What Can You Do With Just 493 Genes?

Quinn: [00:00:00] How did we get here? That's today's big question, not the biggest question of all. And today my guests are Roy Moger-Reischer, and becoming our first three-time guest, Brandon Ogbunu. Roy Moger-Reischer is a scientist trained in microbiology, evolution and data analysis for his PhD. Sure. He completed a laboratory evolution of designer microorganisms, using a combination of wet lab and computational techniques to harness the billion year old power of natural selection to hone the performance of microorganisms for specific tasks.

He's currently a fermentation specialist Arzeda, working to develop new proteins and biochemistry for the production of valuable molecules. Brandon Ogbunu, again, our first three-time guest described by some as a radical collaborator, is an assistant professor in the Department of Ecology and Evolutionary Biology at Yale.

His [00:01:00] research takes place at the intersection of evolutionary biology, genetics, and epidemiology. Brandon uses experimental evolution, mathematical modeling, and computational biology to better understand the underlying causes and consequences of disease. His writing has appeared in academic journals and most recently in Wired, the Atlantic, and ESPN, focusing on topics related to the intersection of science with justice and culture.

Now, look, you guys know I'm a moron, but sometimes I run across a piece of research I can't stop thinking about, even if I barely understand it, sometimes it's something that's immediately applicable to the world at large, or my work here, and sometimes it's not. At least not at first until someone explains it to me.

When I first read about the work of Roy and his lab compatriots to take this idea, a cell so stripped down to only what is most essential, a minimal [00:02:00] cell, and then to see if it would or even could evolve to survive even basic mutations with both hands wrapped behind its cellular back, I guess. My first thought was what?

And second, what is, I imagine everyone else is going to respond is dinosaurs? But this will surprise you. It's not that, or is it? It's a lot of things it turns out, as you'll hear, but mostly it's profound as hell. And because I'm a self-aware moron, I also begged two-time guest, now three-time guest, Brandon Ogbunu, to come back on the show to help me understand what the hell is happening here and what it means for our history, for society today and for future breakthroughs to help answer the question:

What can you do with just 493 genes? And if the answer is not only survive, but thrive, what can we do once we know that about the building [00:03:00] blocks of life? Welcome to Important, Not Important. My name is Quinn Emmett, and this is science for people who give a shit. In these weekly conversations, I take a deep dive with an incredible human who's working on the front lines of the future to build a radically better today and tomorrow for everyone.

And along the way, we're going to discover tips, strategies, and stories you can use to understand the future and help us unfuck it.

Gentlemen, welcome to the show, Roy. Thanks for coming.

Roy Moger-Reischer: Thank you. It's a pleasure.

Quinn: Awesome, man. And Brandon he's back. I think you got to be our first three time guest. This is incredible news.

I'm very excited.

Brandon Ogbunu: Oh, no, I'm thrilled. Thrilled. Thanks to, thanks for inviting me to participate in this.

Quinn: I just got to give you a year or so in between each one. Time to recover, man. Time to recover. Before we get into this pretty profound work that's been going on, Roy, I do like to start off with one question, and I think I've asked Brandon this.

We've asked 160 something guests this, why are you vital to the [00:04:00] survival of the species? And I encourage you to be bold and honest. Go get them.

Roy Moger-Reischer: I cannot be both bold and honest. I feel like that would be a contradiction. But if I was critical to the survival of the species, I don't think it's because of any technical skills that I have or knowledge that I have.

I think it's because when I approach my work, I will never stop dreaming about a better, more beautiful, conscious, radical future for humanity. And I'll never stop dreaming about some sort of radical, open-minded, healthy, conscious, extraordinary life for myself where I can participate in that sort of future and help explore it.

And help create it. And I'm fortunate because, like I said, I don't know anything. I'm not even a synthetic biologist and I tried to do something with evolution, right? I'm a lowly evolutionary biologist, but I think I am fortunate to be good at solving problems and my drive is to solve problems that connects with making the everyday [00:05:00] lived experience of this kind of human of the future into a better one.

So I think that if there is an affirmative answer to that question, that’s why.

Quinn: Look at that. Everybody always laughs at me and I get these incredibly profound answers. It's fantastic. Brandon, you got anything new to offer? Any reasons why you feel like you're, additional reasons why you feel like you're changing the game for humanity here.

Brandon Ogbunu: You want me to follow what he just said? Come on. No, come on. That was beautiful.

Quinn: Hold on. You've been doing a lot more writing since the last time we talked. How's that coming into your life?

Brandon Ogbunu: I mean, it's been good and it's a real kind of technical and scholarly part of my identity now in a way that's grown.

But I think, what was said was beautiful just now. And I think the only thing I would add or modify from what I said before is, I'm talking to you now really on the, if you will, the other side of the pandemic era. And so there's just been a lot of lessons about that, that we've learned.

And I think what I've tried to be transparent about is how bad we were as [00:06:00] scientists with regards to the way that we communicated to the public. And I know that's a little bit of a controversial stance because obviously we weren't the problem. But I think we could have done a lot better.

So I've tried to embrace that problem and a lot of the criticism I have for myself and my colleagues, and animate that into a real part of my scientific skillset.

Quinn: I love that. Was it a conscious choice to go towards more popular, broader outlets like Wired as opposed to mostly just research and journals and I guess more for the scientific community?

Brandon Ogbunu: For me, those distinctions are artificial. I think those are things that somebody came up with hundreds of years ago that told scientists you're supposed to do one thing and not another. Like, that's not, the original university, in the original conception, in the Aristotelian tradition, they were like me, right?

They just did stuff. You just thought of something and you did it. You know what I'm saying? And so what I'm trying to do in many ways is bring us back to the older, romantic conception of what a scholar is. So to me, [00:07:00] I'm doing it the right way. You know what I'm saying, I don't really think about these distinctions.

I think these barriers, and I think this work that we're going to talk about is a good example of that. What he just said was, I'm not even a synthetic biologist, but I had some questions and I can solve problems. So he got the data and the system in place and went after them. And that's what I'm talking about.

Like, that's the type of scholarship that I find the most important.

Roy Moger-Reischer: Yeah. That sounds aligned.

Quinn: I love it. I love it. Thank you both for setting the table here for, I guess less about, the grander why of why we're here. Which is, I come back, I had this wonderful scientist on the show recently who works with a lot of AI data and she said she uses new tools to ask to answer old questions, which I think is great. Alright, so Roy. Let's do this. Give us your, I don't want to say briefest, but give us a sort of concise not necessarily for a kindergartner, but let's say like, imagine I'm still in middle school, high school and this sort of thing is interesting to me, but I don't totally understand [00:08:00] it.

What this research was maybe the hypothesis and how you tested it and why you did it.

Roy Moger-Reischer: Why did we do it? We did it because I think minimal models are important, and one analogy that I didn't come up with, but I think is a good one, is thinking about if you were a physicist in the 1940s and you needed to like split a uranium atom because you needed to win a war, how are you going to do that?

