The Evolution Of An Enzyme Engineer Who Changed Chemistry

- Hey, I'm Floor Lichtman,

and you're listening to Science Friday. In nature, enzymes are the catalysts that make much of biology work. They jump start chemical reactions

“that either wouldn't happen or would happen super slowly.”

They do a lot of basic biological jobs, breaking down food, building other molecules, extracting energy. But what if we could harness evolution to engineer designer enzymes that do other jobs,

specific jobs that benefit us? Putting that idea into practice, changed the game for chemistry, and earned Dr. Francis Arnold the Nobel Prize in 2018. She called it directed evolution.

And this is really big. Today, thousands of labs use these methods to coax enzymes into doing things no one had ever thought of. Dr. Francis Arnold is a professor at Caltech,

and we'll hear about where she sees this approach going in the future and her own personal evolution. The evolution that brought her into Science. Welcome to Science Friday, Dr. Arnold. - Oh, thank you so much Floor,

I'm thrilled to be here. - Okay, in our intro, we describe enzymes as catalysts that make biology work. I know they're near and dear to you.

“Do you have a more poetic way of thinking about them?”

- poetic. Well, I think about them as the transformation agents of the whole natural world. It's enzymes that take carbon dioxide and sunlight and simple, starting materials,

and build trees and human beings and flowers

and birds, they're amazing.

They're the best chemists on the planet. - When we talk about directed evolution, should I be thinking about this like enzyme breeding, but instead of a chihuahua, you're making a tiny adorable protein?

- Well, I think of it that way. It is a way to explain that we have been modifying the biological world at the level of DNA for ages, making strange things like chihuahua that wouldn't be found naturally,

but for some reason, human beings find them charming. Or useful. So why not use that same, very powerful process of directing the evolution,

“which is what breeding is, of enzymes to make what we want?”

- I want to get into this a little bit. I mean, let's say you wanted to create an enzyme that's like a stain remover. Can you create conditions that make a stain removing enzyme more likely?

Or is it more like trial and error? And you find one that gets a little bit better at stain removing, and then you breed that one. How does it work? - Well, you're right, Flora.

It's a process of incremental change. You don't get a whole new enzyme at once. Although that may be coming, but what we do is we start with something that has a little bit of the property

that you're interested in. Let's take your example of stain remover. If you start with an enzyme that has a little bit of capability to remove stains, but doesn't work in the presence of bleach,

and doesn't like your laundry machine, for example, then we can breed in or evolve in those desirable properties one step at a time. - And to do that, you take the gene that makes that enzyme, and you put it in a living organism,

is that how that works? - Well, for example, bacteria are wonderful translators of genetic material of DNA into enzymes. They can read DNA and spit out the enzymes wonderfully. So we use that capability, like a bag of reagents

basically of bacteria, to make all the mutant enzymes

that will program in, and then we search through those bacteria to find the ones that harbor the great stain removing enzyme. - And how do you sort of determine the winner? Like, are you putting these enzymes in a test tube with a piece of fabric that has a stain on it

and seeing which does the best? Like, what does it look like? - Well, I don't do that. In fact, I'll tell you a funny story. Way long ago, back in the early 1990s,

I had a grant from Proctor and Gamble who wanted me to make an enzyme for all temperature cheer. - They're laundry detergent and it's supposed to go-- - This is all real, mine is really real. - My sample here.

- But it's a wonderful example because I didn't have any way to test whether it would take stains off of clothes. So I said, sure, I'll breed you an enzyme that works at all temperatures, but I'll bed it and forget how it takes stains off of clothes.

you can very well lose other things that you're interested in.

“So you need to be able to measure all of the properties”

that you're interested in. It's called the first law of directed evolution, which is, you get what you screen for. And that may sound like a silly statement, but it's actually a very profound statement

because if you don't screen or search for the thing that you really care about, you'll get what you searched for but they not be what you want. We have these great t-shirts in my lab that says,

you can't always get when you want,

when we're searching the non-biological world. - I think we can all relate to that. - Yes. - I mean, if you get what you screen for, do you also ever benefit from serendipity?

Like, do you ever find, okay, this turns out not to be a great stain, remember? But wow, it's wonderful for mending yogurt. - So yes, because that's exactly what evolution does. But if you expand the space of biology

and you go out into new chemical frontiers, what happens is that those new molecules pick up properties that may be interesting for something else.

“And that's how innovation happens in biology,”

how something wholly new is created. Say, in enzyme, the catalyzes a whole new chemical reaction may become possible when you go out into these new spaces. But you have to know what you're looking for and sometimes all those new properties would be lost

because you have no way of knowing that they're there. - So can you screen for multiple properties at once? - Yes, if you know what you're looking for. It's not going to raise its hand and say, oh, I can build a new carbon silicon bond.

