Latest / From First Principles / Optovolution: Teaching Proteins to Think Like Computers (EP. 31)

Transcript

Optovolution: Teaching Proteins to Think Like Computers (EP. 31) · From First Principles

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Hello, Internet.
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This is your captain speaking, Lester Nare, joined as always by my co-host and our resident PhD, Krishna Chaudhary.
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Today, we are going to be touching on a protein evolution story in the lab today.
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directed by humans.
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So historically, if we've wanted to make proteins do things that we wanted them to do, we've used the process of evolution in order to do so.
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But there's a lot of limitations with that approach.
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This next story is taking that method and putting it on steroids, giving us the ability to now be able to
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turn these on and off and sort of create almost like a computer, these simple logic gates that give us much more control.
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And it's fascinating how this is going to have implications in a variety of arenas.
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And the way in which they did so is very interesting.
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So we are going to learn about the science from the ground up today, because this is From First Principles.
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So we want to make new proteins all the time, right?
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That's a lot of biomedical research going on right now is to make new enzymes, new types of proteins to do all sorts of things.
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And traditionally, a lot of times what we can do is use in-lab evolution to make novel proteins.
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Now, those techniques, for reasons that we're going to get into, only make certain types of proteins, specifically ones that always remain on.
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But if we want proteins with actual more natural dynamics, like proteins that turn on for certain things and off for certain things, or if we want to have like mini logic gates, like the ones that we have in our computer for the and or the or or the exclusive or things like that, it's been really difficult to use the traditional technique to build those types.
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This is taking that step forward.
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Okay.
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It's a breakthrough called optoevolution.
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Okay.
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from EPFL in Switzerland, Lausanne.
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It's a cell journal publication.
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And the mechanism is really, really cool.
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What it's doing is it's using continuous evolution with light to steer the evolution of dynamic proteins, not just proteins that are going to be in one state all the time, but proteins that can transition and be in dynamic states.
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It couples effectively like an oscillator, like an optical oscillator, with internal...
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Cell cycle oscillators.
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There's like incredible like deep physics underlying this.
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And it's actually really, really cool.
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And to get started, let's just go through some of the history of directed evolution.
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Okay.
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So evolution...
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is really kind of an optimization, right?
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We all know it as nature's way of engineering biological systems.
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There's the idea of survival of the fittest, which is you've got some population.
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Inside of the population, inside of that DNA, there's a lot of variation when it goes from one generation to the next.
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So you have variations in the genetic code, which leads to variations in phenotype, which means that, you know, like I'm going to have black hair or blonde hair or whatever.
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And through natural selection,
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The organisms that function most effectively are going to reproduce more and they're going to proliferate more.
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And that's basically the central tenet for evolution.
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Now, humans have harnessed this process for a very long time to do artificial selection, artificial evolution.
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Early farmers influenced evolution by choosing which crops or which livestock to actually move on to the next generation.
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And if you look at, you know...
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The thousands of years of selective breeding have given us all of the crops that we know and love, but they started out not great.
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This particular photo, the one on the upper left, that's watermelon.
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That does not look like watermelon.
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That does not look appetizing.
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That does not, no, right?
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The one in the middle, that's corn.
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On the right, that's a carrot.
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That looks like a stick.
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That looks like a twig.
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That looks like a twig.
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That's not what we see in carrots, right?
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So...
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All of the food that we eat today is a result of artificially selecting the ones that we prefer and then having them proliferate to the next generation.
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So this is not a new thing for humans to sort of take over the evolutionary reins and steer organisms to their will.
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Okay?
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Here what we're doing is at a biomolecular level, we're doing targeted directed evolution.
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Okay?
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Okay.
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This is the idea where you induce mutations in the DNA.
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So you make thousands of versions of an enzyme, let's say, from that DNA.
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And then you select the ones, the versions of that enzyme, that do the best for the next round.
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So, you know, let's say I have a thousand different versions.
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I'm now going to create thousands of different enzymes.
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Out of those, the top 100, I'm going to select that DNA and then now do it again.
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Do a bunch of mutations, create a thousand different versions.
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test it.
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I do this natural selection at a genetic level now, right?
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At a molecular level.
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And what I'm doing is through that process, I can make catalysts, replace toxic chemicals.
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This has been huge for the biomolecular industry.
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We've created biofuels out of this.
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We've created agricultural chemicals.
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We've even created a better way to produce a drug for treating type 2 diabetes.
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So...
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This has been around for a very long time.
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Actually, in the 1990s, there was a professor, Francis H. Arnold, at Caltech.
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She started doing this.
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She's really been a pioneer of this type of directed evolution.
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She won the Nobel Prize in 2018 for her work.
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Interesting tidbit about her.
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Undergrad at Princeton.
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Woo!
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Go Tigers!
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It was an undergrad in mechanical and aerospace engineering.
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Which I thought was interesting because from there she went and did a PhD at Berkeley in chemical engineering and then a faculty at Caltech.
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And I think this is just a really cool way to think about, like, what you do in undergrad is not like...
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going to totally sequester you for the rest of your life.
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I think they say what past is not prologue or something.
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I mean, she did aerospace and mechanical and now she invented directed evolution and won the Nobel prize in 2018 in chemistry.
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Right.
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So it just shows that like an undergrad, really what you're trying to do is learning how to think.
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Right.
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And that's, what's important.
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And then you can move on and use that skill later on to do whatever, whatever you want.
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It's not over yet.
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You still have a chance.
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Exactly.
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Um, um,
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So she pioneered directed evolution.
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Here's the problem.
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Directed evolution is all about static selection pressure.
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For example, if I want to make an enzyme that breaks down a certain toxin, what I'm going to do is create a bacteria with this DNA that is constantly inside this toxin bath.