Uranium is like this giant atom with like 238 protons or whatever it is and it's really big and complicated. And so if you were an atomic physicist, you would probably start by understanding hydrogen, which is the simplest atom that there is. It has one proton, there's one electron that's going around that proton in some sort of quantum mechanical orbital.

But you can understand how this proton and this electron are interacting with each other and grasp the basics of what this atom is doing. And then you would probably move on to helium, where now there's two protons. So there's like some strong force interactions in the nucleus and there's two electrons, so they're interacting with each other.

But because you [00:09:00] understood hydrogen, you can tease apart what's new? What are the new interactions that have been added here? What's the new complexity? What effects are additive? What are non additive? And so you can understand those new interactions separately from what you originally understood.

And then you move on to lithium, which now has a third electron. It's in a whole other orbital, so there's like electron shielding. But again, you can understand what is new that has been added because you understood helium, because you understood hydrogen. So that's great that atomic physicists could do that.

But in biology, biology is pretty darn complicated. And we don't really have a hydrogen, like even the model organisms like E. coli or budding yeast that we use to try to understand eukaryotic cell biology. These are very complicated cells with thousands of genes, thousands of proteins floating around in these cells interacting with each other.

And so it can be really hard to have that sort of first principles ground up approach that will let you understand increasing levels of complexity. And especially if you're like me and an evolutionary biologist, your kind of minimal models are like these pen and [00:10:00] paper things, like Hardy Weinberg equilibrium that you might remember from school, where it's like, okay, this population is infinite in size.

There's no natural selection, there's no migration. And from that you can understand, okay, that's how evolution would happen in the super null model. And you can start to add in those processes one at a time. So you might add in natural selection, you can understand that and then understand how that might interact with migration.

But as soon as you introduce a real organism, that kind of all goes out the window and everything is just way too complicated. So that is the motivation for studying a minimal cell, that is a cell that is not E. coli, it's a cell that has as few genes as possible while still being a bacterial cell that we can use to understand cell biology at the most fundamental level we can as well as, in my case, understand evolution, hopefully in a simplest case system that will teach us something fundamental about the way evolution works.

So that was the motivation for doing this sort of evolution of a minimal cell. Now, where it came from is that back in 2016, other scientists who are not me took a pathogenic organism called Mycoplasma mycoides [00:11:00]. It infects goats. It's a pretty darn simple cell. It doesn't have a cell wall.

It's like really weak. It can barely grow in a laboratory. And because it's a pathogen, a lot of pathogens have really fairly streamlined genomes, meaning they don't make a lot of different proteins. They don't have a lot of different genes because they are used to living in a really comfortable environment.

They're used to living inside a host that provides a lot of what they need. So that was a good starting point. And what the synthetic biologists at the Craig Venture Institute did was they deleted every gene that they could from this organism while still getting something that they could grow in the laboratory.

So they took an organism that had about a thousand genes, 900 genes, and they reduced it down to having 500 and, reduced its genome size by a corresponding amount. And basically they tried to see every combination of genes they could delete while still getting the cell to grow and be a little bit hardy and fit.

It had to basically be able to reproduce and survive a few passages in bacteria food. From this they used that information to synthesize a chromosome, which was the novelty of the research [00:12:00] that they synthesized this entire chromosome and inserted it into effectively like an empty cell membrane.

And that chromosome turned on the cell membrane. And we had some sort of approximation of artificial life, which is going to have been completely different from what life was actually like four point, however many billion years ago, or three point, however many billion years ago, when life started, so we're not necessarily approximating the origin of life.

That bacterium or whatever it was, would've been pretty different, but it's an example of, you could argue that life was synthesized. Now, me, as an evolutionary biologist, I was like, okay, that's really cool, but how does it evolve? And so that's where I came in. That was a lot. I feel like I talked for a long time.

Quinn: No, that sets the foundation. That's the thing. That is one of the parts I could never explain. But also it really, it increasingly matters to me and has for a while now the why of why people do this work and why you have to do this work. Brandon, is this sort of research stuff you're tangling [00:13:00] with at all in any way?

Are you, how much you do talking about this with students?

Brandon Ogbunu: A hundred percent. I mean, this is, and I really love that articulation of the motivation, this idea of when you want to study anything, what is the fundamental kind of system that you use to build an understanding around?

I mean, that's, I don't, it doesn't get more important than that, and that's, with anything, that's not just with science, that's with sport, that's with engineering, that's with art. That's with anything is like you have to start with a unit. And I think what I love about the work and what was just articulated is we've had various conceptions of what the basic kind of atom is of biology.

And of all systems. So you talk about the atom being the canonical thing that we use in physics and in, to some degree in chemistry it's more the molecule. But in biology it's been a war of what is the basic thing that we should be studying, right?

And I think the gene won out, right? Like over the time until recently and perhaps still right? It was the individual bundled piece of [00:14:00] genetic information. That's the story. And if we understand individual things, we understand the story. And I think what has happened in the last 20 years is that we've learned that's not quite so true.

It's that, individual stories of individual genes are important. But they don't tell the fundamental story of life. There's a lot of confusing things about the way genes interact and work together and sit in a genome together. And what this work has done beautifully is it's stripped the problem down right to a, the most fundamental system that both values the importance of individuality, but demonstrates that they need to work together in the simplest possible genome.

So this is something I've been wrestling with in my work for a long time, and I think this is a large leap forward for that reason.

Quinn: I love that. So you got Twitter boys talking about break everything down to first principles and this and this. This is literally that. Did you believe how much you stripped this down to the minimal cell?

[00:15:00] Did you believe it would survive mutations? Because you, from what I understand, you even deleted the genes responsible traditionally for repairing mutations. Am I getting any of this right?

Roy Moger-Reischer: You are getting right everything except the fact that I did any of that.

Quinn: Great. But the point is like in trying to, because before you can let it grow however many generations, right?

You have to take it down and to take it down, I guess this minimal cell idea when you got there. So let me preface it this way. So I actually have a little experience and I'm not going to share too much, but I have a little experience with this in that my first two children were made with IVF and it took a lot of tries and a lot of failures and five different incredible doctor scientists, nerdy, the most curious, caring people in the world.

And I learned a lot about the bare minimum of when a sperm and egg combined in those first three days and how these things are [00:16:00] rated, basically, will they survive, in those first few days to get to the point where you can do implantation, but also, they give you these scales and again, important context is, this was 10 years ago and a lot has changed obviously.

What are the early indicators of what is missing for viability or what might be extra or repeated there or things like this as it starts to change. And then they go, okay, if you're going to put it in, you got to put it in. We had a lot of failures. And then finally we got one where they put it in and they were like, look on the sort of grading scale they give it, they were like, it's not great, it's probably not going to work, but you got nothing left, so good luck.

And now he's 10 and going to camp next week. So that is my experience. But when we talk about like minimal cell and not able to survive mutations I'm curious how much that played into. We want to see if it'll evolve, is it dialed down too far? Yeah, I don’t know.

I, this is, I'm just, this is the part where it gets a little more organic and I'm just trying to come at it from semi experience.

