Is there life on Mars? Or Titan? What are we even looking for? Without a formal definition, inquiries into the stars just echo noise. But then, perhaps, the noise contains a signal… To find life elsewhere in the universe requires us to wager a defined biology, to come to terms with what it means to be alive. Looking out is looking in, to ask the hardest question ever: How do we find something we might not recognize as what we’re seeking?
Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and each week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.
This week we talk to SFI Program Postdoctoral Fellow Natalie Grefenstette, who works with SFI Professor Chris Kempes (whom we spoke to on Episode 17) on the multi-institution, NASA-funded Agnostic Biosignatures Project. Over the next hour we discuss how new approaches to astrobiological research may help science finally define the nature of living systems, and where and how to find them in the cosmos.
For show notes, research links, transcripts, and more, visit complexity.simplecast.com.
If you value our research and communication efforts, please consider making a recurring monthly donation at santafe.edu/give, or joining our Applied Complexity Network at santafe.edu/action. Also, please consider rating and reviewing us at Apple Podcasts. Thank you for listening!
Natalie’s Google Scholar page:
"Adaptive properties of the genetically encoded amino acid alphabet are inherited from its subsets"
"Agnostic Approaches to Extant Life Detection"
"Agnostic Polymer Detection Using Mass Spectrometry for Astrobiological Samples"
"Mars Extant Life: What's Next? Conference Report"
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Podcast Theme Music by Mitch Mignano.
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Transcript produced by Podscribe and edited by Rayyan Zahid.
[Time Stamps start at the beginning of the interview, not the episode:]
In the sort of like, human and personal, and just ask you about how you got interested in this work? How you got involved? How you became a scientist? What drew you into this field in the first place?
Sure. That's the question that I actually get a lot and have recently been asked by a few people and I always have trouble answering because to me it's just so obvious that it's an interesting question. If you know what I mean? I think all of us have been thinking about this for eons. And on a personal level, I feel like everyone that I know has been asking those questions, right? Are we alone in the universe? How did we come here in the first place? How did we emerge from seeming nothingness? And so, those are questions that I started asking myself around the same age that everyone else that was probably like 10 or something.
And I just got obsessed with those questions. And I thankfully was brought up in a sort of scientifically minded environment with a lot of supportive people around me and got given books about astrobiology, the few that were there. Cause it was quite a niche field in a way and still is in some ways, but kind of started or continued talking about those questions over and over again. And when people would ask me what I wanted to be, when I grew up, I said, astrophysicist, they didn't really know the word astrobiology at the time.
It wasn't necessarily as widespread and just kept being interested in those questions. Like how does life emerge from non-life like that transition is something that fascinates me. And I think it's very linked to the question too, of how different life could be in the universe, because it's all based on that initial emergence and then link to other questions. Like how would we find it if we looked for it? How would we go about going on another planet or using remote detection techniques to even look for those things, if we don't know what we're looking for?
So, that's kind of what got me started is just this fascination, that curiosity that everyone kind of has, and I wasn't deterred from pursuing it.
And then how did you end up at SFI? Like how did your path and research get you into this conversation and conversations that you've been having with your various research collaborators? Like the 72 hours of science piece, which I hope we get to talk about on the podcast soon, y'all speculated on a tri-parental alien civilization. What got you there?
Yeah, sure. I guess once I was interested in those questions, the next step was, going to university and things like that. And I decided to major in biochemistry, I was in the UK, so it's not quite majoring. Like you just focus on one subject really. And I kind of thought that biochemistry was a merge of biology and chemistry, which seemed like exactly what you would need to study to do something like astrobiology and kind of understand those relationships between chemistry and life. It's not at all that it's much the study of life as we know it on earth, obviously.
And proteins and like metabolism and things like that, which was not exactly what I was looking for, but laid the groundwork for understanding how life works on earth. So, it wasn't a waste of time. And then I was like, okay, enough of that, I know how life on earth works to the level that I need to. And so, I was interested in kind of going down a level, I don't know if, if people on a podcast have been talking about this at all, but a lot of people talk about this hierarchy of scientific disciplines. And sometimes people phrase it in the sense of like, one's more important than the other. That's not what I mean.
But if you study something like biology, it's actually based on chemistry because everything in biology is made of chemistry, but chemistry is all physics and physics is all math and there's like a whole road of things. And so, I wanted to kind of go down a level into the chemical realm. And so, I pursued my PhD in organic chemistry, which was prebiotic chemistry. I was interested in how does life emerge on earth or how did it emerge on earth? And we can come back to that if we want to. But I started, I guess, looking at how things interact on a molecular level, but that didn't quite satisfy me either.
I wanted to kind of go a deeper level and not necessarily into physics, but I guess more into this theory kind of realm and wanted to explore these relationships that lead to certain emergent behaviors in life, I guess. And so, these general properties of life are something that people in astrobiology are interested in. And I know Sarah Walker has been on this podcast and my supervisor, Chris Campus as well. And so, that got me looking into their work because I was really interested in that kind of approach to the problem of like this bigger picture approach.