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So now only those bacteria that have the enzyme to break down the toxin are going to live.
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But naturally, what that means is that
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the enzyme is going to be constantly on.
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It's going to be constantly trying to break down that toxin.
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It's never going to turn off.
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So this whole process of directed evolution is going to select for proteins that have continuous function, not dynamic function.
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Mm-hmm.
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That's very different from proteins that we see in life.
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Proteins are dynamic.
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They move from one configuration to the other.
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Here what we're seeing is a particular ligand, that green dot, is moving in into the protein.
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And the alpha helix in blue is changing shape.
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The protein is literally changing shape and toggling between one state and another state.
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And this is very natural for proteins to do.
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They want to toggle between an active and inactive configuration.
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confirmation in response to some kind of stimuli it's effectively acting like a molecular transistor in some sense right there's an on off switch there's a zero and one and we don't want a protein that's either always zero or always one we don't want to be always asleep or always awake yeah yeah we want we want things that actually wake up and do things based on their particular environment and that's where this paper comes in okay this paper is
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It's called light-directed evolution of dynamic, multistable, and computational protein functionalities.
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That's what they're doing.
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They're using light to do this directed evolution.
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And from that, they can actually figure out ways to create dynamic proteins.
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That's the optoevolution solution that we have.
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And so before we get into the mechanics of all that...
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Let's do a little bit of housekeeping.
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Yes.
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You may not learn a little bit, but you still might find it interesting and entertaining.
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Yep.
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So let's get back to the story.
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We want to talk about optoevolution, which is this new way that this paper has figured out how to use directed evolution, this idea of in-lab evolution, but now to create dynamic proteins, not just proteins that are remaining on,
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but can now toggle between an on-off switch, like normal proteins, okay?
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The physics that underlies the core principle is from coupled oscillators, okay?
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This is something that we learn about in undergrad physics.
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You've got two oscillators that are connected by some kind of mechanism.
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Mm-hmm.
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Over here we see just two masses on a spring.
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And you can see in this case, the energy from one is getting transferred to the energy of the other.
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And so one of them oscillates and then the other one remains stationary.
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And then when the other one oscillates, the first one remains stationary.
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The idea...
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Is that if I were to apply this to my protein challenge, right?
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I want to create a protein that can oscillate between an on and an off state.
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So what if I can tie its performance to a fundamental oscillator of life?
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which is the cell cycle, the reproduction cycle of the cell, right?
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Because the cell has to grow, then it has to split, and then it has to grow, and then it has to split, and it has to grow, and it has to split.
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So if I could somehow couple the evolution of the protein in interest
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With that oscillator, such that it needs to oscillate in order to really talk to this fundamental oscillator of the cell cycle, then perhaps I can optimize for proteins that can be dynamic, rather than only proteins that can be on and off.
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I want to ask a quick question just to help me understand.
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When you say oscillate, can you opine on that a little bit in terms of what exactly you mean by oscillate?
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Yes.
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So in physics, when we talk about oscillate, we mean that it moves from two states.
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in some type of way it doesn't have to be continuous it doesn't have to be discrete for example simplest oscillator would be a pendulum it's going to the left then it's going to the right then it's going to the left then it's going to the right that's an oscillator um a mass on a spring it's going up and then it's going down it's going up and then it's going down um a ball on a hill a ball in a valley it's going to the left then it's going to the right then it's going to the left then it's going to the right
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In physics, actually, it turns out everything is a simple harmonic oscillator.
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Harmonic in that, like, there's, I think it just comes from, like, harmonies and the fact that it's, you can fit it with a sine wave.
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And an oscillator, I think it just means it's oscillating from one state to another state.
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And so the cell cycle is an innate biological oscillator because it's oscillating from growth to division, to growth to division, right?
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So it's a cycle.
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There's a cycle that has some kind of period and a starting position and an ending position.
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And then it goes back to the start.
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And there's a repetition of the movement between those two.
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Exactly.
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Yeah, yeah.
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And so what we want to do here is in order to create an oscillatory protein, something that can toggle between an on and an off, I'm going to couple it, connect it somehow to the original oscillator of biology, which is the cell cycle.
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Right.
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And would the potential benefit of doing something like that be the biology?
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It's sort of like the same reason we use, was it quasars for clocks?
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Because it oscillates on a cycle that is so consistent and so repetitive.
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It's a dependable system to base clocks.
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Yeah.
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With the quasar, it's like so far away that it doesn't depend on my position, the Earth's position around the sun.
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And so it's always in the same spot in the sky.
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Right.
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And so it doesn't depend if I'm in July or March.
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The quasar is always there.
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And so I can use that as my clock to figure out how long my day is.
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In this sense here, we're using the cell cycle because it's...
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The cell cycle is just going to go, right?
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Otherwise, the cell dies.
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Right.
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So if I can make a protein that I need to be dynamic, tied to the cell cycle, then if the protein arrests into either an only on or an only off state, it's going to kill the cell.
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And then that protein is not going to proliferate in evolution.
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That's the sort of high picture idea of how we're going to use evolution here in this case, right?
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Because now it's survival of the fittest.
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I need to be able to toggle the internal dynamics.
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Understood.
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The protein needs to be able to go from one state to the other.
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Right?
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That's what's key.
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So let's talk about this biological oscillator that I've been going on about.
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This is the eukaryotic cell cycle.
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Okay?
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Mitosis, which is something that I hope everybody who did high school biology knows about.
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Yes.
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The idea of binary fission, right?
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The cell...
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Doubles its DNA, and then it splits in two.
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And then it doubles its DNA, and then it splits in two.
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Well, the doubling of that DNA happens during interphase, specifically the S phase.
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That's the synthesis phase.