Roy Moger-Reischer: I [00:17:00] have two answers to that question of like whether I expected it to work at all. We did two experiments. One was to look at mutation specifically where we avoided any sort of natural selection.

And one where we wanted to understand how the cell might adapt and actually get stronger through natural selection. And I, what I expected with respect to adaptation, natural selection, I expected it to work because it made sense that natural selection should function in any population of imperfectly self-replicating entities.

I thought, I'm an evolutionary biologist so I figured, maybe I'm biased, but I did think it would work and that said, I thought that evolution would be constrained, at least to some extent, by the minimal nature of this genome, where every gene that it has is essential for its survival.

So I think, I reasoned that would increase effectively the proportion of mutations that would kill the cell. In any chromosome, every [00:18:00] single DNA base pair is always under negative selection or purifying selection, because most mutations are bad. It's only occasionally that there's a mutation that's good, and it might not be immediately purged and might eventually be involved in adaptation, natural selection of whatever organism that is.

And so, I reasoned that however, the proportion of changes that would be selected against would be really high in a minimal cell. So I thought that it might have, it might adapt more slowly than a non minimal cell by comparison. So that's one answer to the question. Now the other thing that we did was we tried to measure the mutation rates.

And as you pointed out, this minimal cell was missing some of its DNA repair genes. And so it was possible that its mutation rate would just be out of control. And when we removed natural selection from the equation well, so that all the mutations that occurred were effectively not really being exposed to natural selection, but just increasing and decreasing frequency at random, that sort of thing can lead [00:19:00] to populations, getting weaker and weaker, crappier and potentially going extinct.

And just for reference, the way that we remove natural selection from the equation is by serially bottlenecking these populations. So by, listeners may have, may remember from school like. Bottlenecks where a population shrinks down and a lot of random effects can happen there because you're just sampling, like say one or two individuals at random from this population.

They just happen to survive. Not because they're particularly vigorous or fit, but just because they got lucky. So that's what we tried to introduce to eliminate the force of natural selection and study mutation per se. So that actually as it turned out, did not work at all because we couldn't even get the cells to grow on the Petri plates that we needed them to.

So in order to do that, we actually had to pre-adapt the bacteria. So we did some of this natural selection stuff and then use those slightly adapted cells for this bad evolution experiment where they're getting worse and worse through mutation. So, that's a kind of, I don't know if [00:20:00] that's a particularly profound or interesting answer to your question, but I think that's the honest answer is that yes and no.

Quinn: No, I think it makes sense, and again, to frame this for someone like myself and for everyone else, and please again, gentlemen, correct me if I'm wrong, the goal wasn't like, we're going to try to strip this down like one of these amoebas that came out of a deep sea vent however many billions of years ago and see if it works.

Like you said, this is by all intents and purposes and assumptions, not this minimal cell wasn't what came out. There's no real way to do that as far as I understand. It was, can we strip it of all of its, anything that's not essential, tie its hands behind its back and take away anything that'll repair it and protect it and see if it'll evolve, see if it'll make it, see if it'll mutate and possibly, all those things.

Roy Moger-Reischer: See if it'll do the Jurassic Park thing.

Quinn: See if it'll, I mean, Christ, we keep coming back to it, right? God, every time. Every time. Let me ask you this question, and Brandon, maybe you can help here. Why has no one [00:21:00] asked and been able to answer this question before, which I think are two different things, and or have they this entire time and I haven't taken chemistry in 30 years?

Roy Moger-Reischer: One, one answer to that question is, so when this all came about the evolution of the minimal cell came about because my advisor saw a talk by the author of that original 2016 paper where they generated the minimal cell. And he also thought, when he heard about it, he also thought, Hey, has anyone thought about evolving these things?

And kind of the response from the synthetic biologist was like, why would you do that? And the reason for that is because, hey, as a crowning achievement of synthetic biology, what they're thinking about is much more straightforward. Now we have these amazing tools that can con construct an entire chromosome from scratch and, generate this sort of synthetic life.

And now they might be thinking about bio technological applications and like, I describe myself as a lowly evolutionary biologist because that's true. [00:22:00] I think that there's a lot of important things that we can gain in the world of synthetic biology through evolutionary thinking. But it's not necessarily the prevailing milia.

So I think that's why it's not sure been done for a while. Does that make sense? I mean, we started this project back in 2017, so, we started pretty soon after if it came out.

Quinn: Brandon, does that ring true for you?

Brandon Ogbunu: Yeah, it does. I mean, you talking to the person who did the work, so, but I think just from an outsider yeah I think that makes a lot of sense.

I think we've had the tools to reduce genomes for quite some time, and I think we've asked versions of this question in the virus world for quite some time, right? Because viruses are the most reduced in bare bones biological entities in the known universe. But I think, yeah, I think this next step of, can this evolve and how does it evolve?

I mean, how does these, how do these minimal cells evolve, I think is a really critical one. And I'm glad that the work is done.

Quinn: I mean, to make it at [00:23:00] all transferable to what we do here. And I think this is why. Besides reading about it. And I was like, that's so fucking cool. We try here to operate in the sense of like, Hey, this is what's going on.

Here's how you can understand it, and here's what the hell you can do about it to help yourself feel a little bit better, but also to move the needle in some way. And often that's, as we say, like you can't make the jet stream speed back up or whatever it might be, but you can affect, for example, climate change because it's the heat you feel on your back.

It's the water you drink in your community, all these different things, right? This is obviously a little less so unless this is a field dream, but it does beg these questions that I think are important about how did we get here, if not exactly. And what does that mean? And why is it important to keep asking that question mechanically so that we can understand the systems in place for building something better?

And when I talk about building something better in this sense, again, I come at it from the practical applications wise of where do we have systemic [00:24:00] deficits, whether on purpose or not, right? So we, you look at all the hubbub about CRISPR and folks say, oh, this is great. We could remove autism. And you got a bunch of people who have autism going, we don't necessarily want that, right?

So it's obviously becomes this much more societal complicated question, even though we're really talking about, Hey, look at these cool scissors we've made to cut apart genes and switch things in and out. But it does matter how we got here because without that, I've been doing some reading recently on I believe they're called cell atlases.

Basically how we can build let's see, what did my notes say about this? They’re described as detailed maps of the cells and human organs to show how the placenta might work with maternal blood supply. Which is something that the, we've had three kids, pregnancy and giving birth is still really complicated and it's still obviously on the society-wise, really complicated for some birth givers because we just don't give them enough care.

So, but there's also things like we have these [00:25:00] huge shortages of organ donation availability in across the world, but especially in the US for a variety of reasons. So, can we, make kidney cells healthier, all these different things. We can't do that until we understand, like, again, take it back to the bare minimum and go, what can this thing survive?

Sort of what is essential and what is not. I guess that just makes me come to the question of, and again, now branching forward a little bit, what, not what's next necessarily, but it's that rule of like, okay, if this, then what else? What can be built upon the scaffolding of the work that you all have done and that Brandon's been studying forever, obviously that is ongoing and vital, but what are the practical implications going forward?

