)

Prof. Rama Ranganathan shares his pioneering research on evolutionary physics, and explains why he believes biology is at a similar point today as engineering was two centuries ago during the Industrial Revolution.

Rama Ranganathan
Big Brains podcst

Show Notes

From the smallest proteins to entire ecosystems, nature might be the most sophisticated engineer on earth.

Researchers like UChicago molecular biologist Rama Ranganathan are trying to uncover the basic design principles that govern biology and apply them through engineering. He calls the field “evolutionary physics,” and the goal is to unlock the secrets of evolutionary history.

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Transcript:

Announcer: From the University of Chicago, this is Big Brains with Paul M. Ran. Conversations with pioneering thinkers that will change the way you see the world.

Paul Rand: For all of our technological advances, nature still puts human ingenuity to shame, but how does it do it? Rama Ranganathan is a molecular biologist, and he’s trying to figure out the rules of nature and how to apply them to engineering. And he calls this field evolutionary physics. If he can unlock the mystery, it could lead to some truly awe-inspiring breakthroughs. I talked to Rama about his research and why he looks to the past to understand where biology is headed in the not so distant future.

Paul Rand: So your new field, if this is the right term, is evolutionary physics.

Rama Ranganathan: So physics of evolution or evolutionary physics are both very good ideas because what we’re borrowing from evolution is the problem, and we’re borrowing from physics is the approach or the ethic, which is to take a bunch of complex observations and reduce them to a simple law, in the way that the motions of the planets and the motions of the universe or the galaxies going around and what holds us to the surface of the earth were all explained as manifestations of one thing, which is gravity, right? So in that same way, we want to have a simple understanding of cells, but this, it requires us to put together the way people think in physics with the richness of the measurements and ways of thinking in biology.

Paul Rand: Tell me how in the world you’ve got to this point in your career. What prompted the focus in this area? How did you get to this stage?

Rama Ranganathan: Well this for me has been a long-term matter of interest. When I was an undergraduate, actually in studying engineering, I was amazed by our ability to be able to build very complex systems with very simple underlying rules so that we can build electronic circuits, we can send satellites to orbit, we can do all these amazing things because we understand the underlying principles. And during that time, I was also looking over their biology and what amazed me was the incredible performance characteristics of biological systems, kinds of systems that we would love to be able to build as engineers, but we didn’t have the basic underlying rules. We didn’t understand what makes them work. We didn’t understand even their origin. And I felt very strongly at that time that trying to go there and trying to understand how biology is building all these high-performance systems.

Rama Ranganathan: And when you look at the systems, they don’t look like anything that you would have built, right? They have circuitry and the ways that they are created that people for example, it turns out a cell has about the same number of components as a Boeing 777 airplane. And so, it’s a pretty complex thing, right? But a Boeing 777, we have the rules to make it, and people don’t fly those things without confidence that they actually do fly. So there’s computer simulations and things that tell us these things are working the way that we intend, but for cells, we don’t have any computer program that can predict anything they do, because we don’t know the underlying laws of how they operate. And in fact, we can’t just borrow it directly from what we understand about traditional engineering, that’s clear so far, because the underlying principles of these systems is really somehow radically different. We don’t have a physics or an engineering or a circuit theory for biology and the way that we have it for all these other things that we can build so easily.

Rama Ranganathan: I’ll tell you one of the things that biological systems can do that we in man-made engineering, I’ve never achieved and it’s the ability to have both high performance and the ability for a thing to be adaptive. And let me explain what I mean by that. So in normal man-made engineering, there’s a general rule that the more and more high-performance you make a system, the more and more fragile it gets, so it breaks easier as it becomes more and more optimized for its function. So for example, an Italian sports car is an amazing machine, but it’s also very highly tuned and tends to require a lot of attention.

Rama Ranganathan: On the other hand, biology is able to make systems that are arbitrarily high-performance. In fact, in enzymes, we have the concept of a perfect enzyme, an enzyme that can work as fast as theoretically possible. And yet that system remains adaptive. So when the environment changes and it’s asked to do a different job, it can find a path of random variation to get to the new function. So the ability to create what are called high-performance adaptive materials has never been possible in engineering, but that’s something we could learn by studying biology.

Paul Rand: So in essence, we’re getting an Italian sports car that will never break down.