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The splitting in two is the mitosis part.
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But after splitting in two, now each of these daughter cells have only one...
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copy of DNA.
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In order to replicate again, they need to go through the S phase again.
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They need to synthesize the DNA and double their DNA and then split up again.
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Now, this entire cell cycle is driven by something called cyclin-dependent kinases, CDKs, okay?
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These cyclin-dependent kinases are formed and degraded at very specific times.
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And if we go back to photo 11, what we'll see is what's happening is
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A certain compound comes up during, let's say, the G1 phase, which is the very beginning of interphase.
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So this is right after mitosis.
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Right after the split, a certain cyclin E shows up in the cell.
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Okay?
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And that's going to trigger the next phase.
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Okay.
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Then during the S phase, during synthesis, another cyclin comes up.
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That's going to trigger the next phase.
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Now, how is that triggering happening?
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The triggering is happening because the certain cyclin shows up and it immediately gets degraded.
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So it's only there for a short amount of time.
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So it's like this boop signal.
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You know?
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It doesn't stick around.
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It's maybe like, as an analogy, it's like the ignition.
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When you're starting your grill...
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and you click the button on the grill to get the ignition going, and it's only there at the beginning, but then the fire's going, and it's not there anymore.
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Yeah, exactly.
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And we don't want the da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-da-
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a particular sort of factor here that is like starting the cell cycle that is essential for one part of the cell, but if it sticks around for too long, then it's going to completely destroy the cell cycle.
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Interesting.
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Right?
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Okay.
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With the starter that you have on the grill, it's going to be annoying.
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The sound is going to be annoying, but the grill is still going to work.
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Yes.
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We need to find a type of starter molecule that if it sticks around is going to be deadly.
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Mm-hmm.
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For later.
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And what they found is a cyclin CLB5.
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What this thing does is promote DNA replication.
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So essential, right?
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This is the thing that starts DNA replication for the cell.
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But it naturally gets degraded.
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And if it's still present, it's going to lead to cell death.
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Okay.
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Because of later on, it's just going to mess with whatever is going on.
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It's not important, like, how it does it.
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But we just know if it sticks around, it's bad.
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CLB5, okay?
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So they created a strain of yeast.
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The model organism here is yeast.
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They created a strain of yeast called Dajbog.
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This is named after the Slavic sun deity, the god of the sun, and he is in charge of the day and night cycle.
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Okay?
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We're going to learn about why it's called day and night cycle because what we're trying to do is use light in this entire process.
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So that's why they called it Dajbog.
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Okay?
21:12
Okay.
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Here's the trap that they're setting.
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When they made Dajbog, which is this particular yeast strain, it has endogenous cyclins that are there because it wants to replicate.
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They deleted them all.
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Okay.
21:30
Okay?
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So now this yeast strain is completely dependent on what the researchers give it.
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I see.
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Okay?
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We've held it hostage.
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Yes.
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And now the starter thing, it doesn't have its own starter.
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Yes.
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We are going to provide the starter.
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So instead of the grill having the button on it where you can click it and it has the igniter that starts to fire...
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We remove the battery from that on the grill so it can't do it.
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And we're bringing in one of those long lighters ourselves and pointing it.
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But we control when it's going in there and when the light happens.
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Exactly.
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And now that lighter, that critical cyclin, CLB5 that we have, we're going to place it under the control of the protein of interest, the one that we want to evolve.
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Yes.
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Okay?
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And that protein of interest is going to act as a transcription factor for that cyclin.
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Why is this important?
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Why?
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I told you that that cyclin is extremely dangerous if it's on all the time.
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Previously, the problem with directed evolution is that we were only getting proteins that were on all the time.
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Now, that's going to cause cell death.
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That is no longer the fittest.
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Right?
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In the evolutionary perspective, if this protein is on all the time, the cell is going to die.
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we've basically created...
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It's like in the movies where there's a scene, we've put a collar around the protein.
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Yeah.
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And if it continues doing the thing we don't want it to do, the collar self implodes.
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Yeah.
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But we basically now have a means by which to prevent a type of protein we don't want to persist from persisting.
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Exactly.
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I mean, it's such a...
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Such a neat thingy.
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Thing.
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And it's inserting itself because there's a natural process that's already happening.
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Yeah.
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And we're basically trying to make a portion of the candidate proteins in the entire population not procreate.
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Yeah.
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Anytime there's a mutation.
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Yes.
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Where this thing turns on and stays on, the cell's going to die.
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Mm-hmm.
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Anytime there's a mutation and this thing turns off and stays off, it's going to die.
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The only way the cell is going to survive is if my protein of interest, which is the thing that I'm trying to evolve, turns on, creates the cyclin, and then turns off to stop creating the cyclin.
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Right?
23:47
And now, this is the magic of the light.
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Okay.
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The survival condition is the following.
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That protein of interest...
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has a little chromophore, so it's sensitive to light.
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I'm going to turn it on with light.
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It's going to turn on.
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And then when I turn off the light, it's going to turn off.
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Okay?
24:07
And if it ever goes against that signal that I'm giving...
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It's done.
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It's done.
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So we have this external... We're basically trying to have the ability to say... To control the state through the light as an external source of influence.
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Yes.
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The internals are such that we've constructed it that it will always...
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When it responds to our light, to our external perturbment...
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It will survive.
24:43
Yeah.
24:45
If it remains on when we've turned it off, then it'll die.
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And so now we've basically created a mechanism by which we externally can control the state of the protein via light as the mechanism to do so.
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Because if it no longer responds to our external probing, it will no longer survive.
25:05
Yeah.
25:06
Meaning through the natural evolutionary process.
25:09
we will kill off the ones that are not what we want to be.
25:13
Exactly.