What excites you?

Roy Moger-Reischer: Yeah, so, one thing you brought up is like organ transplantation and that's something that synthetic biologists are working on, synthetic biologists are working on, a lot of important biotechnology that, so, so maybe the way that I can get [00:26:00] at the practical applications here is, so what does this mean for synthetic biology and biotechnology more generally?

Which is, it's still one step removed. My answer to that would be first of all, when you are doing synthetic biology, for example, you probably you want your designer organism or cell to do exactly what you asked it to do and not really anything else typically. So some sort of streamlining approach or streamlining thinking would not be uncommon.

And so I think there are implications for even if you are streamlining your organism to do something very specific, this work shows that you can't stop evolution. And so you do need to keep that in mind if you're, say, going to, release your organism into the wild or propagate it in any way.

Now, and again, maybe that's obvious. Me as an evolutionary biologist, I'm not, like I said, I'm not surprised that you can't stop the evolution. But I think another important thing is, for one thing, given that the products of synthetic biology are not stable [00:27:00] endpoints that will never change. There are opportunities in that.

So for example, the minimal cell, it was really sick. It unlike every other organism that's ever existed, it had not been honed by a billion years of natural selection. And compared to the non minimal synthetic cell that it was derived from, it was terrible at growing. It took like twice as long to divide and yet through this process of adaptation and evolution, we were able to recover all of that fitness that was lost due to, human fucking around and that's not just limited to minimal cells. There's a great example of research in George Church's lab where they took an E. coli and they recoded its entire genome. They had to like change out, stop codons. So they're changing, they're having to mutate specific pieces of DNA across the entire genome to get it to make proteins that incorporate non-standard amino acids.

So you, so listeners probably remember that like, the genetic code, there's a bunch of different DNA letter codes that encode certain amino acids and there's 20 of these [00:28:00] amino acids that get incorporated into biological proteins typically. But what they did was they recoded its genome to also be able to incorporate non-standard amino acids that had fun names like zitofinalanine or two natural alanine. But there are problems with this cell too, because when you do that sort of genome-wide recoding, it comes with often, and maybe, tools are getting better, but it comes with off-target mutations.

So there's mutations that they didn't intend showing up all over the genome. That might be hard to find, as well as just the fact that, you've messed around with its tRNAs, which are fundamental to like basic cellular metabolism. And not surprisingly, perhaps these cells were really crappy, similar to the way that the minimal cell was.

And they did something very similar to what I did, which is that they leveraged natural selection to repair the lost fitness in these recoded E. coli, which, what's so amazing about natural selection is that they didn't have to know what was wrong with it. They could just let nature figure out what was wrong with it and [00:29:00] fix it itself.

So that's an amazing approach that let them get better synthetic organisms that can do something that no E. coli cell normally could. And then bringing that back to my research, I think what we showed is that even in kind of this worst case scenario where the cell had the least genetic material to work with, and it should have been the most constrained because we know that essential genes evolve more slowly, it still worked.

And so I think there are like that, that fundamental finding, which maybe isn't even surprising, but it was important to demonstrate. I think that fundamental finding does have important implications for how we can use biotechnology to improve society.

Quinn: Brandon, you're nodding. What, what sticks with you with that?

Brandon Ogbunu: Oh, so much. I mean, I think it, I think you know, it was summarized really nicely there. And I think the way I interpret work like this, the way, my take on it when I read it is, there is this feedback between evolutionary questions and bioengineering questions. Those two fields are always, so anytime you make a big discovery, you're asking two big questions. It's, [00:30:00] does this reflect something meaningful about how life arrived on earth? As we know it? And/or am I reflecting something about human ingenuity that can write, manipulate, and we can we now manipulate nature in these tools?

And those are sometimes different things. So some of the stuff we're doing in bioengineering ain't got nothing to do with how we got here. Now we're using the tools that natural selection delivered, which is cells and DNA and RNA and what have you. But some of this stuff is not about how life happened originally.

It's about what we can do to build tools to help us with disease or help us with environmental, and what have you. And I think this is one of those discoveries that speaks to both of those things very clearly. I think it absolutely does ask questions about how, what is the basic and fundamental unit of organization for how life could evolve.

This is absolutely potentially a origins of life study. But it is [00:31:00] also, as you just heard about, okay, if we want to build life from scratch, if we want to build microorganisms to help us with kind of environmental remediation, if you want to build organs, right? Artificial cells for organs, if we want to build these things, right?

This is, these are the types of synthetic tools we can use. And I think that's really exciting. And I think, Quinn, you have a pretty good handle on this, but you really do have to be smart and careful about the way you walk from a basic evolutionary question to a bioengineering one.

And I think one of the things we can get in trouble when we sprint there. And that's the thing about CRISPR. CRISPR was a, that is a evolved thing that microbes have come up with as an immune system. That's what, that's the discovery, right? And the problems, or, I mean, it's not, I'm, so, I'm a, if you will, I'm in the, relatively speaking in the, I think genetic modification can help a lot of people.

I am really much in that, now with some gigantic [00:32:00] caveats. But what I'm saying is, I think the problem is the sprint to CRIPR in human embryos and what have you. And so discoveries like this one speak to both of these things.

And I think the question is how can you carefully and responsibly walk this discovery about a minimal cell now into conversations about and in what paradigms do we think it could be of most immediate use, but that might be 30 years away. And that's cool. And we got to be okay with that.

Roy Moger-Reischer: Wanted to agree with you. Like, but it's so important to still be bullish on these technologies, right? You have, just because there's 30 years of work ahead of us, there's no reason to write it off.

Brandon Ogbunu: A hundred percent. It might be 30 years of hard work to get you there. Meaning we got to hustle and grind for 30 years.

So to your point, absolutely. We need to lean in.

Quinn: I mean it, so I'm finding more and more transferable. I don't know if the words is processes or what as it reflects with what we are dealing with today. [00:33:00] So for instance, the most big it, it's this, we have to walk before we run, but we really need to understand how we got here so that we can build something because often this whole, like we need to build a better future. Sometimes that's retrofitting what we've got. Sometimes we can do, if we can deal with the incentives that have been perversely aligned the other way, sometimes it's starting from scratch, right? And even if it's the same model, like energy generation, what does that mean when we say, okay, but now we're going to get it from the sun.

We're going to get it from wind. There's all these obviously different implications, but it goes in a lot of different ways. So we look at like you said with CRISPR, all of a sudden was, this is an entirely different conversation, but it's like the Kanye line. Like no one man should have all this power.

All of a sudden, like social media, we look around and go like, are we really are we like cool to use this? Are we in a place philosophically, ethically, scientifically, all these different things to just start using something like CRISPR? And it's the same thing with artificial intelligence right now, right?

As how it's progressing. You've got a bunch of people who [00:34:00] are saying, we're going to sign this letter that we should slow down. Meanwhile, China's like, no thank you. We're going to do it no matter what. And so will a million different individuals. You've got President Biden getting just this week, a bunch of the leaders of the seven most noteworthy companies that can build these sort of LLMs and the tools on top saying, yes, we'll agree to voluntary safeguards.

