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Speaker 1

00:00

You can study chemistry, you can study physics, you can study geology, anywhere in the universe, but this is the only place you can study biology. This is the only place to be a biologist. Earth. That's it.

Speaker 1

00:10

Yeah. So, definitely something very fundamental happened here, and you cannot take biology out of the equation. If you wanna understand how that vast chemistry space, how that general sequence space got narrowed down to what is available or what is used by life, you need to understand the rules of selection. And that's when evolution and biology comes into play.

Speaker 2

00:36

The following is a conversation with Batul Kachar, an astrobiologist at University of Wisconsin studying the essential biological attributes of life. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description.

Speaker 2

00:51

And now, dear friends, here's Batul Kachar. What is the phylogenetic tree, or the evolutionary tree of life, and what can we learn by running it back and studying ancient gene sequences as you have?

Speaker 1

01:04

I think phytogenetic trees could be 1 of the most romantic and beautiful notions that can come out of biology. It shows us a way to depict the connectedness of life and all living beings with 1 another. It itself is an ever-evolving notion.

Speaker 1

01:26

Biologists like visualizations, they like these graphics, these diagrams, and Tree of Life is 1 of them.

Speaker 2

01:33

So the tree starts at a common ancestor.

Speaker 1

01:36

It's actually the other way around. It starts in from…

Speaker 2

01:39

At the end?

Speaker 1

01:39

It starts from the branches. It starts from the tip of the branch, actually. And then further, depending on what you collected to build the tree.

Speaker 1

01:51

So depending on the branches, depending on what's on the tip of the branch, and I will explain what I mean, the root will be determined by what is really sitting on the tip of the branch of the tree.

Speaker 2

02:01

So we could study the leaves of the tree by looking at what we have today and then start to reverse engineer, start to move back in time to try to understand what the rest of the tree, what the roots of the tree

Speaker 1

02:10

look like. Exactly, so the tree itself, by just taking a few steps back and looking at the entire tree itself, can give you an idea about the connectedness, the relatedness of the organisms or whatever, again, you use to create your tree. There are different ways, but in this case, I'm imagining entire diversity of life today is sitting on the tips of the branches of this tree.

Speaker 1

02:35

And we look at biologists, look at the tree itself, we like to think of it as the topology of the tree to understand when certain organisms or their ancestry may have merged over time. Depending on the tools you use, you might use this tree to then reconstruct the ancestors as well.

Speaker 2

03:01

And so what are the different ways to do the reconstruction? So you can do that at the gene level, or you could do it at the higher complex biology level, right? So in which way have you approached this fascinating problem?

Speaker 1

03:17

We approached it in every way we can. So it's the gene, could be protein, the product of the gene, or species, or could be even groups of species. It totally depends on what you want to do with your tree.

Speaker 1

03:31

If you want to understand certain past events, whether an organism exchanged a certain DNA with another 1 along the course of evolution, you can build your tree accordingly. If you rather use the tree to reconstruct or resurrect ancient DNA, which is what we do. Then in our case, for instance, we do both gene, protein and species because we want to compare the tree that we create using these different information.

Speaker 2

04:02

Okay, well, let me ask you the ridiculous question then. So how realistic is Jurassic Park? Can we study the genes of ancient organisms and can we bring those ancient organisms back?

Speaker 2

04:14

So the reason I ask that kind of ridiculous sounding question is maybe gives us context of what we can and can't do by looking back in time.

Speaker 1

04:23

Yeah, so dinosaurs or all these mammals, in at least for us, is the exciting thing already happened by the time we hit to the larger organisms or to eukaryotes.

Speaker 2

04:36

Oh, to you, the fun stuff is before we got to the mammals?

Speaker 1

04:39

The fun stuff is what people think is boring, I think. The phase that's, well, there's 2 different times in the geologic history. 1 is the first life, past origin of life, how did first life look like?

Speaker 1

04:53

And the second is why do we think that over certain periods of geologic time, no significant innovation happened to the degree of leaving no record behind.

Speaker 2

05:05

So what do we not have a record of? Which part? So you say, the fun stuff to you is after the origin of life, which we'll talk about, after the origin of life, there's single cell organisms, the whole thing with the photosynthesis, the whole thing with the eukaryotes and multi-cell organisms, and what else is the fun stuff?