Rama Ranganathan: That’s right, or maybe even get an Italian sports car that if you ask it to use a different fuel, it’d find a way to get there and be able to do that. So it’s this ability to have both performance and adaptive capacity, which really, if right now we have no formal theory how that works.

Paul Rand: If you sit down and you’re thinking, my gosh, this is what could come out of the work that we’re doing here. What’s the potential?

Rama Ranganathan: I mean, it’s a bit hard to be specific about the actual products that will come out of this thing. What I can tell you is one thing is that whatever biology’s doing in the way that cells work and the way the brain works, for example, the brain is not computing anything the way that we know of is working. The moment we understand these things, the number of things that we’ll be able to do right now, it’s hard to even predict it. So it’s a kind of a vast space of new engineering. It’s almost like having a day, there was a day in our understanding of science that we had Newton and we had Newton’s laws, right? And then we had the days before. You couldn’t even imagine what would be the impact. It’s almost like that where we are with biology, where it’s so devoid of any principles at all. It’s hard for us to even imagine right now.

Rama Ranganathan: But if you ask the question, why do we think that there are simplifying laws in biology, right? I would say it’s almost like an article of faith in science is the idea that complex phenomena can be reduced to simple understandings. I don’t think there’s a formal proof that such things have to be true, but that’s been our experience always in science. Every time we look at something and we say, wow, that looks like an amazingly complex thing we go and study it very carefully, and we find out underneath it somewhere is some simple thing that’s going on of which this is one manifestation. And now that we understand it we can connect a broad range of phenomena to this one concept, right? And then we get engineering, right? Because engineering comes from understanding the essential laws that govern the behaviors of thing. I mean, if you don’t have that, you’re just stabbing in the dark. So what you need to do is to be able to deduce the laws from which you can build, not just one thing, but a whole variety of things that share the common principle.

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Paul Rand: So when you first started thinking this was a possibility, did your colleagues think that’s too far fetched, or my gosh, this guy’s on to something.

Rama Ranganathan: I’ll tell you, there is a lot of discord in the scientific community of whether there are principles in biology. People are saying, what do you mean general principles? I mean, what general principle? There’s just this richness of biology, and there are people that I would say are celebrating the complexity of biology and think that is what there is to say. We just need to observe all these things and write our papers, and we will explain biology one piece at a time, right? And then there are people like me who say, no, there’s an underlying principles. And in fact, we should be always trying to unify these things into these principles.

Rama Ranganathan: I don’t think it’s broadly accepted, but I think it’s clear that such rules exist because biology is doing it. We see it all around us, but what was not clear, was how to get there because the problem is if we start taking apart biological systems, since our evolved systems, we don’t necessarily understand their design. We don’t see how they’re put together. Their rules of design are so different than what we build that the question was, how do you learn the simple rules that are underneath these very, very complex, seemingly very complex systems? And so that’s been, actually the thing that I focused on right at the beginning is finding a strategy towards this problem, which we seem to have done now, right? And that strategy seems to be now be paying off to the point where we are able to design synthetic systems that look like biological systems, at least at some scale.

Paul Rand: I would think based on what you’re talking about, people will want to be checking in with you on an hourly basis, that are thinking, my gosh, if this guy figures this stuff out, the potential for commercial value, it could be quite meaningful.

Rama Ranganathan: Right, well, I’ll say two things about that. One is that even in our own field, in biological science, there is, we’re asking in some sense for a change of a view about biology itself, instead of thinking about biology as a whole collection of detailed stories, about all the parts of the systems to try to work on these simplifying unifying principles, which I think is a cultural difference that we’re asking for in biology, which is happening, but it’s going to take some time for that to become completely the case.

Rama Ranganathan: But from a point of view of the practical outcomes of this work, I think that there is a huge amount of excitement, obviously about the potential that could be if we were able to achieve our goals. I think it’ll take us demonstrating these principles in some practical steps over the next five to ten years before that becomes really, I would say routine and practical. It’s just a little bit away from that state right now, where we can immediately make these instant practical.

Paul Rand: So, when you say it’s a little bit away. What does that mean?

Rama Ranganathan: Well, what I mean is that I think there are some fundamental things that we have to work out still, both conceptually, and technically about how to use the knowledge that we’re learning about these systems to actually, practically build synthetic versions of biological systems. I mean, but those are things that we can see happening it’s just things that haven’t happened yet. And I think in the next five to ten years, we will have some of the critical tech.