Meanwhile asking again that question of like, should we, and if we should, how should we and what are the, assuming that, and obviously biology is the most literal definition of this, but the idea with artificial intelligence has always been the alignment problem, right? Which is quite literally what we put in is what we get out.

You want to know why these algorithms are racist or whatever it may be. It's because we're not asking the questions of, okay, but who's writing them and who's choosing the data and what's the data based on and who, why did they get to choose all those different things? And all of a sudden you've got the result of what we got, which is a more efficient way of how we traditionally do things as [00:35:00] it is.

And to me that is, like you said, we might have 30 years of really hard work in front of us to really put these things to use at scale. Whether it's genetically modifying mosquitoes, no one's saying we shouldn't try to get rid of malaria. It's a fucking nightmare. It's just, because it's not here doesn't mean it's, I guess it's in Florida now, which, not surprising, but no one's saying we shouldn't do that.

But you've got some really great ethical biologists who are just saying like, okay, but we have a lot of questions we've got to ask along the way of like, what does this do? What does this mean to, and three and four and five steps down the line, not just for mosquito populations, whether it's in all these tropical places or in the parts of Africa where these kids are just still getting it all the time, but also who is going to take what we've done here and use it for something else?

And we always talk about dinosaurs, but there's a million other variations of that. So again, this is why I really appreciate this conversation because it's less about me going back and not, probably getting like a D-ish in biology, but more just like going, [00:36:00] okay, how do I use these lessons to help our audience understand.

Yes. We need to keep pushing forward. Yes, we need to do it to make a world that's healthier, cleaner, more equitable for everyone, which I guess is redundant, but also asking those questions along the way of like, how might we have gotten here and what were the mutations or incentives, biologically or societally along the way.

And do we need to choose differently? And who gets to choose? Anyways, that's my manifesto.

Roy Moger-Reischer: Thank you. I can't add to that.

Quinn: So, I look at this and I think of things like cancer, right? So I've been working on this my other life, Roy is, I was a screenwriter before this and still do a fair amount of it.

And I've been working on this idea which kind of got thrown for loop with all the AI stuff. It's really hard to write a sci-fi TV show right now because everything changes. Every day. And so you look like a real ass-hat, if you like, choose a lane for 30 years from now, it's a bit of a pain.

So this is why people do the things where they just like take cell phones out of movies or just say like, like Dune. They're just like, we tried robots. You're not allowed to do it. You're like, great, now you don't have to deal. [00:37:00] But one of the sort of plot lines I've been wrestling with is this idea of cancer as part of who we are.

Really, there's all these external influences, obviously the environmental ones and all these things that we've brought on ourselves, but it's this idea of we can't cure cancer. It's 10,000 different things, right? But the choices we make about using tools like this or that are analogous to it to understand the genetic changes that happen early in cells before they mutate so that we can have tests like Grails and then going.

Okay, but what does that mean for treatment? What does that mean for immunology and all these different things? And I wonder again, how much, when you wrestle with, look, life didn't start this way, but this is a version of how we got here through the great filter, as they call that. How much will we keep wrestling with things like this as we face big problems that are endemic to who we are, like cancer, besides the fancy things like CRISPR that we pick and choose.

Does any of that make [00:38:00] any sense at all?

Roy Moger-Reischer: So the reason cancer's so hard to get rid of is that unlike most diseases, it's promoted by natural selection. And this goes back to what Brandon was saying is that what level should we be focusing on? Are we focusing on a gene? Are we focusing on a cell? Are we focusing on an organism?

And in the case of cancer we've got a conflict of interest between an organism and a cell that acquires some types of mutations that let it divide really fast and spread and grow. But that aren't so great for all of the other cells around it. And normally that's not a problem. Cells are able to work together in an organism because they're all closely related to each other.

And so helping one cell helping another cell, right? It's still propagating its own genes, but, a cancer cell has mutations. It's doing its own thing. And that becomes a problem for the organism at large. So I think that's actually a great example of a type of question that can be relevant to this sort of research where we just learn more about the fundamentals of how natural selection works in [00:39:00] simple cellular systems.

Because that understanding the, like how evolution might work at different levels of complexity or simplicity would be directly applicable to cancer because it's exactly that sort of conflict of evolution, natural selection at different levels of complexity. I don't know if that answers your question, but that's what comes to mind to me as an evolutionary biologist when we think about applying natural selection to practical things in the context of cancer.

Brandon Ogbunu: So your question about cancer is a very provocative one, and I think there's a lot of big debates that exist. Seven years ago or so, I think there was this I think it was maybe, this debate about whether or not cancer's just a product of bad luck and there's nothing we can do with it, right?

Like about it, right? And that emerged into a debate and in the sense of bad luck in the sense of is this just a property of the way cells replicate? And I think there's a technical and statistical and nerdy question about whether that's true or not.

But part of the implications for the answer of that question that relates to what you just mentioned, [00:40:00] Quinn, is about our funding and the resources that we put into it. And one of the kind of meta questions there was if this is something that's just a part of who we are, why? Because there is enormous research resources into cancer right now. And I'm not here to say whether or not that's a good or bad idea. I'm just constructing the landscape, which is if it's, because I mean, we've all had people affected by it, right? So, I'm not here to say that's not, and there's a lot of brilliant people doing brilliant work in that paradigm, friends and colleagues of mine.

But part of the question is if that's a good use of funding, that's actually a relevant question and that's also a relevant question, even in the bio technological space, right? So just money and resources and time and training for young people in particular, it's not infinite. We have a finite amount of labs that we can train young people to think about the problems of today or tomorrow.

And if right certain diseases are just the sort of thing that either we care about more on the [00:41:00] west or we care about more because we're living longer, which is also true, or we care about for all these kind of boutique reasons, then perhaps we should be redistributing our intellectual resources as well as our financial resources towards a broader set of questions.

Now, how does this connect to what's going on in this conversation with the minimal cell and what have you? The way that plays out is all right, maybe we just need to be asking and answering fundamental questions about the way life works because darn it, the argument there is that one is the one that seems to develop, deliver the practical solutions, right?

It's actually when people are tinkering with nature in a fundamental way that you actually identify the best antibiotics and the tools that actually help us understand disease. So I, again, I don't, I try not to like, the polarization that has been amplified in the social media era.

I don't participate in it because no answer is [00:42:00] simple. It's always going to be complicated and we need to learn to live with that complication, so, I'm not throwing my weight behind any one of these things, but it is a real debate and it's one that I animate in my laboratory.

Like, so when students apply to my lab, I have a finite amount of time and resources that I can put in to them answering questions. I work on disease. And so my question is, do I want to steer them towards minimal cell style questions or do I want to steer them towards, how the hell can we get rid of cholera?

It's tough. And I think this is going to continuously be the dance, but what I will say is this minimal cell research and work like this, it emphasizes why I think ultimately that's the best thing humanity has is our ability to tinker and ability to explore. And I think we have to support basic research like this because ultimately this is where the best solutions shake out. I feel like.