Speaker 2

05:25

The whole oxygen thing, which mixes in with the origin of life. There's a bunch of different inventions, all that have to do with this primitive kind of looking organisms that we don't have a good record of.

Speaker 1

05:38

So I will tell you the more interesting things for us. 1 is the origin of life or what happened following the emergence of life. How did the first cells look like?

Speaker 1

05:50

And then pretty much anything that we think shaped the environments and was shaped by the environments in a way that impacted the entire planet that enabled you and I to have this conversation. We have very little understanding of the biological innovations that took place in the past of this planet. We work with a very limited set of, I don't want to even say data, because they are fossil records. So let's say imprints, either that comes from the rock and the rock record itself, or what I just described, these trees that we create and whatever we can infer about the past.

Speaker 1

06:32

So we have 2 distinct ways that comes from geology and biology, and they each have their limitations.

Speaker 2

06:40

Okay, so, right, so there's an interplay. The geology gives you that little bit of data, and then the biology gives you that little bit of kind of constraints in the materials you get to work with to infer how does this result in the kind of data that we're seeing. And now we can have this through the fog, we can see, we can look back hundreds of millions of years, a couple of billion years and try to infer.

Speaker 1

07:07

Even further, and I like that you said fog, it is pretty foggy, what we are, and it gets foggier and foggier, the more you, the further you try to see into the past. Biology is, you basically study the survivors, broadly speaking, and you're trying to pitch the sort of put together their history based on whatever you can recover today. What makes biology fascinating also let it, it's erased its own history in a way, right?

Speaker 1

07:38

So you work with this 4 billion year product, that's genome, that's the DNA, it's great. It's a very dynamic, ever evolving chemical thing. And so you will get some information, but you're not gonna get much unless you know where to look, because it is responding to the environment.

Speaker 2

08:00

Yeah, so what we have, that's fascinating, what we have is the survivors, the successful organisms, even the primitive ones, even the bacteria we have today.

Speaker 1

08:12

So bacteria is not primitive and we-

Speaker 2

08:15

Sorry, sorry to offend the bacteria.

Speaker 1

08:17

We should be very grateful to bacteria. First of all, they are our great, great ancestors. I like this quote by Douglas Adams, humans don't like their ancestors, they rarely invite them over for dinner, right?

Speaker 1

08:31

But bacteria is in your dinner, bacteria is in your gut, bacteria is helping you along

Speaker 2

08:35

the way.

Speaker 1

08:36

Well, they get themselves invited in a way. And they're definitely older and definitely very sophisticated, very resilient than anything else. As someone working as a bacteriologist, I feel like I need to defend them in this case because they don't get much shout out when we think about life.

Speaker 2

08:59

So you do study bacteria. So which organisms gives you hints that are alive today that give you hints about what ancient organisms were like? Is it bacteria, is it viruses?

Speaker 2

09:10

What do you study in the lab?

Speaker 1

09:12

We study a variety of different bacteria, depending on the questions that we ask. We engineer bacteria. So ideally, we want to work with bacteria that we can engineer.

Speaker 1

09:23

Seldom we develop the tools to engineer them. And it depends on the question that we are interested in. If we are interested in connecting the biology and geology to understand the early life and fundamental innovations across billions of years, there are really good candidates like cyanobacteria. So we use cyanobacteria very frequently in the lab.

Speaker 1

09:48

We can engineer its genome, we can perturb its function by poking its own DNA with the foreign DNA that we engineer in the lab. We work with E. Coli, It's the most simple in terms of model systems goes. Organism that 1 can study well-established, sort of a pet, lab pet that we use it a lot for cloning and for understanding basic functions of the cell given that it's really well studied.

Speaker 2

10:20

So, and what you do with that E. Coli, you said that you inject it with foreign DNA?

Speaker 1

10:25

We inject pretty much all the bacteria that we work with, with foreign DNA. We also work with diazotrophs, these are azotobacteria. They're 1 of the prime nitrogen fixers, nitrogen fixing bacteria.

Speaker 2

10:39

Can you explain what that is, nitrogen fixing? Is that, is the source of its energy?

Speaker 1

10:43

So nitrogen is a triple bond gas that's pretty abundant in the atmosphere, but nitrogen itself cannot be directly utilized by cells given it is triple bond. It needs to be converted to ammonia that is then used for the downstream cellular functions.