And so, I started reading a lot of that and contacted various people, but ultimately the interestingly, the way I found a job at SFI was through Twitter. So, I guess that's thanks to you. And I'm not really super active on Twitter or anything, but I was kind of just searching keywords, looking for a postdoc. And I found an ad for theoretical astrobiology. That is exactly what I’ve been looking for. Those are the keywords I was searching and this popped up and it's the position I currently have. It is funded through this grant called the laboratory for agnostic biosignatures and that's a subject that I’ve always been interested in in astrobiology because I think it's very linked to these general properties of life.
And the emergence of life in general is how do we look for life if we don't know what we're looking for? And so, the position was kind of both that like a more applied part of it, which is actually like, how do we look for these things, but also asking questions about like, what are certain properties that we think might be universal to life and things like that. So, my work now is kind of on both of those sides and that's how I got involved with the SFI community.
That's actually the perfect place to dig in. I wanted to talk about your contribution to a conference last year on Mars, extant life. What's next, the search for life on Mars and you and your collaborators proposed a number of these different agnostic techniques, these approaches. So, this is, I think this is a really good entry point for people. I'm always the one bringing up the science fiction on this show, just, some of my favorite works are like tours of speculative proposals or just how radically alien life could really be, not just inorganic but like holograms made out of magnetic vortices, the most bizarre stuff.
But of course, the question that all begs is how would you even go about identifying these things? And so, you have a list here and I would just love to go with you down this list, which, we will provide links to these abstracts as well as to the end conference summary that you and a large number of collaborators worked on really interesting stuff. But let's just start with that. What would be possibly the most intuitive or like low hanging for people, which is chemical complexity. So, why that, and then how do we go about looking for it?
Sure. So, chemical complexity, I think is a term that's kind of intuitive for a lot of us. I think even if you're not in the field, you can kind of imagine what people mean by complexity. But I think that's a problem that a lot of people have SFI have is kind of defining what they mean by complexity. And I remember my first week at SFI, I asked people like, what do you mean by complexity science? And everyone gave me a completely different answer. So, it's kind of the same thing with chemical complexity. Like they're a bajillion indices out there trying to kind of quantify what we mean by that.
How is a compound more or less complex? How do we define that? So, there's been recent work in the last few years done by some collaborators of our grant group in Glasgow. So, there's Lee Cronin. Who's been trying to develop this along with Sarah Walker, actually. The kind of theories of how can we quantify chemical complexity for the problem of astrobiology or other problems like that. And he's not necessarily the first to ever come up with the idea of an index like that, but it's, I guess trying to make it a bit more intuitive in a way.
So, I'm not going to describe it in detail because I wouldn't be able to do it justice necessarily. But the idea behind this new chemical complexity index is using different building blocks. How many steps would you need to build the, that you see before you? And so, they give good examples of that. Aren't necessarily chemical to help the reader in their papers. For example, to build the word banana, how many subunits essentially in steps would you need and things like that.
And so, the more steps you need to build something, the more complex it is. So, that's one way of looking at it and there are other ways of looking at it. And a lot are, are based on like different chemical factors, how many atoms does a molecule have or how big is it? How many bonds, et cetera? There are many different ways of looking at that compound. So, that's still not necessarily solved, but some people like Lee Cronin and Sara Walker are working on that. So, that's kind of one way of looking at chemical complexity. When it comes to how do we detect it?
That's another matter. Cause how do you actually link that more like theoretical aspect of the complexity that you might see if you actually have the chemical structure of a compound. But when we go on Mars, for example, the technology that we have is not as advanced as we would need to identify compounds completely. And even on earth, honestly, it's quite difficult. If you have a mixture, a completely unknown mixture, it can be quite difficult to see what's in there on a molecular level.
So, imagine doing that on another planet, right? The machines that we send on Mars, we're completely blind to what's there. And we kind of have to make use of those very simple techniques. One of them, for example, is mass spectrometry. That's quite popular because it's been used over and over again in different missions. It's called high heritage. That's what we call machines. It's been sent over and over again. It's kind of shown that we can fly it or we can sit on missions. It's quite popular, it's online, tons of missions. And so, that technique gives us the ability to kind of see the masses of what the compounds are in a mixture it's kind of in the name mass spectrometry.
Some people like Lee Cronin's group again, have been looking at the relationship between a mass spectrum and the complexity of molecules that are in there. And I don't really know what stage necessarily they're out there, but that's an interesting idea. It's like, how can we use something as kind of crude in a way as a mass spectrum, to look for this property of compounds, complexity, that might be useful to say whether they're biogenic and origin or not, whether they come from biology or not. In our group, we kind of use that idea in a way among others of like, how can we make use of this simple tool of mass spectrometry to look for signs of whether this came from biology or not.