- I may not take off stains, but I can do this. No, it's not going to tell you that.

You have to ask it a million questions.

- Well, what if you don't know the right questions to ask? What if you can't think up the right question? - Wow, I mean, we're searching on almost infinite space. And you can't search infinite questions against an infinite space.

Humans can't do that. But you know, biology does it. Novel tea happens because all of this incredible diversity of the biological world is constantly changing. And constantly looking for new opportunities

for survival, right, survival with a fetus. So a new solution to let's say eating up an environmental pollutant can just pop up anywhere in the world. That's so incredible because it gives,

if you say for example, you break down an environmental pollutant

that it gives you a new rich nitrogen source, you have a selective advantage over your neighbors and you grow faster and then you can occupy the whole world to eat up that pollutant. I don't have any way to do that when I'm breeding in the laboratory.

- So are you starting from scratch each time or do you have a library of enzymes that you start from

“and are you adding to it with enzymes you find in the natural world?”

- All of that, yes. So we have a great big refrigerator of things that we've made that are now no longer what you would find in the natural world. We have an even bigger database of enzymes that all of science has deposited, what we understand.

And we have the almost infinite size of space of all possible enzymes that no one has explored. - Can you evolve an enzyme to do something sort of completely outside of the bounds of what life normally does? And are there problems that are easier to solve

with enzymes than other problems? - Definitely, yes. So if you, what does evolution do? Evolution takes what is there in one form or another and makes it better and confers maybe slightly new properties.

So if you know how to look at what is there, let's say in the biological world, or what we could even design, evolution lets you move that into something wonderful, something that actually, for example,

would make money or would solve a problem. So the problem for the researcher like me is to understand from what's there, what new properties could come about. And that's called chemical intuition.

- And is it intuition, I mean, is it a gut feeling? - No, it's a lot more than a gut feeling. It's knowing what chemistry might be possible from the machinery that already exists. So we know the structures of hundreds of thousands

of millions and millions more thanks to these new AI tools.

“And if a chemist looks at these structures”

and recognizes some machinery that might look like some chemistry that was invented by human beings, then maybe we can find this ability in those structures that evolve to do something

completely different. And that means we can find novelty by being the breeder, by recognizing what the biological world might be capable of based on our experience.

What's even more exciting is that AI tools for design might even give us access to virtually any chemical transformation that an enzyme could do. And that is so exciting because if we could actually design

a starting point for desired chemistry, not have to already find it in the biological world, then we can essentially press a button

“and genetically encode any chemical transformation.”

Wouldn't that be incredible?

- I mean, it sounds truly incredible, like, beyond belief. - But it's not beyond belief. All the steps towards that are being taken today. AI design of enzyme, obviously the evolutionary optimization novel measurement techniques

to let us sort through all of these new genetics sequences. I think in the next five to 10 years, we will be able to genetically encode almost all chemical transformations

that you could perform in an enzymatic system. - In the next five to 10 years, you could type in, like, vibe coding. I want this chemical transformation. - Yep. - Make me an enzyme.

- Yep, I think so.

- You heard it here first, everybody.

(laughing) We need to take a break, but there's so much more to talk about when we come back turning from, you know, what you achieved, Francis Arnold, to why, the evolution of a scientist, stick around.

(upbeat music) - Francis, can we get personal for a second? - Sure. - You said that in a way, like, no, thank you. - No, no, that's fine.

Everything that's ever been said to me is now out in chatGPT. (laughing) Why not add a few more? - I want to know what you were like as a kid.

Give me a sense of young Francis.

“- Oh, young Francis was a real pain in the, you know, what?”

I was bored in school, and so was off doing my own thing most of the time. I was very curious about the world, and so didn't pay attention to the very boring classes that we had starting in elementary school.

So they, you know what they did with a little girl in the 1960s who was bored in school, they sent me to typing class. So at age 10, I learned how to type sitting on phone books. Learn how to type, and then I took mechanical drawing,

geometry, and a number of other classes in the high school. And so that by the time I went to middle school, I was completely bored, and I started cutting classes. I didn't go to school anymore. This started in eighth grade.

I got kicked out of the private school that my mother had worked so hard to get me into because they would cater to bright girls. But I got kicked out because I would go off and do other things instead of going to school. And I just said, okay, well, high school is not very interesting

and started leaving school again. - How did that go over with your family? - Well, they didn't like it. They told me, shape up or ship out. So at age 15, I went out and got my own apartment,

and I worked in various horrible jobs. I had so many bad jobs that made me want to go to college. Tell me about your terrible jobs. - Oh, you know, I've had the jobs that if they're lucky, teenagers will continue to get working in pizza parlors

and sales department, a department store. And then by the time I could lie about my age and pass for 21, I talked myself into a good job as a cocktail waitress at a local jazz club. And that was really fun, except for it kept me up all night,

and that before I didn't go to school.