Speaker 2

11:04

And that's what counts as nitrogen fixing.

Speaker 1

11:07

Yes, so nitrogen needs

Speaker 2

11:08

to be

Speaker 1

11:08

fixed before our cells can make use of it. And it's-

Speaker 2

11:13

No offense to nitrogen either.

Speaker 1

11:14

Well, It's actually a very important element. It's 1 of the most abundant elements on our planet that is used by biology. It's in ATP, it's in chlorophyll that relies on nitrogen.

Speaker 1

11:30

So it's a very important enzyme for a lot of cell functions.

Speaker 2

11:33

And there's just 1 mechanism that evolution invented to convert

Speaker 1

11:38

it, to

Speaker 2

11:38

fix it.

Speaker 1

11:39

So far we know there's only 1 nitrogen fixation pathway, as opposed to, say, carbon. You can find up to 7 or 8 different carbon based microbes invented to fix carbon. That's not the case for nitrogen.

Speaker 1

11:53

It's a singularity across geologic time. We think it evolved around 2.7 maybe, roughly 3, probably less than 3000000000 years ago. And that's the only way that nature invented to fix the nitrogen in the atmosphere for the subsequent use.

Speaker 2

12:12

Would we still have life as we know it today if we didn't invent that nitrogen fixing step?

Speaker 1

12:17

I cannot think of it, no. It's essential to life as we know. You and I are having this conversation because life found a way to fix nitrogen.

Speaker 2

12:27

Is that 1 of the tougher ones? If you put it sort of oxygen, nitrogen, carbon, what are, in terms of being able to work with these elements, what is the hardest thing? What is the most essential for life?

Speaker 2

12:45

Just to give context.

Speaker 1

12:46

Well, we think of this as the cocktail. You may hear schnapps.

Speaker 2

12:49

What's in the cocktail?

Speaker 1

12:50

It's the schnapps, right? Carbon, hydrogen, oxygen, nitrogen, sulfur. So there are 5 elements that life relies on.

Speaker 1

12:59

We don't quite know whether that's the only out of many options that life necessarily needs to operate on, but that's just how it happened on our own planet. And there are many abiotic ways to fix nitrogen, like lightning, right? Lightning can accumulate ammonia. Humans found a way about a hundred years ago, I think around World War I, the Haber-Bosch process that we can abiotically convert nitrogen into ammonia.

Speaker 1

13:34

Actually, 50% of the nitrogen in our bodies comes from the human conversion of nitrogen to ammonia. It's helped, it's the fertilizer that we use, urea, comes from that process. It's in our food. So we helped, we found a way to fix our own nitrogen for ourselves.

Speaker 2

13:55

Yeah, but that, you know, that's way after the original invention of

Speaker 1

13:59

how to fix nitrogen. Oh, absolutely, absolutely.

Speaker 2

14:01

And without that, we wouldn't have all the steps of evolution along the way.

Speaker 1

14:06

Oh, absolutely. We tried to replicate in the most simplest way what nature has come up with. We do this by taking nitrogen, using a lot of pressure, and then generating ammonia.

Speaker 1

14:20

Life does this in a more sophisticated way, relying on 1 single enzyme called nitrogenase. It's the nitrogen that is used together with 8 electron donor and ATP, together with a lot of hydrogen. Life pushes this metabolism down to create fixed nitrogen. It's quite remarkable.

Speaker 2

14:42

So the lab pet E. Coli inject them with DNA, so E. Coli does nitrogen fixing in part, or is that a different 1?

Speaker 1

14:50

So some biological engineers engineered E. Coli to fix nitrogen, I believe, not us. We use the nature's nitrogen fixing bug and engineer it with the nitrogen fixing metabolism that we resurrected using our computational and phylogenetic tools.

Speaker 2

15:11

How complicated are these little organisms? What are we talking about?

Speaker 1

15:15

Depends on how we define complication.

Speaker 2

15:18

Okay, so I can tell that you appreciate and respect the full complexity of even the most seemingly primitive organisms, because none of them are primitive. Okay, that said, what kind of, what are we talking about? What kind of machineries do they have that you're working with when you're injecting them with DNA?