And I guess the main question and the main problem that I'm working on is what do we mean by that? Like how do we know if they're a science of biology? Because traditionally in the past, a lot of people were just looking for some specific molecules that I knew are associated with biology on Earth. And looking at that, it makes sense that you would start like that. That you would start looking for things that, because that's kind of the only place that you can start in a way. But I also found that a bit frustrating, I guess, in a way it's like, why are we just looking for these very specific things?
And so, that's kind of in the movement recently in the community, a small group of us are kind of asking us and we're not the first to think that, but this is an effort that's being funded right now. And so, a part of my postdoc is asking these questions and trying to come up with answers. So, there are several ways of approaching that you can either kind of look at it from the ground up. So, have theories of what you think might be general to life on Earth and kind of go from there. Or you can kind of go the other way around. It's like without necessarily knowing what the theories are from general properties or anything. You could just kind of look at what's different between biology and non-biology.
So, between biotic samples, you can kind of look for some specific differences. So, obviously you'd have differences. Like there's no DNA in the biotic samples, but that's not really abstracting the problem, but then you could look at like leak, run-ins doing, you have very complex molecules in the biotic samples, whereas you might not have those complex molecules in the abiotic one. And they're a good theory as to why that wouldn't be the case because you might need, specific sequential addition of certain things to make a complex compound.
But what we're doing in our group is also kind of looking more at the sample level as a whole. So, kind of at the community of molecules that are there. And we're interested in understanding if there are any patterns like that, in the distribution of the compounds that are there, that could be informative of whether it came from biology or not. So, it's kind of almost an ecological viewpoint of the problem of what's the relationship between these molecules and how would you detect that in something like a mass spectrum?
Yeah. So, to dive into that a little bit more, when you go into a little bit more detail in the conference abstract on the lunar and planetary science conference on agnostic polymer detection with mass spectrometry, it's like hindering on this observation that polymers, not necessarily DNA and RNA, but some kind of polymer is likely to be, and this is again akin to what Lee Cronin and Sara Walker are looking at, long, complex like metallic compounds and so on.
But there's a note in here that the use of polymers allows life access to a larger chemical space, as well as reliably storing propagating information. So, in order to identify these, in order to light prosecute this hypothesis, you're involving some pretty kind of sophisticated techniques that involve machine learning. And I'd love to hear you unpack the actual methodology here for people and explain how you get from the raw data that's being transmitted from like the ExoMars 2020 Rover to something where you can say, maybe that looks a form of life that we have never recognized or identified before.
Sure. So, there are kind of two aspects to the problem of polymer detection. The first one is actually detecting the polymers using something like a mass spectrometry. The second one is even if we detect it, how can we tell if that polymer might be coming from a biotic system or not? And so, the project kind of has these two steps. And the first one I think is, is the one that we put in the abstract that you were describing using those Fourier transform and machine learning and things like that. So, that's kind of what we're working on now.
And so, what we're interested in is, basically polymers are like beads on a string, right? So, you have like these repetitive units that are strung together to make this kind of long macromolecule and life makes use of that a lot. DNA is a polymer, proteins are polymers. And so, what I wrote there about accessing a larger chemical space, that's what proteins allows us to do with all the amino acids using together and folding in a certain way. It accesses a different part of the chemical space and allows us to do these really interesting reactions like with enzymes and things like that.
And it also in the form of DNA allows us to store information. So, the theory is that other lifeforms might also make use of that. But then the second part of the problem is how do we distinguish those polymers that have been utilized by the biotic system from those that are naturally produced in certain environments. Because polymers are also easily produced in different environments. So, to come back to the earth, for example, or even in meteorites, we detect polymers and things like that. And so, then it's a question of what kind of complexity do those farmers have.
And that's something that we'll kind of work on in the future is trying to understand if there are certain aspects of polymers, perhaps in the sequence of the units that they have, or in the units themselves that they use, the compounds that they use to form those strings, that would be diagnostic of coming from biology or having been through the funnel of biology. But the first problem is how do we even detect it in the first place? And so, that's where those tools that I was mentioning come in, Fourier transform, auto correlation and machine learning.
It's because since polymers are these kind of beads on a string structure, you'd expect them to fragment in a way that would show this repetitiveness in the spectrum. Because mass spectrometry, fragments molecules as well when you use it. So, there are tons of different techniques that I won't go into detail, but things like you shoot a laser at a rock essentially. And so, breaks up what's in there to some extent, and then you can do more interesting things like tandem mass spec, where you fragment a second time and things like that. But anyway, you end up with this kind of mixture that is kind of almost processed to some extent and shows the fragmentation of molecules.
So, with these beads on a string, the polymers you'd expect to see because it's not just one molecule that's breaking up, it's a collection of them, otherwise you wouldn't be able to detect it. And so, you'd see like, where it broke up after two units or after three units, four, et cetera. And so, you'd see this repetitiveness and in the mass spectrum. And so, if you're an expert and you know that there are polymers in there, you can kind of see it with your own eyes. But the problem is with the resolution that we have on these machines on Mars and with, there's compression of data being when it's sent back and you can only do it once on that one sample and things like that.