And then finally, I got a job as a taxi driver,

I learned how to get around Pittsburgh, Pennsylvania, which is a very complicated city. And one of those fattled yellow tabs with no GPS. I want you to think about that. There was no GPS then.

- Isn't there a part of the brain that expands for taxi drivers because they keep these mental maps in their head?

“- I think so, I think it was a wonderful experience.”

And I loved learning all about Pittsburgh. - I read that you had to hide your hair under your hat because people didn't want a woman driver. - Well, you can imagine this was what 1974, I think. People were not used to seeing women behind the wheel

of a big fat yellow cab. - I can imagine, yeah. - So once they got in, then they got in the car and then it's too late to leave. (laughing)

- I mean, you talk about your rebellious streak. And I think many, really successful scientists, I've spoken with, have that characteristic. Do you think that's necessary for making a paradigm shifting discovery?

- I think what's necessary is the willingness to go beyond what all the other monkeys are doing. This is what I tell my children. - Why are you doing what all the other monkeys are doing? (laughing)

You have to be willing to do something that is outside the bounds.

“Otherwise, you'll just be adding incrementally at best”

to what's already there. So it takes a sense of adventure, maybe. - And a little bit of courage, I think. - Oh, definitely courage. Where do you get that from?

- I never cared what people thought.

So I've been gifted with the ability to let criticism go in one year and depart from the other one without getting too worked up about it. And is that courage? No, it's just I followed what I wanted to do

rather than what other people thought I should do. - Is there a moment from your childhood that was predictive of your career in science? Me've done so many things. - Oh, I don't think of that.

No, there's no moment of this predictive. And whose career is predicted? I don't, I find it very hard to predict even the next five years, even though I just did that with the prediction that we'll be able to genetically

encode chemistry. But I can predict that because I can make it happen. - You know, I want to talk a little, I know you're interested in the humanities too. I have to ask, how many languages do you speak?

- I can understand French very well. I lived in Italy for a couple of years. So I speak pretty good Italian. I speak Spanish. I lived in Madrid.

I used to speak Portuguese because I lived in Brazil, but that is pretty much fallen by the wayside. - That's a lot. You mentioned also Yiddish and you're, you seemed to have a flare like for languages.

I mean, do you see that interest as separate from your scientific interests or did they connect in some way? - I think it's a connection. I'm just curious about words.

I'm just curious about words as I am about DNA. And the evolution of languages is completely fascinating. Just like the evolution of proteins, you can build family trees of languages.

And have always been thrilled by how words express

thoughts in different languages. - You know, reading your Nobel biography at almost reads like fiction, just the number of experiences you've had traveling across Europe, sleeping on farms,

offered motorcycling, taking care of horses. Do you feel like your life could have gone in many different directions?

“- Oh, of course, I think all lives can go in different directions.”

And just like evolution, there's a contingency there. This opportunity came in front of me at this time, and I chose this path, whereas I could have had a different opportunity at a different time.

And the trick I think is to choose a path is not be paralyzed by opportunities, choose something and go for it.

And you can always change directions if you don't like it.

So I tried many things before I found what I loved at age 30, I finally found what I liked. But I did a lot of things before then. - Let's fast forward to your career in science. So you work at the intersection of biology

and chemistry and engineering. Did you have to carve that niche out? - Yes, I did. I started as an assistant professor of chemical engineering at a time when chemical engineers were all working

for the oil companies.

because I had come from the solar energy background. But I ended up at Berkeley getting my PhD at the beginning of the DNA revolution. Imagine how exciting that was. So here I am an engineer, but I could see

that there was this future of rewriting the code of life. And I said, I want to be an engineer

of the biological world at a time when that first became possible.

- Right, it didn't exist before. It didn't exist, and my timing was perfect. - It's timing, but it's also you saw the opportunity. - I did, I did, but I was lucky to be in the middle of it. - What was the biggest failure in your career?

- Oh, I've had so many failures. The biggest failure is staying too long, it's something, or I don't, I don't dwell on failures. I just move quickly to other opportunities. So I don't actually think about big failures very much.

“- Well, I mean, I wonder if that's sort of key to success.”

- Well, of course, that could be, but sometimes those who dwell on failure learn something really, really hard and really important. So there's probably some sweet spot, right? - To work hard at a problem and achieve it or give up

and move on to the next thing. And sometimes you have to do one, sometimes you have to do the other. - You know, you were often out front as one of the few women working in your institution

or your department, you are one of eight women to win the Nobel Prize in Chemistry. Going back to your taxi days, did you ever feel like you needed to hide your hair under your hat in your scientific career?