Speaker 1

15:43

So I will start with 1 of the most fascinating machineries that we target, which is the translation machinery. It is a very unique subsystem of cellular life in comparison to, I would say, metabolism. And we used to, when we are thinking about cellular life, we think of cell as the basic unit or the building block.

Speaker 1

16:12

But from a key perspective, that's not the case. 1 may argue that everything that happens inside the cell serves the translation and the translation machinery. There is a nice paper that called this that the entire cell is hopelessly addicted to this main informatic computing biological chemical system that is operating at the heart of the cell.

Speaker 2

16:42

Which is the translation?

Speaker 1

16:43

It is the translation.

Speaker 2

16:44

What's the translation from what to what? So RNA to enzymes?

Speaker 1

16:49

It converts a linear sequence of mRNA into a later folded protein. That's the core processing center for information for life. It has multiple steps.

Speaker 1

17:06

It initiates, it elongates, it terminates, and it recycles. It operates discrete bits of information. It itself is like a chemical decoding device. And that is incredibly unique for translation that I don't think you will find anywhere else in the cell that does this.

Speaker 2

17:31

So even though it's called translation, it's really like a factory that reads the schematic and builds a three-dimensional object. It's like a printer.

Speaker 1

17:44

I would divide it into actually even 4 more additional steps or disciplines than what would it take to study it by the way you described it. It's a chemical system. It's the compounds that make it up, or chemicals.

Speaker 1

17:59

It's physical. It's tracks the energy to make its job, to do its job. It's informatic, what is processed are the bits. It's computational, the discrete states that the system is placed when the information is being processed that's itself is computational and it's biological.

Speaker 1

18:22

It's there's variability and inheritance that come from imperfect replication even an imperfect computation. So you're- Oh

Speaker 2

18:30

man, that's so good. So from the biology comes the, like when you mess up, the bugs are the features, that's the biology. Informatics is obvious in the RNA, that's this set of information there.

Speaker 2

18:44

The different steps along the way is actually kind of what the computer does with bits. It's done computation, physical, there's a, I guess, almost like a mechanical process to the whole thing that requires energy and actually, you know, it's manipulating actual physical objects and chemicals because you have to, ultimately it's all chemistry.

Speaker 1

19:08

Yeah, and it tracks this information. So it is almost a mini computer device inside ourselves. And that's the oldest computational device of life.

Speaker 1

19:18

It's likely the key operation system that had to evolve for life to emerge.

Speaker 2

19:29

It's more interesting, or it's more complicated in interesting ways than the computers we have today. I mean, everything you said, which is really, really nice. I mean, I guess our computers have the informatic and they have the computational, but they don't have the chemical, the physical or the biology.

Speaker 1

19:46

Exactly, and the computers don't have, don't link information to function, right? They are not tightly coupled, nowhere close to what translation, or the way translation does it. So that's the number 1, I think, difference between the 2.

Speaker 1

20:03

And yes, it's informatic, and we can discuss this further too.

Speaker 2

20:09

LRH 100%. Let's please discuss this further. Which part are we discussing further?

Speaker 2

20:15

Each 1 of those are fascinating worlds, each of the 5.

Speaker 1

20:18

Yeah, so well, we can start with the more, I guess, the ones that are more established, which is the chemical aspect of the translation machinery. The specific compounds make up the assembly of RNA. Chemists showed this in many different ways.

Speaker 1

20:36

We can rip apart the entire machinery. We know that at the core of it, there's an RNA that operates not only as an information system itself or information itself, but also as an enzyme. And origin of life chemists make these molecules easily now. We know we can manipulate RNA, we can make even with single pot chemistries, we can create compounds.

Speaker 2

21:01

What's a single pot chemistry?

Speaker 1

21:04

That's, I would say when you add all the recipes that you know that will lead you to the final product.

Speaker 2

21:09

This is what original life chemists do, is they come up with this pot, they throw a bunch of chemicals in, and they try to, they're basically chefs of a certain kind.

Speaker 1

21:19

I'm not sure if that's what they call it, but that's how I think of it, because it is all combined in a test tube and you know the outcome, and it's very mathematical. Once you know the right environment and the right chemistry that needs to get into this container or this pot, you know what the outcome is. There's no luck there anymore.