Like there are a lot of limitations. And so, there's a lot of noise in the data. And that's what we're trying to understand is how can we reliably tell whether there's a polymer in there and then next steps would be how long has that polymer, how many different types of units that have of it as different feeds and more information about the composition essentially. And the more information we have, then the more information we'll have for that second step of whether we can tell whether the polymer came from biology or not.
So, one of the interesting things I thought about this process was that you were looking for to see if there was an underlying power law in the data. That there is that you're looking for it like a Zipf’s distribution, and that would help you tune the inquiry to determine the noise that you're getting from the instrument itself. I mean, because this is one of those things that's like, it's almost become a joke about like a complexity science that it's like, everybody's looking for the power laws, but like in this case it's like a really interesting kind of subtle application of this. And I'd love to hear you just unpack that a little bit more.
I'm not sure I’ll be able to unpack it too much because that part of the project wasn't my work. But as I understand it, so my colleague Lu Chou was working on that of like what, what's the relationship between the noise and the signal in these spectra that we have. And is there a way to just remove the noise? And so, we did kind of look at the frequency of different intensities and peaks in there. And there seemed to be at some point like a sort of tailing effect, you had peaks initially that were quite high, that seemed to be the signal.
And then as you'd expect kind of, there's less of the noise and there was this interesting relationship that looked like a Zipf’s Law. So, that's something that she explored for a bit to see if we could use that relationship to kind of mark off where the signal ends and the noise starts and kind of get rid of it as this sort of preprocessing step, but also as a way to recreate noise if we wanted to, because part of the project is also for us to use artificial data. So, we're kind of creating mass spectra of our own.
So, we're writing code to create, well, if we have a molecule, how would it break up in a very simplified manner in this machine? What spectrum would it give us? And then can we add things like noise to kind of make it a bit more complicated for us and then work at the problem from that end? So, that's a way for us to kind of have a test bed, to test out our different methods before looking at the real data that we don't have yet from Mars, but before the data from ours, we could also use real data from earth, obviously, cause they're replicas of the machines that are sent on Mars that exist that NASA has.
And so, we can kind of use those two to run different samples and like test out different things. But as you'd imagine, there's a limitation of how many spectra we can acquire that way because it's, well, COVID aside, it's a lot of manpower and like you're limited by how many samples you have and things like that. Like it takes a lot of time. Whereas if we're creating artificially these things, even though it's not, a perfect mimic of what we might have in the lab, it can help us test out different things. So, that's what we're doing now. And worked out well because of the global situation right now, but our work is artificial and using computers.
So, that's great. And it means that because we can essentially create a lot of data, we can use things like machine learning. So, that's where that comes in is that we're creating like all these different spectrum of fake polymers essentially, and trying to either make them a bit more realistic, making essentially proteins and using like acids to construct these polymers, breaking them up, et cetera, adding noise or not, or we can make them even more abstract than just pick a number and add them together to make this polymer.
And then we can put them through something like machine learning that one of our collaborators is doing, and look at what machine learning is able to do with this problem. Like whether it would be able to help us with this kind of detection problem in the first place and whether it can give us even more information down the line of how many units, the things I was saying earlier, how long the polymer is, how many units does it have and things like that. And machine learning is obviously a very powerful tool, but you also have to be very careful with it.
And I am by no means an expert in it. Then that's why we have these collaborators who are also helping us and who know a lot more than I do, but it seems to be able to pick up really interesting information. And so, that's been really fun to watch as well.
I don't know how meaningful this is as an observation for our audience, but you know, this, I think points to like the structure of this research points to a common theme across human pursuits, which is, it sounds to me a whole lot, running a military exercise or practicing free-throws and a windstorm. You're looking for a limited number of encounters, ultimately, and a lot of this, the way that science of this kind is practiced is about, you said, it's about making the most of limited opportunities.
Yeah. That does it sort of pours back into this question of how you're devoting your life and work to rehearsal for first contact, rehearsal for, preparing for anything. How do we prepare for any possible scenario or would like to tie in Melanie Mitchell's work? How do you get to levels five independence with a self-driving car? Like how do you prepare a vehicle for, all of these like extremely low frequency possibilities, how are you training your own machine learning algorithm for the unthinkable?
Yeah, exactly. And in the case of space exploration, it's clear that as you say, there aren't many opportunities for any encounter and it'd be such a shame to spend all this time and money sending something on another planet and then missing something so obvious, but just because we didn't look for it. So, it also kind of ties into the whole point of agnostic biosignatures as a project is trying to fight that like the traditional way that astrobiology has been approached when it comes to life detection, which like, I'm not criticizing, it's obvious why it was done like that before, because that's kind of the only thing we knew, but we're past that now.