25:14
Yeah.
25:14
So now we're only keeping proteins that are toggling on and off.
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On and off.
25:18
And, and as long as the light is in sync with the cell cycle, which means, you know, it's like over like, so it's going to be like on for an hour, then off for an hour, on for an hour, then off for an hour, because that's about, it's about takes them like two hours for yeast to go through the cell cycle and reproduce.
25:33
And so that's what we're doing.
25:34
We can drive this oscillator now.
25:36
Mm-hmm.
25:37
with light.
25:38
It's like you're, you know, pushing on a swing and as long as the swing keeps going, you're good.
25:43
But if the swing stays up, that yeast cell is going to die.
25:47
Can I ask a quick clarifying question?
25:50
You know, we've talked a lot about proteins on the pod before and why they're so important.
25:57
Yeah.
25:58
Can we just briefly touch on for folks who may not be familiar with why we would even,
26:06
Why this is even relevant.
26:08
Like having control over the protein's ability to exist or not exist is a powerful tool.
26:13
Yeah.
26:13
But to what end maybe?
26:15
Yeah, sure.
26:16
Does that make sense?
26:17
Yeah.
26:18
So proteins are the workhorses of life.
26:21
Okay.
26:22
When we think about life, we think about like DNA, right?
26:25
A lot of times we think about genetics.
26:27
The reason why genetics is important is genetics is the blueprint for creating the machinery.
26:32
Okay.
26:32
Okay.
26:34
You can imagine genetics, the DNA is the IP, but the protein is the car and the vacuum cleaner and the lights and the camera and the computer.
26:44
The DNA is the KFC 13 herbs and spices secret recipe.
26:50
Yeah.
26:51
The protein is the actual...
26:52
It's the chicken.
26:53
It's the chicken.
26:54
Right?
26:55
And so what we want to do when we're doing this directed evolution here...
26:59
In the KFC analogy, we're changing the recipes to create the best chicken.
27:04
Right?
27:04
We want wings.
27:05
We want tenders.
27:06
We want, you know, da-da-da.
27:08
And so far with the directed evolution, the way that we've done it is, you know, the toxin's always been there.
27:14
So this particular machine, the protein, has just always remained on.
27:18
It'll always eat the toxin.
27:20
It'll never not eat the toxin.
27:22
And it's just always going gangbusters.
27:24
Mm-hmm.
27:24
That's not how a lot of proteins in life work.
27:27
A lot of proteins will toggle between being active and being inactive, and they only get active when there's a certain stimulus.
27:34
For example, the lactate enzyme.
27:37
The lactase enzyme, which digests lactose, only gets on –
27:42
or only really is expressed when there is lactose in the environment.
27:46
Now, there, the difference is the protein isn't actually there in the first place until lactose is there.
27:53
Lactose then triggers the transcription of that DNA to create the lactase enzyme that then digests lactose.
28:02
But here, we want to create proteins that...
28:05
Can toggle while being present, right?
28:08
We don't want to initiate their production, and then there's a time delay because the DNA has to be read into RNA, which has to be read into this, and then become a protein, and then the protein goes, right?
28:18
What if we want instantaneous...
28:20
reactions from a protein.
28:22
Well, we want it to be off and then we want it to turn on.
28:24
That's a good question.
28:25
Yeah.
28:26
Does that make sense?
28:26
Yeah, no, it does.
28:27
And so the justification for trying to research this area is if we can control the state of the protein, there are a variety of ways in which...
28:41
With that capability, we can try to pursue any number of, let's say, therapeutic outcomes.
28:50
I mean, like, for example, even with just the old directed evolution, right, the reason why the 2018 Nobel Prize was given to this is because there's been tons of research and tons of pharmaceutical uses from just classic doctors.
29:05
directed evolution and that directed evolution was only giving us proteins that always remain on now imagine if we can have a dynamic protein that comes out of this and later on we'll get into something that's very very cool that's helpful thank you for i just wanted to reground really quick please continue no that makes sense so that's the that's the idea that's the whole idea is that we're trying to um use light
29:30
In synchrony with the cell cycle, the light is going to drive this protein.
29:33
And as long as this protein can turn on and then off and then on and then off, we're good to go.
29:38
Based on the input of the light being present or not present.
29:40
Exactly.
29:41
Yeah.
29:41
So now let's get into some proof of concepts.
29:44
Does this work?
29:46
Okay.
29:47
The first thing we're going to do is spectrally modify the light oxygen voltage domains of a certain protein called EL222.
29:57
This is a protein that is ubiquitous in research.
30:01
Okay?
30:03
It's a transcription factor.
30:04
So what that means is this protein, I shine light on it.
30:09
That's going to attach to DNA, whatever part of DNA that you want.
30:13
And then that part of DNA is going to be transcribed into mRNA, and it's going to cause the gene to be expressed.
30:20
So we can turn on and off genes using EL222.
30:25
I shine blue light of 450 nanometers, and whatever gene of interest is going to turn on.
30:32
Interesting.
30:33
That's an incredible technology already.
30:35
Right.
30:35
Okay?
30:36
Right.
30:37
But it's only one color.
30:38
Right.
30:39
Okay, what if I wanted to turn on two jeans?
30:43
right well you could say well i just get an el222 on gene a and el222 on gene b but then when i turn on blue light both are going to get expressed what if i want to turn on one and then maybe sometime later i want to turn on the on the other and then i want to turn on both later i'd need two colors of light right so so currently we sort of have a very naive way to start the factory yeah we can basically say start the whole factory yeah
31:10
What we're trying to say is we want to start the chip department only.
31:13
Yeah, and then maybe a time later we'll get the phone department going because the chips are ready or whatever it might be.
31:19
Exactly.