Rama Ranganathan: For example, I can tell you one of the key technologies that will be necessary is rapid, cheap DNA synthesis. We have to be able to create synthetic genes. When we build designs of biological systems, what we’d like to do is to build the DNA that codes for, for example, proteins. And we would like to be able to put those synthetic DNA molecules, the synthetic genes, back into biological systems, but creating synthetic DNA is expensive and slow right now. And it is actually a limiting technology as being able to proceed in the future. So for example, solving that kind of a technical problem, to be able to cheaply create DNA molecules, what I’m talking about are your synthetic genes and ultimately synthetic genomes, is going to be a critical step in achieving the practical potential of these ideas that will take a little bit of time.

Paul Rand: And so you’re at the stage of just beginning to build out your lab.

Rama Ranganathan: Here at University of Chicago, yes.

Paul Rand: And what is this going to look like?

Rama Ranganathan: It’s going to have three components to it actually. The lab will continue to work on this problem of trying to find the simple rules underneath the systems that are evolving, particularly focused on proteins and cells. But we’ve learned so much about that now, actually, that we’re moving on to two other problems. One is, can we understand how a thing works now that we know the simple rules underneath it? Can we actually directly study the physics of these biological systems? And to do that at the level of proteins, we’re actually taking advantage of Argonne national laboratories at which we have facilities, which for the first time we can directly probe the mechanics of proteins to see how they work directly by doing experiments, using a synchrotron radiation. So that’s one new thing that I’m adding, coming here to Chicago.

Rama Ranganathan: And the second new thing is to actually everything we’ve done so far has been accomplished by looking at the past history, what evolution has done and by studying the products of what has come through the process of evolution. Now we are in the laboratory learning how to do forward evolution. And that means to start with materials in the laboratory and make them go through an evolutionary process, and actually look at the future history of these sorts of systems as they’re evolving in the laboratory. So forward evolution is a really new thing. It’s evolution has taken millions and millions of years, how do we reproduce that in the laboratory? Well, it turns out that we can speed up the process of evolution, quite a lot actually, in the laboratory. And we’re able in practical time to be able to do forward evolution experiments. So I think doing the forward evolution will really allow us to test our ideas that we’ve learned by looking at the past history

Paul Rand: What gets you really excited when you come in? And I imagine it’s probably hard to shut this off. This is a seven days a week, you’re thinking about this. What gets you really excited when you start saying, I think we have the potential of X.

Rama Ranganathan: Well I think we have the potential now to simplify our understanding of biology, which looks so very complicated. If you look at all of the papers that are being published, there’s a huge number of facts of all the individual parts of these systems, all the reactions, every single thing seems to have a story. So science in biology has become almost a kind of storytelling where each of the parts are considered individually and their stories told. But I think what really gets me excited is the idea that one day we will understand the simple laws underneath these systems, which will explain their behaviors without having to memorize all of the detail of all the parts taken into.

Paul Rand: So we have not Newton’s law, but Rama’s law?

Rama Ranganathan: Well, it won’t be Rama’s law, it’ll be the work of many people, but it’s something like that exactly. When you think about a Newton’s law put together a whole slew of different phenomena, that look all different, into a single law that, with which we could predict all those things. It’s exactly what we’re missing in biology is any kind of unifying law like that, which takes many of the observations that we see and is able to explain them through the action of a simple principle. That is the most exciting thing that we could achieve, I think.

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Paul Rand: With all the work that you’ve done, how did you get to proteins?

Rama Ranganathan: I was interested in how biology is building information processing, material processing systems. You could say that’s the true from the scale of ecosystems all the way down to the scale of atoms and the way the proteins are made. When I first came to biology, I started at the top level and tried to figure out what could be done practically, right? And it turns out that the experimental and technical power we have to solve these problems of design and evolution are optimal at the level of proteins and cells. The technologies are really most powerful down at the scale of proteins and cells, and so it makes only. In fact, I would say it was the only choice if you really want to work on the process of evolution itself, then it was the right scale at which one should work.

Paul Rand: Is there going to be a point where you feel like you’ve unlocked something? The discoveries, the inventions, the opportunities are going to come at a rapid pace.