And so, it makes sense to kind of abstract the way we look for things. Even if it's a simple abstraction and not completely agnostic, looking for polymers instead of looking for DNA. And so, that's the whole point of the project is to make sure that we don't have blinders on when we're going on another planet and looking for something that's so specific that we're missing all the rest outside. And I remember telling someone wants to conference who didn't share that opinion. I was trying to find a sort of metaphor and I'm not sure it's perfect as an analogy, but I was like, it's like, if you're going in a forest and you have a hatchet and you're told to look for humans as a proxy for life, go look for life.
And by that we mean humans and you're chopping down trees to look for it. And it's like all around you, there's this beautiful life around you. And you're not even noticing it because you're so focused on just one thing. And so, it's just trying to abstract the search and hopefully we'll find something interesting one day
And, really, not to spend too much time on this, but this has some pretty steep, ethical concerns associated with it because obviously the history of the exploration of our own planet is a tragedy of the exact flavor that you just described. Oh, this continent is uninhabited by, people not even recognizing civilization while they're trotting over it. So, this is something that, I think should we make the kind of mistake that you're talking about? It's the kind of thing we would have a hard time living down there. It's really important that we get this right.
Yeah. And that's both on the side of detection and of contamination and that's a big issue too, in the field of planetary protection. And there are a lot of people working on that. And I think it's very important. And as you said, there are a lot of ethical implications to that. And I think we need to take the utmost care to make sure even just where science like, to make sure that we're not contaminating our own samples with our own biology. Otherwise there's no point in us doing this because we'll just find life as we know it because we brought it there with us and it would be so frustrating if that ever happened.
But also, you're right on an ethical point. Like I don't think personally that we have the right to go there and just completely take over the ecosystem that might be on another planet. And that comes back to things like also terraforming Mars, which some people are very keen on. I don't think we have the right to do that, but that's just a personal opinion. That could be enough.
I'm sure a lot of listeners know that was very deeply discussed. And Kim Stanley Robinson's Mars trilogy, that ends up sort of being the crux of that whole political argument through that series. And it's fascinating how those concerns and those, those debates on earth transpose into these other worlds. But, I want to bring it back to this question of how do we abstract life and you know, how do we think about it in the most fundamental ways and to link this to of all things, complexity, economics, and the understanding of an economic system as out of equilibrium as a form of metabolism on the surface of this planet, one of the other things that you and your colleagues discussed in this paper is looking for disequilibrium, redox, chemistries, and other instances, not of like the sort of components of life as we know it, but evidence of life has a process. So, how are you and the other people in this field thinking about that and pursuing that particular approach?
Sure. So, I don't think I can necessarily tie it in nicely with complexity economics. Cause I can't pretend that I know anything about that
Smoke stacks. “Oh, there's an industry.”
But when it comes to looking for a disequilibrium, that is again, by no means a new idea, the way that we're approaching it is to abstract, the molecules that we're looking for. So, people in the grant are looking for this kind of exchange of energy as a way to show that there is disequilibrium and I’ll come back to why we're looking for that. And other people, including the group that I'm part of within this larger group is also looking for evidence of a metabolism at the molecular level.
So, it's more coming back to what I was saying earlier about the distribution of compounds that you might have in a sample. For example, a specific distribution might be distinctly different from an, a biotic sample, no life because of metabolism and because life needs to have this kind of chemical network in order to function. And I’ll just caveat what I'm saying here by everything that we do in our research and that I do in my research is based on life as a chemical system and as cool as it is to know like theories of life as a hologram, that is something that artificial life community is working on.
And it's something that I really want to get into more. And so, I'm trying to read more about that community. It's just a bit harder to look for it at the moment. So, I’ll just focus on chemistry for now and just wanted to put it out there because that's valid too. And it's very interesting. It's just not what we're doing right now, but why metabolism is a great question. I think it's one of the important pillars of life. And I think a lot of people would agree with that and, Sue Kaufman and autocatalytic cycles and things like that is also rooted in SFI history.
And I actually like had read some of Stuart Kauffman's books before I was hired. Didn't even like connect the two together. Like I didn't even think about the fact that it was at SFI, but anyway, I just think that this idea of life and disequilibrium being so intertwined, that's something I’ve been thinking about more recently and a lot of people will state that life needs to maintain itself at a low entropy state. Like as if that was just like an obvious fact.
And that always kind of made me wonder, and I was kind of thinking it was a bit circular in a way, because for me, it's kind of the other way around, it's not that it needs to maintain a low entropy, is that without having that low entropy state, it wouldn't be life. But that might just be the same thing phrase in a different way, but it's just kind of to point out that whenever you think about these deeper questions of what life really is, you usually get a bit lost in your thoughts or that's what I find like it's just so confusing and gives you so many existential crises.
It's a very difficult problem obviously, but nevertheless, the disagreement we have in life are, are very linked and you can see that in the way that life briefs, for example, the gasses that life uses up and produces that links to gas at the planetary scale being in disequilibrium. And that's a clear bio signature on earth. For example, it's having things that co-exists in the atmosphere that wouldn't be able to coexist normally as in chemical species, that should kind of react together and form something, but they, we can detect them in the atmosphere.