31:19
So let's get a little bit into this protein here, EL222.
31:23
Okay?
31:25
A lot of these proteins that are light-sensitive use something called a chromophore, okay?
31:30
This particular one uses a flavin mononucleotide chromophore.
31:35
That's the FMN.
31:36
If you look at the protein here, the bulk is the protein.
31:39
And then that little gray—sorry, no, the bulk of the protein is in gray.
31:43
The black little compound there that looks like a nucleotide—nucleotide is the building block of DNA.
31:48
In this particular case, that little black molecule needs to be there—
31:54
That black molecule is going to absorb the blue light photon, go into a higher energy state like in quantum mechanics, just classic quantum mechanics.
32:02
It's going to go into higher energy state.
32:03
The protein is then going to sense that higher energy state and change its shape.
32:09
I see.
32:10
Okay?
32:11
And for the longest time, that blue photon, which is at 450 nanometers, blue, remember, is high energy.
32:17
Yes.
32:18
Which means that that chromophore, which is the little triggering molecule, requires a high energy photon to bump up to that high quantum state.
32:28
And then that causes the shift in the protein structure.
32:30
Some random alpha helix goes from one state to another state.
32:34
And then that activates the protein.
32:35
The challenge is...
32:37
That chromophore is pretty happy with blue light.
32:41
It doesn't want to accept other nanometer wavelengths, right?
32:44
So shifting the absorption to, let's say, a lower energy green light, because green light, there's a bunch of lasers we have with green light.
32:50
It would be really nice if we could make a chromophore that shifts to green light.
32:56
Okay.
32:56
Okay?
32:56
Okay.
32:58
How do we do that?
32:59
Yeah.
32:59
Yeah.
33:00
Right.
33:00
Because we talked about purple lasers recently.
33:02
Yeah.
33:04
But that's hard.
33:04
Right.
33:05
Green light is easier because it's lower energy, so it's fine.
33:09
Right.
33:09
Right.
33:10
So I'd like to be able to create an EL222 that doesn't just respond to blue light, but there's another one, there's another version that responds to green light.
33:17
That way, if I want to start the chip department, I shine the blue light.
33:21
Then if I want to start the phone department, I shine the green light.
33:24
And I have independent control of which gene I'm going to.
33:28
Turn on.
33:29
We want to have more granular ability to turn the factory on to generate the proteins we want to under the circumstances we want to and then be able to also stop that process when we want to and then have this control of saying if the factory starts producing the thing we don't want it to do, the factory will automatically shut down.
33:48
Yeah, yeah.
33:49
And so I want multiplexing ability.
33:53
So here's what they did.
33:54
They selected under green, orange, and red LEDs.
33:58
And again, you do the same thing.
34:00
You do directed evolution.
34:02
You shine it on green.
34:04
Those that survive make it through.
34:05
Those that don't, oops.
34:07
What they found was key mutations.
34:09
They actually were able to create this almost impossible...
34:17
light oxygen voltage transcription factor.
34:20
The chromophore didn't change.
34:23
The little black molecule didn't change.
34:25
The original triggering one we talked about.
34:27
Didn't change.
34:27
It turns out there's some intermediate state that that thing has that does respond to green light.
34:33
It goes into an intermediate quantum state, but the original protein was not sensitive to that change.
34:39
Through two...
34:40
changes in amino acids.
34:42
There was at the 83 location, T went to A, so the therionine went to alanine.
34:50
One amino acid was switched for another.
34:52
And at the 80 location, the glycine was moved to an arginine.
34:56
Both of those 83 and 80, as you can see, they're very close to that black...
35:01
So they're right next door.
35:03
And just those two changes made the entire protein sensitive to that intermediate quantum level that green light triggers.
35:12
And now on the left, you can see now the yeast is growing using those.
35:18
Yeah, yeah.
35:19
changes right and this this is what's kind of interesting here is again you you come up with the plan you try it and then you find out oh actually there's this thing that we didn't understand which is this intermediate stage that exists and if your fundamentals are good then you can then continue the process because then you're like okay well now if we manipulate these intermediate stages we should still be able to get the results we're looking exactly
35:50
EL222 star, I guess, that is allowing for orthogonal color multiplexing.
35:56
Now I can have green light.
35:57
Now I can have blue light.
35:59
Blue light on, green light off.
36:00
Or vice versa.
36:02
Because the combination of the two is its own... Yeah.
36:07
Now I can...
36:08
control a bunch of genes imagine if i could do this over and over again right if i keep doing the directed evolution such that the bandwidth of the response on that protein is really narrow so green light of this particular frequency is only going to trigger that protein right green light of this other you know teal versus aquamarine is going to trigger some other thing right mm-hmm
36:30
Because with lasers, we can get really, really narrow bandwidth.
36:35
We can be like, it is at exactly 450.
36:37
It's not 451.
36:39
It's not 452.
36:40
It is 450 nanometers, right?
36:42
So, again, like for biomedical research, this is huge.
36:46
It's allowing multiplexing of genomes.
36:49
Yeah.
36:49
Right?
36:49
Of gene turning on and off.
36:51
Yeah, yeah, yeah.
36:52
Right?
36:53
And to maybe distill it down to kind of a basic concept level,
36:58
We're creating a controller for researchers to better drive the process, the research processes they want to around protein synthesis.
37:10
Yeah, exactly.
37:10
Yeah.
37:11
And gene expression.
37:12
And gene expression.
37:13
That's the big one.
37:13
Yeah.
37:14
Okay.
37:14
Yeah.
37:14
And protein synthesis is gene expression.
37:17
It's the thing that drives the gene expression.
37:19
Yeah, exactly.
37:20
Okay.
37:20
Okay.
37:20
Okay.