Quinn: And also everything comes from that, right? We can argue about [00:43:00] the, let's see, you've got the tree of the, this minimal cell, whatever version, right? Imagine this was, let's just say this is how it started. And Roy's like, oh my God, I figured it out. Great. And then you've got 7,000 trees of different research and different diseases and all these different things from microplastics to air pollution to smoking to just like you said, is it bad luck?

All these different things. There is in this sort of infinite landscape of research and testing and treatments and all these different things we can do. The scope is finite, but we can't do any of it until we understand the basic stuff or we can't do this better until we understand the basic stuff.

We go back to, hey, part of the reason it turns out why all this Alzheimer’s research has been failing for the past 15 years is because so much of it has been based on doctored images. We, everything grows in this tree from here on out. But at the same time, like you said, your lab and specifically you have finite time each day, each week and over the course of your career and your life.

And I think again, moving to how society, which is on [00:44:00] a bit of a ticking clock with something like climate change. And potentially AI, but probably not in the way we think, but in the sense how do we as a society or as a policymaker apply ourselves? Where do we choose to use our political capital or societal capital, but also how does each of us in our time here use it?

Because you can't do it all. We can't do it all. And it's easy to say, no one caress about how we got here. It's how we go forward. It's like, we keep fucking things up that way and also like, this is why we're here and there's a lot of good about why we're here and there's some not so great.

There's a lot of inequities there. But at the same time, it's funny because, we're building this thing out that I'll share with you guys offline, and it turns out I'm this pagan atheist religious studies major from a liberal arts college who didn't do well in biology and all these different things, but I grew up reading Wired and Popular Mechanics and Star Trek and all this shit.

And I care about these things, but it turns out the thing that I am best at is not carbon removal or clean energy or hunger or food or [00:45:00] biology or anything. It turns out over the course of this work so far, it has been taking all these generalizations and the religious studies of why do people do what they do, which is basically why I did it.

And political science, all this jazz, nonprofits, best friend died of cancer. How do I help? I'm not a scientist, I'm not a researcher. I'm not a doctor. What people come to us for, and what I can do is help them answer the question. What can I do? And you can phrase that a bunch of different ways it turns out you can say, what can I do?

Which sort of implies that you don't have a lot to offer with this particular thing. When my friend was dying, I was like I don't know how this cancer works. I don't know how to help him. I can't do anything, but I can sweat, so I can raise money and give this to doctors and researchers and maybe it'll help.

It didn't, but maybe to help somebody else. But you can also say, things like what can I do? Which implies like, I want to help, but I don't know what to do. I have all these interests and I have these skills, but I don't know where to apply them. What we do here it turns out, is do all the work that we possibly can to find the most [00:46:00] reputable ways within the scope of my career in my life to help people of a huge variety of backgrounds and interests and skills apply that question in the most reputable way possible of what can I do?

So Roy, you come to me and you say, I'm an evolutionary biologist and that's what I'm really good at, and this might be this other thing I'm into, right? Or you've got Brandon who's like, I do all these incredible things. I also write for Wired, also my Twitter name's, big data cane, like this is it, and then I can point you towards 7,000 things you can do within that Venn diagram.

And that is this idea of how I've realized I can use my finite bandwidth as much as I can. So again, I know this is not a question, which is the worst thing about a q and a is when someone doesn't an actually ask a question, but it's me trying to find this way into the nerdiest research, whatever it might be, talk to these incredible pediatric cancer researchers and they're like, oh, we figured out how to do it by using [00:47:00] zebrafish.

And I'm like, I don't even know where you buy zebrafish. How, however, much less like you involve them in cancer research. And that's great because kids shouldn't get cancer. Fuck that. That's my answer and I will help you however I need to. But this is all saying, like, this has been really beneficial to me so far because it helps me understand we have to be able to walk and chew gum at the same time if we're going to make different choices going forward and more effective choices going forward about how we help the most people and help the most ecosystems so that this thing is a little more solid for more people going forward.

That's my interim assessment.

Roy Moger-Reischer: Since it wasn't a question. I'll say my response to that idea, what comes to my mind is the way that the minimal cell evolution, our research demonstrated to me the importance of understanding fundamental simple systems as something that I can do, because one thing that turned up as I was doing this research was that pretty much all of my predictions were wrong.

Even though this was supposed to be the simplest possible system, we [00:48:00] had no idea how it actually worked. So for example, remember how I said it should be more constrained because we know. From evolutionary biology, we look at organisms in the wild. We know that essential genes evolve more slowly.

So I expected the minimal cell to be slower at adaptation. Turns out it actually adapted faster than the non minimal cell. And you can hypothesize why that might be right. It's starting from, a worse place, had more adaptation to do. Its genome was all messed around, had never been exposed to natural selection before.

So there's all these kind of new perhaps protein interactions that are going on inside that cell that can now be optimized. The basic prediction was completely wrong and thinking about mutation, it turns out these bacteria have the highest mutation rate of any known bacteria.

In retrospect, I can see some features of the organism that could lead to the evolution of a high mutation rate. But given that could have led to population extinction, that was also surprising in some ways. We also observed that one kind of [00:49:00] fun finding, when we looked at the, we tried to understand the physiological and genetic mechanisms of adaptation in the minimal cell, and it turned out that the non minimal cells, so we did these, we did evolution in parallel, just to be clear.

We compared the non minimal cell to the minimal cell when we did this adaptation. And we found that the non minimal cells became giant during adaptation, which is something that has been observed before. In other experiments like this, say with E. coli where they've adapted it to laboratory conditions, the cells get bigger.

It seems to be adaptive in a laboratory environment, given the way that the evolution is happening. But the minimal cells actually did not change in size during evolution. And what was really interesting was that this was the case, despite the fact that they both minimal and non minimal cells were getting mutations in a specific cell division protein.

So perhaps you could see why changes in a cell division protein could lead to giant cells. But interestingly, despite being very similar types of mutations, it had a completely different effect in the minimal and the non minimal [00:50:00] cell. In both of them. It was adaptive, it made the cells more fit, but in one case, it increased the size of the cells.

In one case it didn't, which demonstrates how important the sort of genome. What genes do you have? That context affects what mutations in a certain gene might do to a cell, and that was something we could never have predicted. Now, is it known that type of gene interaction exists in organisms?

Of course. But coming back to my point of that we really had no idea how even this minimal system worked. I think it shows that this type of basic research was very instructive in a lot of surprising ways. So hopefully that has contributed to what we can do next.

Quinn: I appreciate that.

I appreciate that from the perspective of we have to keep building or rebuilding and challenging these assumptions of, again, how we got here and how things move and change. Especially something that, again, you go back to the ridiculous Jurassic Park analogy. It should have been pretty evident when they're watching the thing.

And my 10 year old just got to watch it for the [00:51:00] first time. He is losing his mind. They go in the little thing and the character's talking to him on the screen. They're like, man, then we threw some fucking frog DNA. You should have stopped and been like there's your first question mark.