And so, that means that they're constantly being produced or used up. And so, that's a signature of disequilibrium, for example, on a planetary scale that is due to life. And that's something that people propose as a biosignatures for other worlds, either by looking for those specific chemicals species that shouldn't be coexisting with coats, things like oxygen and methane and things like that, or in a more agnostic approach, just looking for what species are we seeing in the atmosphere? What chemicals are we seeing and thinking about, whether it makes sense of like, what we're seeing is that compatible with a completely lifeless body, or do we need to invoke something like a planetary scale ecosystem in order to account for what we're observing?
And so, that's a sort of planetary scale agnostic by saying nature. That would be good for like remote detection, for example. But in all these cases, it's really difficult to actually tell whether he came from life or not, because we don't necessarily know the null hypothesis. Like we don't know what the environment could produce without life. So, it becomes very complicated. So, for all of these things, we actually need multiple lines of evidence, brand new science, to be able to actually tell whether there is life or not, ultimately, which might still be more difficult than I'm describing.
It sounds super simple when I'm saying it now, it’s like, just have a few evidence things and it'll be fine. But yeah, when it comes to disequilibrium, you can also see it at a smaller scale. So, these redox pairs that are mentioned in this abstract and the energy does being transferred between them is something that life makes use of in order to harness energy. And so, the ability to detect either a redox pair in disequilibrium or the transfer of energy between them would both be kind of valid ways of at least detecting that there's something there that's compatible with life.
Yeah. And, to link that back to the first part of this conversation, you mentioned elsewhere in this abstract, that if you're looking at chemical complexity, that there may be a threshold beyond which complex molecules are unlikely to form without that supporting biological machinery. So, really these, you said, these are just two different ways sort of noun and verb of looking at how do we detect these things. So, you, you brought up a life and aside from the fact that the idea is extremely cool and that there's a really cool conference going on for this stuff, you know, organized by former SFI educator, Juniper Lovato, shout out. Something that I find kind of interesting about the methodologies that we've discussed here. Some of them is that, you said, it requires the creation of enormous artificial datasets, which to me, I can imagine eventually tailing into a situation where we end up simulating complex alien life before we even find it.
And this is, I hope a bridge we can walk across to the last piece. I want to, I want to talk about with you today, which is the paper that you coauthored in nature research scientific reports on adaptive properties of the genetically encoded amino acid alphabet are inherited from its subsets. So, this is like for anybody who is familiar with the writing of Simon Conway Morris, life's solution that really beautiful book, many, many people over the years have asked these questions about why it is that we see life take the shape that it has on this planet and asking these parallel set of deep questions about the balance in evolution, inevitability, and contingency, given a specific set of components.
And in this particular piece of research you and your coauthors created, I love this an enormous set of xeno amino acids to ask this question of why it is that we have that like all life on earth today uses this very, very narrow slice of what is possible given the components that we have on this planet now. So, could you talk a little bit about the basis for this and then how you and your colleagues dug into this particular question?
Sure. So, I’ll just preface it by saying that I joined this project that was being led by Jim Cleaves at ELSI a bit later in the game. And I worked there for about five weeks. So, I contributed a little bit to that project, but I think what the most interesting part of it was actually the papers that were published before that we built upon in this specific project. And so, I’ll try and talk about that a little bit, because I think that's, what's fascinating about their work. So, the work here is looking at whether the genetic code that we currently have with 20 amino acids, if there's a way for us to decipher how it was built from just a few amino acids at first, but the work that it built on was why those 20 in the first place.
And I think that's even more interesting as a question in a way, and that there were more interesting results that came out of that in my opinion. And so, what they did there was, as you said, built this kind of huge set. I can't remember how many, but like thousands of amino acids and kind of process them in a way to have their like certain attributes of the compounds, things like molecular weight and how acidic a compound is or not, or how hydrophobic it is, these kinds of properties of molecules.
And there are certain ways of doing that, coding, there's certain packages that you can use that based on like a certain structure of the compound, they can kind of predict those properties, even if they haven't been tested out in the lab. And so, the project that I joined was they'd already shown that those 20 amino acids, essentially the ones that we use in our biology, we're better at covering the chemical space and a random 20 from this xeno amino acid set. And what I mean by better, what they meant by better is that it covered the chemical space and I’ll come back to what that means more evenly and more broadly in the 3D space.
So, the chemical space as they defined it. If I remember correctly, it was a three-dimensional chemical space based on the size of the molecule to hydrophobicity of the molecules. So, how much it likes water or not. And the PID isoelectric point of that molecule, and that was trying to capture one of the interesting properties of amino acids is that they have like different pKa’s and different to do certain reactions that are essential to proteins functions. And so, they're trying to kind of capture that through those three properties.