37:20
So.
37:22
Breakthrough number two has to do with trying to use it with red light.
37:26
Now, with red light and infrared light, you can't use the EL222 because red light is way far.
37:31
You know, red light is at, what, like 800, 700 nanometers, whereas this thing was at 450.
37:35
So it's like almost half the energy.
37:37
Right.
37:37
Right.
37:39
So you don't have any hope in using the same protein.
37:42
You're going to use something else called the 5B PIF3 system, okay?
37:46
This is something that uses 660 nanometers to turn on and 740 nanometers to turn off, okay?
37:54
Why would you want to use red light?
37:55
Well, red light is very good for deep tissue penetration.
37:58
Yes.
37:59
It's the same reason why sunsets are red.
38:01
Okay?
38:02
The sunset is red and the sky is blue because blue light scatters more because of Rayleigh scattering.
38:08
And so that's why from every direction in the sky, you're getting blue light because the sun is illuminating it with all the colors.
38:14
But really, the shorter frequencies are the ones that are...
38:16
Sorry, the shorter wavelengths, the higher frequencies are the ones that are...
38:21
coming to us from all different angles.
38:23
But when the sun is setting, it has to go through a lot of atmosphere.
38:27
So for the same reason, all the shorter wavelengths, higher frequencies, are getting scattered away from us, and the red light is penetrating through.
38:35
Same thing happens in tissues, in biological tissue.
38:38
If I want to do this kind of, you know...
38:41
light-directed turning on and turning off of genetic factors and things like that in my biomedical research, but deeper in the tissue.
38:50
The blue light is only going to get through so much.
38:53
If I use red light or infrared light, that's going to get deeper into the tissue, and so it's very much...
38:58
To my advantage.
38:59
Have you seen the...
39:01
Speaking of red light and getting deeper into the tissue, the new masks that have been created in sort of the, I guess, beauty and skincare space.
39:11
Oh, I've seen those, yeah.
39:12
And they're...
39:13
blaring red light at your face because it gets deeper into the tissue.
39:18
Yeah.
39:19
Same thing.
39:19
Same thing.
39:20
Same thing.
39:21
Exactly.
39:22
Now, these proteins, just like the EL222 that we were discussing with the blue light, these all rely on a chromophore, which is some kind of molecule that is going to absorb the light.
39:34
That's going to get triggered into a high energy state, and then the protein around it is going to...
39:39
be sensitive to that high energy state, and then change its configuration and become active.
39:44
The particular chromophore here is phycocyanoblin PCB.
39:50
This thing is hella expensive.
39:52
Yeah.
39:52
Okay.
39:53
A thousand, it's $1,400 per two milligrams.
39:58
It's also highly unstable, and it's not natively produced in yeast and mammals.
40:03
So in order to actually express it in yeast, I have to give it this chromophore, and I have to give it the red light.
40:10
It's just really expensive, and it's got to be timely because it degrades really fast.
40:16
So the campaign that we want to do with this optoevolution is can we make this thing respond to red light without that chromophore?
40:22
Without the additional secondary piece that is required to actually make the process work.
40:27
Exactly, without PCB.
40:29
Can we get the lobster tail without the caviar?
40:31
Yeah.
40:31
Yes, that's exactly right.
40:33
And so that's exactly what they did.
40:35
They subjected these dashbox cells to red and far red pulsing and no external PCB.
40:42
There were mutants that had loss of function mutations that survived and created and were actually responsive to PCB.
40:50
But...
40:51
They had deletions of this particular enzyme, this particular gene called YOR1.
40:57
Now, why YOR1?
40:59
Because that YOR1 is basically a trash collector enzyme.
41:02
Okay.
41:03
That's weird.
41:03
Yeah, yeah, yeah.
41:03
Why would a trash collector enzyme cause me to be now sensitive to the red light that I was no longer sensitive for?
41:10
Yeah.
41:10
I don't have the chromophore that I need for the red light, but if the trash collector is not there, all of a sudden I can be responsive to red light.
41:17
What does that mean?
41:18
That means the trash collector was collecting some other molecule that I was using.
41:24
Yeah, yeah, yeah.
41:25
That I'm now using for the chromophore to be sensitive to red light.
41:29
Right, right.
41:30
And now that the trash collector is gone, there's some random other molecule that I can now grab and use to be sensitive to red light.
41:38
Yes, right.
41:38
Isn't that cool?
41:39
Yeah, that is very good.
41:40
The trash collector was taking away the active ingredient that allowed the response to the red light.
41:46
When you get rid of the trash collector, the active ingredient is then available.
41:48
Then available.
41:49
And that's exactly what they found.
41:50
They found this active ingredient, biliveridin BV.
41:54
And when you give the yeast cell artificial BV, it'll respond to the red light.
41:59
If you take out the trash collector YOR1 gene, it'll be responsive.
42:04
It'll also be responsive.
42:05
It'll also be responsive.
42:06
So now, what does that mean?
42:07
That means that...
42:09
The endogenous biliverdin can actually trigger my red light receptor cells.
42:15
All I have to do is delete the trash collector enzyme.
42:19
And now it's way cheaper.
42:20
It's way cheaper.
42:21
This goes back to this thing you brought up before and continue to bring up, which is if we can use the body's natural system to drive the outcome we're looking for versus artificially inserting something, it is...
42:35
always better it's always but i don't want to say always but just in case yeah just yeah you know what yeah you're you're very correct in biology there's never and always generally generally you're right yeah it's better most of the time most of the time yes yes biology is a notorious well actually
42:56
Yeah, biology is not like physics that way.
42:58
But that's a really interesting point.
42:59
Again, the tracing of the process to the root, to the first principle, and the why, then allows you to make more calculated choices about how do you want to intervene or interact with the system to decrease as much external disruption as possible.