Life found a way because you fucked around with it. But life also finds a way, but it's helpful to keep dialing it back because again the analogous example is like, we know that if statistics were going to get it done, we could probably be in a different place. We know that 8 million people a year die from indirect and direct air pollution exposure.

8 million people a year. Like, that's just outrageous. And not only have we not said like, holy shit, let's stop all that immediately. It's still incentivized and subsidized in most parts of the world, including here. But that doesn't mean we shouldn't keep doing it so that we can understand it more and build better systems on top of it.

It's the idea of like, it's better to know what you say no to as opposed to say yes to. When you're trying to like a sculptor taking something down to what it is, we know we just absolutely cannot do fossil fuels [00:52:00] anymore because these are all the manifold ways, whatever the opposite of co-benefits is that it affects us, right?

So understanding those things more and more is important. It's not like we've stopped research on air pollution because we know how bad it is, right? So to me that as much as it's, I get excited about going, like, what's next? What do we build on top of that? I get so excited about this because we still really don't know how a fucking brain works.

Like it's easy to be like, oh, I had some migraines at one point. I remember going to this neurologist at UCLA and she was like, nobody knows this better than me and I don't have a fucking clue what's going on with you. And you're like, I appreciate the, like how humble she is and can you know candid about this because that's also exciting. It can be terrifying, but it's also exciting. But it just implies we have so much more work we get to do.

Brandon Ogbunu: So much good stuff there. What I'll quickly add is I think, to integrate a couple of things that I just heard, there is a way for a what's next [00:53:00] that is like, I feel like appropriately ambitious, right?

Like in the sense of this study to me makes me think if we can make a minimal cell, right? And we've achieved that and we demonstrated that minimal cell can evolve. It makes me think about, all right, what are others? Is it one species of bacteria? How does this look like in other cells?

And this is obviously what's happening next. And I think you can ask, the people who've done the work. So I think this whole new paradigm of questions about what is the minimum and basic number of things you need to make blank work, I feel like is a smart way to do biology as a whole, right?

So I can now take that perspective and walk it into metabolism, right? I can now walk it into neuroscience, and I think this is why people study C. elegans, right? Because they, the small number of genes and even as a system in neurons, in drosophila. So I think this minimal approach is something that we can walk into a bunch of other systems and I think we will continue to learn important things [00:54:00] that can then be animated for practical use.

But to go back to something you said, Quinn, in terms of what your role is here, and I think what the use is truly, I believe people like me and people like other scientists, because of the way science is taught, we have a limited vocabulary to be able to see all of the uses of what we do. I think the, you talk about being bad, being a D student, and I don't know if that's true but the part of the problem with science education is that it prunes a lot of the creative people.

And I've been saying that for many years. And my defect was that they didn't prune that, that they didn't prune the sci-fi nerd out of the science. That's what they didn't do. And so what I'm saying is, what we actually need, I think the practical questions have already come from science fiction.

They've, we already have practical solutions for things that came out of Moby Dick, and that came out of all kind of things like that. There are already inventions that [00:55:00] came into that. And so what I'm saying is these spaces, because, no disrespect to my science colleagues, but that they're not the most interesting and creative people when it comes to the uses and this is why their ethics are bad, right? Because they don't know how to think about people and society very well. So what I'm saying is spaces like yours and stages like yours that bring this work together I think are going to be the critical thing we need to really make that important next step between the these intriguing basic science discoveries and what the next and some of the practical applications that will happen in the near future.

Quinn: I mean, I appreciate that and I don't want to keep you guys too long, but that is where it really comes down to. And again, is, and that wasn't again, I wanted to have this conversation and reached out to both of you just because it was so fascinating to me. But all along the way in researching it and thinking about and preparing it and having this conversation is again, I keep coming back to someone out there's listening to this, whether they are in marketing or they're a student or they run a family office, they're an investor.

What? Like whatever, it matters. [00:56:00] They're a musician and there's some part of them that's going, I'm really into that and I don't know how the hell to find my way in, but how do I like find it? Even if it's just like, what is the next thing I read? What is the next conversation I've listened to whatever it might be.

But there's other people who are going like, shit, maybe I want to be a scientist. I mean, we all know the person who, the people who went to college, they're like, I'm going to be a doctor. And six weeks later they're like, fuck that. I'm into Buddhism. This is fantastic. And their parents freak out and it's like, but that's great.

They were culled for some sort of reason, right? They were pruned for some sort of reason. And I mean, thank god science didn't prune you out, right? I mean, it's like we have to have that perspective. It matters so much. And that's why you're able to do this incredibly influential writing now. To reach out to more people because you're not just in the lab like so many folks. But we need more of that because we need, every time you see everyone's cheering from Mark Zuckerberg this week, holy shit, how did that fucking happen? Because the guy just copies Twitter. Everyone's like, he's great. Look at him. He can water ski now.

And you're just like, we don't have a democracy [00:57:00] anymore, but like, holy shit. And part of that is because, look, I don't know how to build these things. I'm not a front end developer or backend or engineer, but I know there should be a chief liberal arts major in every one of these boardrooms going like, hold on a fucking minute.

Like what are the implications of us doing this? And I don't think the implications of understanding how a minimal cell goes 2000 generations or doesn't, and it fails at any stage along the way is going to bring the whole place down, but it could make it better. And the more people, I think they're exposed to these things while seeing the broader, more surface level integrations as you are, or applications for just theories or ideas.

I think maybe that's what brings along more of these. Hey, wait a minute. Have we ever thought about even just asking a question like that in this space? So, that's where I come at all this stuff. I have last set of questions I ask everybody if either of you have anything else you want to add to this particular, I appreciate it.

Thank you so much, Roy. Anything else you want to close with before we get you out of here? [00:58:00] I could do this for hours, but you two have actual jobs, so I'm not going to do that.

Roy Moger-Reischer: I suppose I just shout out my company Arzeda. So we're a protein design company. We use synthetic biology to make proteins and enzymes that hopefully we can produce in a more efficient way than is being done at present.

We have partnerships with like home care goods, with food products. And I think what's exciting about working in synthetic biology as well as coming from my background and thinking about things the way I think about them is everything from an evolutionary perspective becomes an optimization problem.

And I think there's a lot we can learn from these sorts of, like I was saying about the genomically recoded E. coli, that kind of research I think can be applied in a synthetic biology context and really can help us make better shit. That's about all I got. I guess it is just that I'm trying to, I'm hopefully, I'm trying to emphasize that even though this was some silly evolutionary[00:59:00] biologist looking at a synthetic cell and being like, can we Jurassic Park it?

I think that we actually learned a lot from doing that. And I'm excited about how we can apply what we learned.

Quinn: I appreciate that. It does matter. It does matter the questions we ask, but who gets to ask them and why do they ask them? And where are those sort of ideas of asking fundamental questions, whether technically or theoretically.

It really does keep adding to this conversation of how do we build something better and also like just fucking cool. Like, fuck, there has to be room for that shit too, besides just like the basic fundamentals and doing better on those things. Yes. Everyone needs clean water, of course.