Speaker 1

21:37

It's a pretty rigid, established input-output system and it's all chemistry.

Speaker 2

21:43

So you actually wear a lot of hats. Is 1 of them origin of life chemist?

Speaker 1

21:48

My PhD is in chemistry, but I don't do origin of life chemistry.

Speaker 2

21:52

But you're interested in origin of life.

Speaker 1

21:54

Yes, absolutely.

Speaker 2

21:55

So some of your best friends are origin of life chemists.

Speaker 1

21:58

Just make sure that you have good chemist friends if you're interested in the origin of life. That's 100% requirement, should be mandatory.

Speaker 2

22:07

Okay, so chemistry, so what else about this machinery that we need to know chemically?

Speaker 1

22:12

Well, chemically, I think that's it. You have enzymes, you have proteins. Enzymes are doing their thing.

Speaker 1

22:19

They know how to chew energy using ATP or GTP. They know what to do in their own way. They do their enzymatic thing. So it's not just the ribosome that is at the heart of the transition, but there are a lot of different proteins, you're looking at about 100 different components that compose this machinery.

Speaker 2

22:40

Well, let me ask, maybe it's a ridiculous question, but did the chemistry make this machine or did the machine use chemistry to achieve a purpose? So like, I guess there's a lot of different chemical possibilities on Earth. Is this translation machinery just like picking and choosing different chemical reactions that it can use to achieve a purpose?

Speaker 2

23:14

Or did the chemistry basically, there's like a momentum, like a constraint to the thing that can only build a certain kind of machinery. Basically, is chemistry fundamental or is it just emergent? Like how important is chemistry to this whole process?

Speaker 1

23:33

You cannot have life without chemistry. You cannot have any cellular process without chemistry. What makes life interesting is that even if the chemistry is imperfect, even if there are accidents along the way, if something binds to another chemical in a way it shouldn't, there is resilience within the system that it can maybe not necessarily repair itself but it moves on, however imperfect mistakes can be handled.

Speaker 2

24:02

That's where the biology comes in.

Speaker 1

24:03

That's where the biology comes in. But in terms of chemistry, you absolutely cannot have a translation machinery without chemistry. And so, as I said, there are 4 main steps.

Speaker 1

24:12

These are the core steps that are conserved in all translation machinery. And I should say, all life has this machine, right? Every cell, everything.

Speaker 2

24:22

On Earth. On Earth.

Speaker 1

24:24

Yeah. Yes.

Speaker 2

24:26

When you think of this machine, do you think very specifically about the kind of machinery that we're talking about, or do you think more philosophically? A machine that converts information into function.

Speaker 1

24:37

HALA HANSON I cannot separate the 2. I think what makes this machinery fascinating is that those 5 components that I listed, they coexist. So, for instance, if we, let's just, talking about the chemistry part, we know the certain rate constant, all these proteins that operate in this machinery needs to harbor in order to get the mechanism going.

Speaker 1

25:09

Right? If you are bringing the information to the translation machinery and you're the initiator of this computation system, you need to have, you can only afford a certain range of mistakes. If you're too fast, then the next message cannot be delivered fast. If you're too slow, then you may stall the process.

Speaker 1

25:30

So there is definitely chemistry constant going on within the machinery. Again, it's not perfect, far from it, but they all have their own margin of error that they can tolerate versus they cannot, otherwise the system collapses.

Speaker 2

25:47

So it's like a jazz ensemble, the notes or the chemistry, but you can be

Speaker 1

25:52

a little offbeat. I like that you said jazz, it's definitely true. It's a party and it's like everybody's invited, and they need to operate together, right?

Speaker 1

26:01

And what's really cool about it, I think, there are many things that are very interesting about this thing, but if you remove it from the cell and put it in a cell-free environment, it works just fine, right? So you can get cell-free translation systems, put this translation in a test tube and it is doing its thing. It doesn't need the rest of the cell to translate information. Of course, you need to feed the information, at least so far.

Speaker 1

26:32

But because we are far from evolving a translation, maybe not so far, evolving a translation in the lab, or a machinery that can process information as it generates it. We have not done that yet.

Speaker 2

26:46

That's a pretty complicated machinery, so it's hard for those origin of life chemists to find a pot that generates.