- No, never. I took advantage of it because scientists, just like everybody else, want people to listen to them. Every scientist is working hard to solve a problem and we love talking about it.

Even the people who are shy, love talking about it. And if you go out and say to a conference and you give a talk and nobody comes, that's kind of sad, isn't it? Well, I was an oddity and so people when I walked in the room, they'd sit up and say, oh my goodness, who's this?

And they would listen to me and I just made sure

that the first words that came out of my mouth

caught their attention and they would stay to listen more. So I took advantage of this oddity that I was to get in front of people with my ideas. - That's really interesting to me. I mean, partly just also in the way you think about

the power of language, right?

“Like, I think scientists are often very careful”

in the way that they talk, not a lot of metaphors. Yes, a lot of caveats. What is your philosophy on that? My philosophy is that scientists need to tell a story. It doesn't have to be embellished.

It doesn't have to be hyperbolic, but it should be a story that captures the attention of the audience. Otherwise, you put people to sleep. We're very good at that, as you probably will know.

And I decided early on, I didn't want to put people to sleep and that I wanted to share the beauty of the enzyme world and my excitement about evolution. And honestly, it is truly exciting and wonderful to hear the stories.

- Well, let's talk about the next chapter of your work and of this field. You know, I heard from a biologist recently that the 21st century, he said, it's gonna be biology's moment.

Like, this is biology's moment to join the grown-up table of science, where it's typically been physics and mathematics and chemistry. And I know that you're working at the intersection, but do you agree with that sentiment?

“- Well, I think it'll be science's moment”

as big AI turns its attention to science.

We will have incredibly powerful tools

to address our understanding or lack of understanding of the physical and the biological world. I think biology is particularly exciting because it's so complex and the new tools that are coming up will help us navigate this complexity

and get better understanding.

of the complexities of life.

“What are some of the problems that you're working on right now?”

- Well, the one that I mentioned at the beginning, which is how do you genetically encode any chemistry? So, half of my research team at Caltech is expert in AI and machine learning. I'm not.

(laughing) I kind of ride along the top and we are integrating these experimental methods of evolution in the laboratory with AI tools so that we can explore this universe of possibilities

that biology provides. - It's interesting because you're not focused on one problem.

It's like you're focused on all the problems.

Find a solution for all the problems. - Well, we do it in the context of individual problems. So we'll take on a challenge of making a, for example, a tuberculosis drug using enzymes

“so that it can be sold cheaply in developing countries.”

That's a really hard enzyme design problem. And we took money from the Gates Foundation to build enzymes that do new to nature chemistry to do that. And it worked really quite well

or we have a project to degrade forever chemicals using enzymes for which there's no known chemistry, but we can create that in the laboratory. Those are examples that allow us to test our methods

and see if what we say we can do we can actually do.

- Do you think forever chemicals will be kind of like a killer app for designer enzymes? - I hope so. - How close are we? - It's a complicated issue.

P-fast, let me just say that enzymes are one of the many ways one could consider to attacking forever chemicals. And one of those ways of course is not to make them in the first place. So what I'm hoping is that enzymes will provide

a clear cut, hugely cost-effective method for degrading plastics or forever chemicals. And that they will win the race, but I hope anyone wins the race. - If you were starting fresh today,

would you be working in the same field or what problem would you tackle? - I would work exactly on what I'm working. It has given me endless joy, fascination, fulfillment, interest, I just love it.

- You found your evolutionary niche. - I did. And young people find it exciting. I've been doing this for 40 years and the excitement just continues to grow.

It's not a field that's closing off. Many fields that people were working on 40 years ago are kind of, you know, closing off. We've answered those questions and it's time to move on to something else.

But rebuilding or building a new biological world, that's just something that's exploding in opportunities and I'm thrilled to be at the beginning of it. - I'm gonna ask you one last question and it's like a big thinking philosophical one.

What's the purpose of science? - The purpose of science. As a technologist and an engineer, I translate science to solving problems for the planet and human beings.

But the purpose of science is to give us better understanding of where we sit in the universe and what is our role and our origins and our future in this universe. - Dr. Francis Arnold is the Linus Pauling Professor

of Chemical Engineering, Bioengineering and Biochemistry at the California Institute of Technology and the winner of the 2018 Nobel Prize in Chemistry. Francis, thank you so much for talking with me today.

- Thank you for having me. - It was really a pleasure.

“If you want to help this podcast evolve a bit,”

why not give us some direction? Call us at 877-4CiFry and coax us to solve some new problems. That's 877-4CiFry. Call us with your questions that you can't find answers to.

This episode was produced by Charles Berquist. Thank you for listening. I'm Floor Lixman, catch you tomorrow. (upbeat music) [BLANK_AUDIO]