And I hope that those were the right ones, but those, I think are the ones that we use at least in a follow-up paper. So, and I think I'm sure that they also looked at other properties and whether it, it, the results also applied. I wasn't there for that part. So, I can't speak for that. But anyway, it was just really interesting that, they picked 20 random amino acids from this huge set that they created, which also included the canonical amino acids, the ones that we use in biology. And whenever they compare those sets in terms of how much they covered the chemical space and how evenly they covered that space, they found over and over again that the 20 amino acids on those 20 together were, if not better, at least like among the best possible sets that you could have of 20.
And the reason why even ness was something that they were interested in looking at is that's an intuitive notion too, is that you'd imagine that if you want to have 20 amino acids in your genetic code to build things like proteins and unfold and have catalytic activity, it would make sense for all those 20 to have slightly different properties so that you have, you can kind of maximize how you're able to use the chemical space. And so, that was what being covered with even is, and then the spread over the chemical space is also kind of intuitive is that it would make sense to kind of cover all the possible properties that you want to cover.
So, can I just dig in here just because I feel like part of my job on the show is just to send tentative, hypothetical feelers out to like the way that this research might inform research into other kinds of systems and listening to you talk about this and reading this, this paper, I couldn't shake the implications of this kind of thinking for other work into the, the diversity of team building, how you select people for a particular function.
And then also how in studying, doing textual and historical analysis of, what survives history, what, what it is that we decide to keep culturally that something becomes canonical precisely because it suits a particular set of selective demands that like the reason that the Septuagint picked the particular books of the Bible that have been like leftover is canonical texts has something to do on a very fundamental level with why you don't want to put five identical people on the same team or why, we don't have a different 20 amino acids that are coded for by our DNA. So, anyway, just a stray thought.
Yeah, well, that's actually kind of what this follow-on project that I helped with was about, was whether we could actually reconstruct which amino acids might've been added in which order, and we didn't quite get there in that project. I don't know if that's continued in that group actually, but I think what that paper was about was whether there is a way to see whether if you start it with like three amino acids, assuming that life, or protolife had just three amino acids at its disposal, which might've been, the ones that are easily produced for by and the environment and things like that, glycine is a super simple amino acid that's assumed by most people would have been widely available.
We can even detect it in space. So, it is just like easily produced. So, it would have been available to life or protolife. If you start it with those three, how do you add a four? And which fourth would make sense to add if you know, that those 20 are being used ultimately, and it's kind of that, it only makes sense to add this fourth because we already had those three and et cetera, the fifth one and things like that. And so, it's an interesting question because you can't just jump and go to the other side of the chemical space like that wouldn't really make sense and also happens that those molecules are probably more complex anyway and harder to me. So, there is this kind of question that you were saying the same as like building a team or the Bible apparently,
Or, really like fan fiction. When does fan fiction become canonical? Like when, when it becomes useful enough to the audience of a particular franchise to have to like, to be able to build narratives that are able to explore a larger narrative space, but then there's, this paper talks about, brings in a, a scaling dimension too, which is why we don't have more than 20 and that you get, you get locked in after a certain amount that it becomes to grow the code in the same way that like growing an elephant at some point, it just not worth it to add more elephant. Right. So, I would like to hear you speak to that piece of it as well.
Yeah. The question of why we only have 20 or why we have 20 in the first place is a very interesting one. And I know there are a lot of theories and I don't think that our paper answered it necessarily, but it is very interesting. And I think in this line of research that I was part of, it was very much about what you said. If we're already covering the chemical space fairly well, what's the advantage to having extra amino acids in a way, cause you're already kind of covering everything you need. And there are extra costs to having more namely like the current genetic code is a three base fare codon.
And so, if we have more, there is redundancy. I mean, there are theories as to why it was three and that limits how many amino acids you can have and things like that. And I mean, I honestly don't know if it is just a matter of the chemical space or if it is just frozen accident theory is also a good one. Just like that's kind of what happened at the point of maybe LUCA, the Last Universal Common Ancestor. And until then it was just like frozen. And if you change anything, then it'll break down.
But think for me, what really interested me in this work was the fact that the ones we're using were the best ones in that sense. And we also did this study wanting that in a way. So, I know that it's not necessarily the answer to everything, but I found it fascinating just to see that in the way that we were approaching it at least, or the group before me was approaching it. The answer was undoubtedly that the 20 amino acids that we're using now are a good set and there might be other ones that are as good or slightly better.
I can't remember if there were slightly better ones, but that already know in the same ballpark. And why that was fascinating to me is that when I started the field and I had told you earlier that I was interested in this since I was like 10, I was very much of the mindset that there's no way life elsewhere would look remotely like ours. And it's just stupid that everyone is looking at carbon and water, and we're looking at amino acids. Like I was very against like the status quo and then like during my PhD and the origin of life community, and also during this work where in both cases, we showed that there are certain reactions for my PhD, for example, that you could do over and over again and in different conditions.
And it will be a very, very similar outcome. Like some molecules just want to be made. And I hate when people in part want on tamale heels, but it is the easiest way of phrasing it, I guess.
Or material agency, which is the way that my humanities friends talk about this.