Speaker 1

26:53

Because it's far more than chemistry. You need biology, obviously. You need biochemistry.

Speaker 1

27:00

You need to think as a, I think, network systems folk, you need to think about computation, you need to think about information. And that is not happening yet, except we are trying to bring this perspective. But the more you understand how the information systems work, You cannot, once you see it, you cannot unsee it. It's 1 of those things.

Speaker 2

27:21

So, but you can still rip it out and the chemistry happens.

Speaker 1

27:25

Yes, and chemistry can happen even with, even if you strip some of the parts out. It can, You can get very minimal level of information processing that does not look anything like the translation that cells relies on, but chemists showed from linear, you can generate information that arrives to a processing center in the form of a linear polymer. The informatic part of this system that I think sets it apart from computation and from metabolism comes in if you think about the information itself.

Speaker 1

28:05

So we have 4 nucleotide letters that compose DNA, and they are processed in the translation in triplets. So you have in triplet codon fragments. So you have 4 times 4 times 4. So you have 64 possible states that can be encoded by 4 letters in 3 positions.

Speaker 1

28:29

All right, so...

Speaker 2

28:30

It's so amazing. Yeah. It's so amazing.

Speaker 1

28:33

There is only 1 code that says start. That's the, that there's only 1. And then there's 2, if not 3, that says stop.

Speaker 1

28:42

So that's, that's, that's what you work with. But you can have 64 possible states, but life only uses 20 amino acids. So we use life uses 64 possible states minus 4 of the starts and stops to code for 20 amino acids in different combinations. That is really amazing.

Speaker 1

29:05

If you think about, there are 500 different amino acids life can choose, right? It's narrowed it down to 20. We don't know why a lot of people think about this genetic code is quite fascinating. So far, right?

Speaker 1

29:18

I mean, it didn't do it for 4000000000 years. I don't know, we may wait for another 4000000000 years.

Speaker 2

29:22

But you didn't have those amino acids in the very beginning, right? We

Speaker 1

29:25

don't know. So we would be fooling ourselves if we said we know exactly how many amino acids existed early on. But there's no reason to think that it wasn't the same.

Speaker 2

29:37

So similar.

Speaker 1

29:38

Yeah, we don't have a good reason. But because roughly 20 out of 60 states are used, you're using 1 third of your possible states in the, in your information system. So this may seem like a waste, but informatically it's important because it's abundant and it is redundant, right?

Speaker 1

30:02

So, so the, this code degeneracy, you see this in, that's implemented by this translation machinery inside the cell. So it means you can make errors, right? You can make errors, but the message will still get through. You can speak missing some letters, to the information can miss some parts, but the message will still get through.

Speaker 1

30:22

So that's 2 thirds of the not used states gives you that robustness and resilience within the system.

Speaker 2

30:29

So at the informatic level, there's room for error. There's probably room for error probably in all 5 categories that we're talking about. There's probably room for error in the computation, there's probably room for error in

Speaker 1

30:41

the physical. Yes, exactly.

Speaker 2

30:42

Everywhere there's room

Speaker 1

30:43

for error. Because the informatic capacity is made possible together with the other components. And not only that, but also the product yields function, no, in this case, enzyme or protein.

Speaker 1

31:00

Right, so that's really amazing to me.

Speaker 2

31:04

It is, I mean, in my head, just so you know, because I'm a computer science AI person, the parallels between even like language models that encode language, or now they're able to encode basically any kind of thing, including images and actions, all of in this kind of way. The parallel in terms of informatic and computation is just incredible.

Speaker 1

31:32

Actually, I have a image maybe I can send you.

Speaker 2

31:36

Can we pull it up now?

Speaker 1

31:37

If you just do genetic code on charts, we can pull that up. Yeah, it's a very standard table. So I can explain why this is so amazing.

Speaker 1

31:47

So you're looking at, this is life's alphabet, right? And so I also want to make a very quick link now to your first question, the tree of life. When we try to understand ancient languages, right, or the cultures that use these extinct languages. We start with the modern languages, right?

Speaker 1

32:10

So we look at Indo-European languages and try to understand certain words and make trees to understand, you know, this is what Slavic word is for snow, something like snig.

Speaker 2

32:25

Now we jumped to languages that humans spoke.