43:19
Exactly.
43:20
Exactly.
43:21
And the journey to get there...
43:23
Very clever.
43:24
Yeah, yeah.
43:25
And finally, Breakthrough 3.
43:26
I think this is going to be your favorite.
43:27
Oh, my God, no.
43:28
There's another one.
43:29
Yes.
43:29
Okay, so just a really good...
43:30
So with the Breakthrough number one... Breakthrough number one was we made the blue light sensitive protein...
43:36
Yes.
43:37
Sensitive to...
43:39
Green light.
43:40
Green light.
43:40
Which was good because now, and also later we can be sensitive to multiple.
43:46
Right.
43:47
Here, then now we figured out the red light trash collector piece with the Raleigh scattering.
43:53
Yes.
43:54
And now there's a third.
43:55
Finally, the last one is single protein computers.
43:58
Okay.
43:59
Okay.
43:59
Right.
43:59
We are now trying to create an AND gate.
44:02
Okay?
44:03
All the students of logic know about the AND statement, right?
44:08
I need both of my inputs to be... No, no, no.
44:12
I need either my input, 0 or 1, to be 1, and I'll get... Am I showing... No, I'm showing a...
44:21
This is an OR gate.
44:23
Okay, guys.
44:24
Whoever's looking at the thing, this is like a not AND gate, right?
44:29
Because the A and B, if they're 1, the output is 0.
44:34
So this is an AND gate.
44:35
Yes, yes.
44:36
Sorry.
44:36
That's my fault, okay?
44:37
But in any case, an AND gate is when both the inputs are 1, and that's when the output is 1.
44:43
Otherwise, it's always 0.
44:44
Right, right, right.
44:45
Okay.
44:45
Which the idea is like...
44:47
This and that are true.
44:49
That means the total thing is true.
44:51
And prosper.
44:51
Yes.
44:52
Okay.
44:52
So historically biological logic circuits, we can construct them, but usually what they require is a multi-gene cascading process.
45:00
Meaning gene A is on and gene B is on, which means that gene C will be on.
45:06
Okay?
45:06
So it requires this and that to be on, and both of them go on.
45:10
and become that.
45:11
I'd like all of this to be in a single protein.
45:14
Because that way, it's not as slow.
45:16
I don't have to wait for one gene to turn on another gene and another gene.
45:19
It's not a sequential process.
45:20
It becomes just an instantaneous discrete protein.
45:24
And it's not also resource intensive because to transcribe one gene it's a lot of ATP.
45:29
To transcribe another gene I get a lot of energy.
45:31
And so what I want is a single protein advantage.
45:34
The computation is instantaneous.
45:37
And there's negligible...
45:39
metabolic load so what do i do i use my tet on and tet off system this is something that we have discussed in the um it was the time capsule oh one of my favorite that one was so yeah that was a crazy that was a great if you guys have not watched that episode i think i put that in my favorites list for last year yeah
46:00
Very fascinating.
46:00
No, no, that was this year.
46:02
Oh, I'm thinking about...
46:03
I'm confusing time crystals.
46:06
Yeah.
46:07
And this is the time capsule.
46:09
The honeycomb structure.
46:11
Yeah.
46:11
That one was also really good.
46:13
But the idea is with RTA, this is this tet on tet off system.
46:17
Basically, whenever there's doxycycline, this particular protein is going to get transcribed.
46:24
The gene is going to get transcribed.
46:26
Yeah.
46:27
So what they did was they combined this teton system, the RTA, with something called a pest degron, which is effectively, if you have this pest degron, it's targeting the protein for rapid destruction.
46:43
Okay?
46:43
So here's what I've done.
46:45
I've created a protein where if I get doxycycline, it's going to come on.
46:52
Yes.
46:53
But as soon as it gets transcribed,
46:56
Part of it has this degron system to degrade.
46:59
It's like a degrade flag.
47:01
The proteasome is going to come in and degrade it.
47:03
Okay?
47:04
So it's only going to be transiently active for a very short amount of time.
47:07
Okay?
47:08
Now, instead of being a continuous on and off, like a continuous thing that is either in an on or off state, now you're kind of gating it to a...
47:17
a window of time that has an explicit start and explicit exactly and so here is why the logic works because it requires input a which is transcription on from the light that i'm getting yes and input b doxycycline needs to be present okay both need to be present and they need to outpace the degradation okay if i turn off input mm-hmm
47:41
then whatever protein is still there is going to get degraded immediately.
47:47
So now it's a super time-sensitive and switch.
47:51
Yes, yes, yes, yes.
47:52
Does that make sense?
47:52
Yeah, it does, it does, it does.
47:54
It means the and of the light and the doxy.
47:57
Yes.
47:58
And the light I can trigger immediately, right?
48:00
The doxy can sort of just hang out.
48:02
Right.
48:02
But the light I can now trigger immediately.
48:04
Right, right.
48:04
And turn off.
48:05
And as soon as I turn off, it gets degraded.
48:08
The light is our controller.
48:10
The doxycycline is a part of the substrate that's necessary to facilitate the environment where we have control.
48:16
But we don't necessarily... As long as the doxy is present, that's the thing that matters.
48:21
Exactly.
48:22
And they were able to actually do this.
48:24
They were able to actually create this ant switch in a single protein.
48:28
Now, just imagine, right?
48:29
Like, computers are...
48:32
Based on logic, on computational logic.
48:35
And here we're able to do computational logic with a single protein at, like, the second timescale resolution, right?
48:44
It just opens up a lot of really cool avenues for biomedical research, for fundamental science research.
48:52
Because now if we want to figure out what this particular gene does, we can use this AND gate to be like, well...