Like let's fix that shit while we also do the really cool stuff. So I really appreciate that. For both of you and Brandon, I don't know if you answered this last time, but time has passed. Who is someone in your life that has positively impacted your work in the past six months? Just a brief moment to kinda call them out because none of us are doing this alone. Either of you can go.

Roy Moger-Reischer: For me, it would probably always be an answer like this for the past six [01:00:00] months, I would say my cohi at work. So I started work here at Arzeda in January, same day as a more junior associate scientist. And it's always from someone who is potentially one, supposed to be one's mentee, I find that, I always learn more from them than I could ever hope to teach. And so that, that's been, that was the case in grad school working with undergraduates on this research. And that's still the case now. So. Thanks, Lexie.

Quinn: I love it, Brandon.

Brandon Ogbunu: Yeah, to stay within the spirit of the show, talking about a minimal cell.

It's not going to be an individual, it's going to be an institution because that's been my kind of minimal cell with regards to the thing that's empowered me the most. I was elected to the external faculty of the Santa Fe Institute a year ago. And I'm incredibly indebted to that place because that, it's like you, you're old enough to remember the blind melon video with the B girl.

And that's how I feel. I feel like I finally met my [01:01:00] tribe of people who think about the world and the way that I think about it. And they empower me to do so. And I think it's my unusual way of doing so, it's not unusual there. And so with them it's allowed me to lean into kind of my multiplicity and it's, and all aspects of my work, from my lab work to the other stuff has been amplified because of it.

So I would thank them.

Quinn: I love that. Do you guys know this scientist, and I apologize because I don't remember his exact discipline. Carlo Rovelli, have you heard about this gentleman? Wrote the book on time that's very small. And I just keep highlighting it and I feel like a conspiracy theorist talking about it all the time.

It's incredible. But he wrote this other piece, just to sum this up and come back to the question we just asked, and it's called The Big Idea Why Relationships Are the Key to Existence. And I'm just going to read this quote from it. I use this app called Readwise that sucks in all my highlights.

And I can come back to them and he said, Perhaps there's no need to make anything up about what lies behind quantum theory. Perhaps it really does reveal to us the deep structure of reality where [01:02:00] property is no more than something that affects something else. Perhaps this is precisely what properties are, the effects of interactions.

A good scientific theory then should not be about how things are or what they do. It should be about how they affect one another. And I love that. And I thought about that while reading about all the mutations that happened and didn't happen and all the evolution along the way because none of us evolve in isolation here or get better.

And I'm the product of 163 ish conversations. So I appreciate your time and everything you guys are bringing to this wide range of research, so thank you.

Roy Moger-Reischer: Thank you. I heard there were three questions.

Quinn: Oh, that's right. Oh. Yeah. This is always my favorite one because then it just demolishes the rest of my list.

What's a book you've read in the past year that has opened your mind to a topic you hadn't considered before or has actually changed your thinking in some way? And we got a whole list up on Bookshop. I'm going to get you guys out of here.

Roy Moger-Reischer: I'm currently reading Stolen Focus by one of your previous guests, Johann Hari.

[01:03:00] And certainly that's a good book so far. If I had to pick one. One book that has changed me in the past year is The Ghost in The Shell by Shirow Masamune. I read the original, the classic 1991 Cyberpunk Manga. And the reason that opened my mind so much is something that's written in ‘91, set in 2029, and just the perspective shift that requires and made me think, what sort of dreams were totally wrong?

What sort of dreams were totally spot on. The fact that I'm still dreaming about some of the same things of computer brain integration. Just as one example. But I'm not really, I don't know. I'm not super hot on radios these days. And the way it also made me think so what, if I was writing a cyberpunk Manga right now set 38 years in the future, what it would look like and what would I be incredibly wrong about?

So I would say, I don't know how many fiction manga there are on your book list. But that [01:04:00] changed, that's a book that changed me.

Quinn: I love that. That's a classic. Now I'm going to go reread it again. Brandon, what's on your list?

Brandon Ogbunu: Oh, gosh, so much. But I'm reading the Dawn of Everything by David Graeber and David Wengrow, which is just a massive and titanic rethinking about kind of everything.

So it's one of these grand books about how, the social order and the diversity in certain societies that has been taken for granted. And like you, I think about how I think what's important about the book is we just have this impoverished view with regards to the possibility within the human species.

We think there's the narrow view and frankly biologists are partly responsible for this, frankly, this narrow view of what a person is and what society is and the way it should be structured, that it's been this physics that just grows and all of a sudden everything's just flowered at Europe and everything's been great since that they gave us civilization. It's just not true. It's never been true. And I think this book really does a beautiful job of articulating just how diverse the scope of human structure has been through time. So I'm enjoying that.

Quinn: I love it. I'm not kidding when I say my [01:05:00] mother-in-law gave me that for my birthday in November and it’s still sitting at the foot of my bed because it's so big. I'm just like, I'm going to have to set aside some real time to do this. Roy, and this could be anything. We've had people talk about running for fifth grade class council. We've had people who lost somebody. It could be anything. The first time in your life where you felt like you had the power of change or the power to do something meaningful, and that is up to you on how to define that.

Roy Moger-Reischer: Defined in a boring way.

I would say that when I started work Arzeda, because I felt like, you've been in grad school for years and years doing stuff in academia. Yeah, it's cool. Synthetic, minimal cell stuff. But, it was, at the end of my first week here that I felt like, wow, okay now we're working with gas and doing something important.

But I don't think that's the, I think the best answer I have is that there's actually a lot of those moments that are more personal in nature, right? Where you finally understand something in your psychology that was [01:06:00] holding you back and you finally access that kind of, at least for me, the sort of vibrant, infinite feeling of love that drives you to do meaningful work.

And those are the moments where you go, oh shit, oh my God, look at what lies before me that I can do.

Quinn: I love that. I love it. It adds up. Brandon, if you got anything else you want to throw at it, go for it. But that's awesome. Gentlemen, that's it. I can't thank you enough. This has been fantastic.

Thank you for all your research, your time. Thank you for listening to my rambling. I will endeavor to cut mine down, but the rest of yours is just fantastic and enlightening. Thank you so much, Brandon. Thank you for coming back. I'll call you in five years to make you do it again.

Brandon Ogbunu: We'll do it sooner.

We'll do it sooner. Roy, thank you. It's a pleasure meeting you.

Roy Moger-Reischer: Likewise Brandon. Seriously, privilege.

Quinn: Roy, thank you so much. Really just so, so cool to see. I love the question of like, what if I think that really matters whether we're looking forward or back? So, [01:07:00] thank you gentlemen.

That's it. Important, Not Important is hosted by me. It is produced by Willow Beck, it is and edited by Anthony Luciani. And the music is by Tim Blaine. You can read our critically acclaimed newsletter and get notified about new podcast convos at important not important dot com slash subscribe. We've got t-shirts and hoodies and coffee stuff at our store.

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