Speaker 1

32:27

Humans spoke, exactly. So we make trees to understand what is the original ancestor, what did they use to say snow? And if you have a lot of cultures who use the word snow, you can imagine that it was snowy, that's why they needed that word.

Speaker 1

32:43

It's the same thing for Biology, right? If they have some, if we understand some function about that enzyme, we can understand the environment that they lived in. It's similar in that sense. So now you're looking at the alphabet of life.

Speaker 1

32:59

In this case, It's not 20 or 25 letters, you have 4 letters. So what is really interesting that stands out to me when I look at this, on the outer shell you're looking at the 20 amino acids that compose life, right? The 1, the methionine that you see, that's the start. So the start is always the same.

Speaker 1

33:20

To me, that is fascinating, that all life starts with the same start. There's no other start code. So you sent the AUG to the cell, that when that information arrives, the translation knows, all right, I gotta start, function is coming. Following this is a chain of information until the stop code arrives, which are highlighted in black squares.

Speaker 2

33:46

So for people just listening, we're looking at a standard RNA colored table organized in a wheel. There's an outer shell and there's an inner shell all used in the 4 letters that we're talking about. And with that, we can compose all of the amino acids and there's a start and there's a stop.

Speaker 2

34:01

And presumably you put together, with these letters you walk around the wheel to put together the words, the sentences that make.

Speaker 1

34:10

Yeah, the words, the sentences, and again, you get 1 start, you get 3, there are 3 different ways to stop this, 1 way to start it. And for each letter, you have multiple options. So you say you have a code A, the second code can be another A.

Speaker 1

34:28

And even if you messed that up, you still can rescue yourself. For instance, I'm looking at the lysine K. You get an A and you get an A and then you get an A that gives you the lysine. But if you get an A and you get an A and you get a G, you still get the lysine.

Speaker 1

34:44

So there are different combinations. So even if there's an error, we don't know if these are selected because they were erroneous and somehow they got locked down. We don't know if there's a mechanism behind this too, or we certainly don't know this definitively. But this is the informatic part of this.

Speaker 1

35:03

And notice that the colors, and in some tables too, the colors will be coded in a way that the type of the nucleotides can be similar chemically. But the point is that you will still end up with the same amino acids or something similar to it, even if you mess up the code.

Speaker 2

35:20

Do we understand the mechanism how natural selection interplays with this resilience to error? So which errors result in the same output, like the same function, and which don't, which actually results in a dysfunction, which are...

Speaker 1

35:40

We understand to some degree how translation and the rest of the cell work together, how an error at the translation level, this is the really core level, can impact entire cell. But we understand very little about the evolutionary mechanisms behind the selection of the system. It's thought to be as 1 of the hardest problems in biology and it is still the dark side of biology, even though it is so essential.

Speaker 1

36:11

So this is, yeah, you're looking at the language of life, so to speak, and how it can found ways, rather, to tolerate its own mistakes.

Speaker 2

36:23

So the entire phylogenetic tree can be like deconstructed with this wheel of language.

Speaker 1

36:32

Because all the final letters, those are, that's the 20 amino acids, that's our alphabet. They are all brought together with these bits of information, right? So when you look at the genes, you're looking at those 4 letters.

Speaker 1

36:46

When you look at the proteins, you're looking at the 20 amino acids, which may be a little easier way to track the information when we create the tree.

Speaker 2

36:55

So using this language, we can describe all life that's lived on Earth. It's 1 perspective.

Speaker 1

37:03

It's, we are not that good at it yet, right?

Speaker 2

37:07

So in theory, this is 1 way to look at life on Earth.

Speaker 1

37:11

If you're a biologist and you want to understand how life evolved from a molecular perspective, this would be the way to do it. And this is what nature narrowed its code down to. So when we think of nitrogen, when we think of carbon, when we think of sulfur, It's all in this, that all these nucleotides are built based on those elements.

Speaker 2

37:36

And this is fundamentally the informatic perspective.

Speaker 1

37:39

Exactly, that's the informatic perspective. And it's important to emphasize that this is not engineered by humans. This evolved by itself.

Speaker 2

37:49

Like, right, humans didn't invent this just because we were just describing, we're trying to find, trying to describe the language of life.