48:57
What is the logic of this particular gene in relation to the entire logic table of the rest of the genome?
49:05
So would you say there are a lot of ways you could utilize it?
49:08
There's one way you could utilize it as basically being able to isolate in a very complex biological environment –
49:18
certain things you want to look at and control it so that you can watch the process or the outcomes, knowing that you're controlling the inputs into the system.
49:29
Exactly.
49:29
Yeah, exactly.
49:30
And from that, we can, as I said, create the logic table.
49:33
And that really lets us understand how genes relate to one another, how they relate to external stimuli.
49:39
Right.
49:39
Like all sorts of stuff.
49:41
Right.
49:41
And the idea is with this optoevolution, we can now create proteins that have this dynamic behavior that need to end that are not always one.
49:50
This is a logic.
49:51
This is this is one that requires inputs to turn on.
49:55
which means then you could then, you know, have proteins that only turn on based on an external stimuli that we define.
50:07
And so, you know, if you're putting something in the body, you don't want it to be always be on.
50:12
You want it to be on only when you want it to be on.
50:14
And now we kind of have the early makings of a mechanism that we can repeat that is discrete, controllable, and...
50:24
has also the ability to terminate at the end.
50:28
Yeah.
50:28
Which is like, we talked about a story, for example, where you have the half-life of a drug in the body, and drugs can have a really long half-life, which goes really, but you can't really, you can't just decide, today we want to turn it off.
50:42
Yeah.
50:43
You kind of just need to let it,
50:44
the system dissipated naturally.
50:47
In this case, for this particular use case, we can say, no, we're done.
50:50
Yeah.
50:51
Yeah.
50:51
And I just...
50:54
The possibility of all the stuff that we can do with this is endless, right?
50:58
Right.
50:58
So it's really like...
51:00
When I say that, right now, I don't have...
51:04
exact ideas about how this is going to be used, but that's kind of the beauty of it.
51:09
It's such a new paradigm to take this oscillator, tie it to the cell cycle, and make it such that the protein toggles on and off.
51:17
Right.
51:17
Now, it's a whole new avenue of directed evolution that we can now use to create a myriad of different proteins, a space that we didn't even have access to before.
51:26
Right?
51:26
Right.
51:27
It would have an analogy that makes sense be like it's like when we first figured out how to use binary in computing systems.
51:38
Yeah, like even before the transistor, right, the vacuum tube was big, was huge.
51:43
Right.
51:44
Yeah.
51:44
Right.
51:45
And we didn't know that we were going to get Uber or Facebook when we were starting to just be like, oh, we can like have an on and off game.
51:52
Yeah, yeah.
51:53
Yeah, imagine all the logic that we can now put in a cell.
51:57
In a cell.
51:59
We can have the same level of sort of software style engineering that we have in computers.
52:04
Again, I know there's a lot of other details.
52:06
Yeah, yeah, yeah.
52:06
This will be more machine language.
52:08
Right.
52:08
But...
52:10
As a rough kind of reference point for people to try to understand who might not grasp the concept as organically, we are building our own ability to create programs at a biological level.
52:25
Yes, exactly.
52:26
Like the equivalent of software programs.
52:28
It's the beginning of that.
52:29
It's the very, very early, early, early, early stages.
52:33
Yeah, it's exciting.
52:34
This is very, very good.
52:36
And this was...
52:37
This came out of, I want to make sure.
52:40
EPFL.
52:41
That's right.
52:41
That's the Ecole something, something.
52:44
Ecole Polytechnique Federal de Lausanne.
52:46
Oh, there we go.
52:47
University de Beirut.
52:48
Beirut.
52:50
Not Beirut.
52:51
B-A-Y-R-E-U-T-H. Yeah.
52:55
Not the...
52:56
Anyway.
52:57
Yeah.
52:59
We got to be careful of that.
53:01
But this is... And again, you know...
53:04
It's so...
53:04
It's very...
53:05
This was very dense.
53:06
Yeah.
53:07
But I think it's, again, the...
53:11
The level of depth of previous knowledge and work that created the base by which these researchers are now building on top of to try to move away from this previous directed evolutionary approach.
53:31
And trying to find a way to be able to create these control mechanisms within it.
53:35
And the three different breakthroughs are necessary.
53:38
It was just proof of concept.
53:40
They were just doing proof of concept.
53:42
Imagine what other people are going to come up with, right?
53:44
Right, right.
53:45
And that's another interesting point.
53:48
Not all science has a consumer product at the end of it.
53:51
No, it's just more science.
53:53
Right, right.
53:53
But imagine the amount of more science we can do with this new tool.
53:57
Which will ultimately end up in real world impacts.
54:00
This is very different than folks who, well, I was going to talk about dark matter, which we'll never figure out and we'll never know in our lifetime.
54:07
So that's one area where we don't have the ability to have real world impacts.
54:13
Fascinating, fascinating story.
54:16
We've had a lot of protein stories.
54:19
I mean, we talked about the Yale...
54:22
uh a lego block story last year yeah i mean at the end of the day when you get to the molecular level everything is proteins right right and we have to we have to we want to be able to do more with them again we are in our new format on the show multiple times a week you'll see us pop up in your feed on the podcast feeds if you're on spotify or apple on the youtubes
54:46
And you'll catch some of our clips on the socials.
54:49
This gives us more times to get deeper into each story.
54:52
Instead of just 30 minutes and rushing through, we can really, really dive in and get deeper.
54:57
We still have the rundown.
54:58
The rundown will be a standalone.
55:00
Catch that later this week.
55:02
And I am your host, Lester Nare, joined as always by my co-host and our resident protein synthesizer and PhD, Krishna Chowdhury.
55:13
We will see you guys for the rundown.