Rama Ranganathan: It’s hard for us to see that in biology right now, because we don’t have these laws yet, right? And we don’t know where, what things we’ll enable once we have them, but we can go back and look at history, and see what has happened in other areas when such laws were discovered. So in the early 1800s, the 19th century, it was just after the industrial revolution, people were building engines now of all sorts and engines, of course, burn fuel, and then produce work. What everybody wants to know was how to optimize these engines, right? It makes sense. You want to minimize your fuel costs and get the most amount of work done, right? And what people were doing actually to optimize these engines looks a lot like what we’re doing in biology today, which is that they were detailed modeling individual engines trying to optimize their specific characteristics, right? And sometimes it worked, sometimes it didn’t, but even when it did work, whatever they learned about how to optimize one engine didn’t transfer to any other engine, it was a specific model for this specific case. So what happened at that time, that changed everything was the arrival of a guy called Sadi Carnot. And so Sadi Carnot is a physicist who comes and he says, look, if there’s anything general to say about the relationship of fuel burned over here and work being done in an engine, it has to be true for all imaginable engines, not just the particular ones that we’re making here today. And so what he managed to do was a complete cultural change, where he threw away all the detail of the individual engines and made the most abstract, simple concept of an engine and deduced some laws.

Rama Ranganathan: And you know what those laws were called? They were called the laws of thermodynamics, which began a line of work, which many people contributed to later on. But that is now the reason we’re able to build all the machines that we have today, the laws of thermodynamics are the foundational structure on which all of modern engineering and physics is built without Sadi Carnot, there would be no general ideas of how to build these complex machines. And then people were able to do so many things that were not even envisioned at the time that Sadi Carnot made his initial discoveries. So what I’m trying to say is what we’re doing today in biology is like that. We’re modeling individual proteins and individual cells and individual organisms and not seeing anything that’s.

Paul Rand: So what will this be called the laws of what exactly?

Rama Ranganathan: Yeah, so I guess it would be the laws of biological design or biology or design of living systems, maybe something like that.

Rama Ranganathan: But I guess what I’m saying is what we need today is the Sadi Carnot for biology, which we don’t know what that looks like, and that’s why it’s hard to be specific about what sort of practical things we’ll be able to build once we have these sort of unifying laws for biology. Now you could make one argument and say, well, how do we know such simple laws even exist? Maybe biology is just really complicated and it’s truly an interactively complex system. Well, we don’t believe that’s the case because a process like evolution is a very, very, an underlying, it is a very simple idea of just stepwise variation and selection. That’s Darwin’s idea, right? Things change forms, change through variation and selection. And we feel like that kind of a process has such a simplicity to it that the systems it builds may look very complicated and hard for us to understand, but underneath there, there are these simple laws that we don’t yet see, and they may not look like any other laws we have for building any machines that we know of today. But when we have them, we’ll be able to now have a completely new playing field in being able to analyze systems that is to understand your genome or a bacterial cell or anything like that. But we’ll also have the rules to design synthetic ones. And what that looks like at this day, this moment, right now, it’s hard to say, but we know it’s going to be very exciting. One of the key things I want to point out is the need to draw from many disciplines to be able to solve this problem. This is not just a problem of that looks traditionally like biology has in the last 40 or 50 years. We need people from computer science, from engineering, from economics, even because it turns out some of the theories in economics look a lot, like some of the theories that we’re trying to expose for evolution. Now we’re experiencing in biology, the influx of people from many non traditional backgrounds, I think that’s going to be quite essential. And one of the exciting things about coming to University of Chicago is the capacity to draw on that breadth of disciplines, to be able to address this one problem in biology.

Paul Rand: And what I consistently hear here is the barriers that may exist in other places really are really quite removed here.

Rama Ranganathan: Yeah. And I think that the Institute for molecular engineering is a prime example of this. This is a institute which is doing engineering in a very non-traditional sort of way. So it sort of paved the way for the kind of way that we need to take with this problem in evolution, which is to integrate across disciplines. There’s no one background which is ideal to solve this problem. You need people that are interdisciplinary individuals who are coming from many different backgrounds to work on this kind of a problem.

Paul Rand: But what it really takes is having somebody with a clear vision of what it could be, that all the pieces can come together. And so we’re eager to see how this develops. We’ll keep tabs on the growth and the progress that you’re making. And hopefully you’ll come back and give us some updates as things progress.

Rama Ranganathan: Of course, I can’t wait to see how it works out myself.

Paul Rand: Good.

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