That these molecules are just the natural product of that reaction. And so, they're more stable. They're whatever means that they're the outcome they are. And there's some obvious building blocks to RNA that are just so obviously easily made in different reaction conditions that makes sense that ribonucleic acid came about and there are multiple ways of looking at it and it's always bad to comes out. And I was kind of frustrated. Like I was just like, why is it that one?
What makes sense too, our biology is making use of what was available. And so, what was available, must've been abundant and easy to make. And same with the amino acids. Like the ones that were easily made were probably the ones that were incorporated first. And because for some reason, our biology made use of amino acids and then proteins, then this genetic code arose because it was better at covering the space, but it's still kind of frustrating in a way for me because rejects a little bit that idea that life might be different, but it also doesn't completely because I think what's more important is what environment life arises in.
And so, if we had a copy, an exact copy of the earlier, perhaps we get very similar life, we might get a slightly different genetic code. We might even not have discovered amino acids. Like there might be luck in this too, but it's kind of hard to tell where that chance element comes in. Was it really chance or was it just that it was what was around? But I think there are a lot of steps where you could kind of ask that question. So, I think if we rewind the tape life on earth would be slightly different, at least likely because even in the research that was done here with the genetic code, there are some other sets that are slightly, that are similar and that are equally good.
But I think if we had, if we discovered life on Titan, then there would be no reason for it to be the same in a way, because it has a completely different environment. Like we're talking about like liquid methane and liquid ethane lakes with, with a crust, that's not like soil, it's ice and like everything is completely alien. And so, we'd probably find a super different and interesting form of life there.
Yeah. That disappointment though. I think it speaks to something that underlies this, you mentioned very early on in the call, the poly semantic nature of complexity. It's like everyone has a slightly different idea, but one thread that seems to run through a lot of them is, and I I'm constantly bringing up physicist Mark Buchanan's 2018 Nature Physics editorial on the bias for simplicity. I know a lot of people have written about this. This is something where our models of the world are parsimonious.
You know, that Ockham's Razor is almost like a metaphysics underlying this work precisely because the world itself seems to be lazy in a sense, or, to even take it down a layer, even though it's hypothetically it's possible for all of the particles, quantum tunnel out of a glass of water, it's just, you're never going to see it happen. And so, we have that contingency, but because everything seems to be running downhill, we end up with a world, you said, that, we ironically, after all of this work, maybe we are more likely to find something like the world, the life we know out there.
I don't know. Let's wrap this up. I really appreciate you taking all the time to talk. I know it's later in the evening over there, but I'm curious before you go to just know where this is pointing you know and like what's next on your horizon of research.
Yeah. So, what I might say might be slightly contradictory to what I just said, but this bite, this disappointment that realizing that there might be a good reason why life on earth evolved the way it did. I still think that it's really important for the community to look past the one example that we have on earth and abstract our search. And so, part of the work I'm doing, as I said early on is kind of still this idea of how do we look for it. But I think what drives me even more is the bigger questions of what are these general properties of life.
If you don't even think about life as a specific molecule, if you just think of it built of certain, what are the properties of these blocks in their interactions? Do we have to have complex chemistry? That's still an open question to me and I understand Lee Cronin's approach to. If you find something really complex on another planet, it probably came from life and that's kind of intuitive in a way that you would need these specific, enzymatic reactions to make something really complex. But if you don't find anything complex, that might not mean there's not life, perhaps.
And I think that's a question that needs addressing, and that's something that I'm interested in is whether you could have a living system that's composed of like really simple molecules or rather the question I guess, is it doesn't really matter what it's composed of and is it's more of a process than a specific amalgamation of certain compounds. And I think that's how a lot of people think about it these days too, that life is a process and not just a specific system. And that's the question that kind of drives me. And I think it's also innately linked to its emergence in the first place.
And so, that process of going from just a random chemical system, or without necessarily thinking of what the compounds are again, but just like a random bag of things, how do you get from that to something like us? That's always what fascinated me. I don't even remember writing about it in the letter that I had to like a motivational letter to go to university. And it was like, how do you get from just a bunch of star stuff to a system that's able to ask these questions about itself. And I'm sure other people are interested in that question more from like the emergence of thought and in us and like neuroscience and things like that.
And that's super interesting too, consciousness, but what interests me is like that what makes life different from non-life fundamentally? What are those properties? Like, what are we? You just get into these like interesting discussions with people all the time during work calls, you'll just hear us being like, what is life?
I mean, I just remember when, when David Krakauer was a guest on The Astral Hustle Podcast. He actually confessed to being kind of a panpsychist to the extent that information processing seemed like it had some sort of interiority to it. And he was willing to extend it to at least down to the bacterial level. So, maybe it is the same question. I don't know, maybe. I mean, certainly that's what Tononi and Koch in their integrated information theory are proposing as crazy and unresolved as that is.
Anyway, good luck with everything. I hope you find it. Yeah, that would be cool. Thanks a lot for being on the show.
Yeah. Thanks for having me.