Speaker 1

37:58

Yeah, it appears to be a highly optimized chemical and information code. It may indicate that a great deal of chemical evolution and this may indicate that a lot of selection pressure and Darwinian evolution happened prior to the rise of last universal common ancestor. Because this is almost a bridge that connects the earliest cells to the last universal common ancestor.

Speaker 2

38:26

Okay, can you describe what the heck you just said? So this mechanism evolved before the what common ancestor?

Speaker 1

38:36

The

Speaker 2

38:36

last universal common ancestor?

Speaker 1

38:37

Yes, so when we talk about the tree, when we think about the root, if you ideally included all the living information, all the available information that comes from living organisms on your tree, then on the root of your tree lies the last universal common ancestor, Luka, right?

Speaker 2

38:57

Why last? Last universal? Because the earlier universal, it also had trees, but they all died off.

Speaker 1

39:04

We call it the last because it is sort of the first 1 that we can track because we don't know what we cannot track, right?

Speaker 2

39:16

So there's 1 organism that started the whole thing.

Speaker 1

39:19

It's more like, I would think of it as more like a population, a group of organisms than a single.

Speaker 2

39:23

Okay, hold on a second. I tweeted this, so I wanna know the accuracy of my tweet. All right.

Speaker 2

39:29

I sometimes, early in the morning, I tweet very pothead-like things. I said that we all evolved from 1 common ancestor that was a single cell organism 3.5 billion years ago. Something like this. How true is that tweet?

Speaker 2

39:51

Do I need to delete it? No, there's, actually, correct. I mean, I think, of course, there's a lot to say, which is like we don't know exactly, but to what degree is the single organism aspect, is that true, versus multiple organisms?

Speaker 1

40:08

Do you want me to be?

Speaker 2

40:10

Brutally honest? Yes, please. There's still time.

Speaker 2

40:17

This is how we get like caveats and tweets.

Speaker 1

40:19

All right, so first of all, it's not, 3.5 is still a very conservative estimate. That's what's first.

Speaker 2

40:25

In which direction?

Speaker 1

40:27

I would say it's 3.8 is probably safer to say at this point.

Speaker 2

40:31

A bunch of people said it probably way before.

Speaker 1

40:34

If you put an approximately, I'll take that.

Speaker 2

40:36

I didn't. I just love the idea that I was once, first of all, as a single organism, I was once a cell.

Speaker 1

40:46

Well, you're still is. You're a group of cells.

Speaker 2

40:48

No, but I started from a single cell. Me, Lex.

Speaker 1

40:52

You mean like you versus Luca? Are you relating to Luca right now?

Speaker 2

40:57

No, no, no, I'm relating to my, like Lex.

Speaker 1

40:58

Your own development.

Speaker 2

41:00

My own development, I started from a single cell. It's like, it like built up and stuff, okay. That, and then, so that's for single biological organism.

Speaker 2

41:09

And then from an evolutionary perspective, the Leuka, like I start, like my ancestor is a single cell, and then here I am sitting, half asleep, tweeting. Like I started from a single cell, evolved a ton of murder along the way, this brutal search for adaptation through the 3.5, .8 billion years.

Speaker 1

41:37

So you defy the code of Douglas Adams. You are proud of your ancestors. And you invite them over to dinner.

Speaker 1

41:42

And you invite them over to your Twitter.

Speaker 2

41:44

Yeah, And it's amazing that this intelligence, to the degree you can call it intelligence, emerged to be able to tweet whatever the heck I want.

Speaker 1

41:52

That means I'm

Speaker 2

41:53

able to.

Speaker 1

41:53

It's almost intelligence at the chemical level, and this is also probably 1 of the first chemically intelligent system that evolved by itself in nature. Translation.

Speaker 2

42:04

Yeah, so you see that translation is a fundamentally intelligent mechanism.

Speaker 1

42:10

In its own way, and again, if we manage to figure out how to drive life's evolution. If it can evolve a sophisticated sort of informatic processing system like this, you may ask yourself what might chemical systems be capable of independently doing under different circumstances?

Speaker 2

42:40

Yeah, so like locally, they're intelligent locally, they don't need the rest of the shebang, Like they don't need the big

Speaker 1

42:47

picture. So that's a great segue into what makes this biological. The heart of the cellular activities are translation. You kill translation, you kill the cell.