157 | Elizabeth Strychalski on Synthetic Cells and the Rules of Biology

Natural selection has done a pretty good job at creating a wide variety of living species, but we humans can’t help but wonder whether we could do better. Using existing genomes as a starting point, biologists are getting increasingly skilled at designing organisms of our own imagination. But to do that, we need a better understanding of what different genes in our DNA actually do. Elizabeth Strychalski and collaborators recently announced the construction of a synthetic microbial organism that self-reproduces just like a normal unicellular creature. This work will help us understand the roles of genes in reproduction, one step on the road to making DNA molecules and artificial cells that will perform a variety of medical and biological tasks.

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Elizabeth Strychalski received her Ph.D. in physics from Cornell University. She is the founder and current leader of the Cellular Engineering Group at the National Institute of Standards and Technology. She serves on the steering group for the Build-A-Cell collaboration.

• NIST web page
• Google Scholar publications
• Talk on Controlling Biology with Complexity
• “Genetic requirements for cell division in a genomically minimal cell,” Pelletier et al.

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0:00:00.2 Sean Carroll: Hello, everyone. Welcome to the Mindscape podcast. I’m your host, Sean Carroll. And it has been said that while the 20th century was the century of physics, the 21st century will belong to biology. I’m not sure if that’s true or not. I think the 21st century is big enough to have more than one science in it. There’s plenty of room for both physics and biology to do good things.

0:00:20.1 SC: But there’s no question that the rate of progress in biology has been pretty amazing in recent years, and shows no sign of slowing down, especially in our ability to really manipulate what’s going on down at the level of cells and even individual strands of DNA. Those of you who are long-time Mindscape listeners will remember a conversation we had with Kate Adamala, who works on synthetic life, putting together cells from scratch, right? I mean, we don’t quite have that done yet, but this programme of building a cell starting with our human knowledge rather than from existing biology.

0:00:58.7 SC: What we have done so far is taking existing organisms, removing their DNA, by organism, I mean a little tiny, one-celled organism, removing its DNA and inserting DNA that we have designed, and seeing whether or not it will keep going. So a few years ago, scientists at the Venter Institute named after Craig Venter, were able to build what is essentially we think, the minimal cell that actually works in some sense, that actually reproduces itself and so forth. But to be honest, it didn’t reproduce itself that well, like we hope that an individual cell will split in two so that both halves look more or less like the original cell, that’s not happening with these minimal cells.

0:01:41.0 SC: So today’s guest is Elizabeth Strychalski, who works as the group leader of the cellular engineering group at NIST, the National Institute of Standards and Technology. And so she and her collaborators, including many of the people on the previous programme, were able to fix the minimal cell to build a minimal cell that reproduces nicely in some way. So basically, they took genes and they reinserted them back into the DNA until this little one-celled bugger was able to reproduce nicely, splitting in two, equal sizes, perfectly healthy, single-celled organisms.

0:02:20.5 SC: What’s amazing is, it’s amazing number one, that we can do that, right? I mean, this is opening up tremendous vistas for future progress. The fact that we can do it means that someday we’ll be able to do it well and easily. But also number two, we don’t know what all the individual genes do, what their responsibilities are in the cell. We know that if they’re not there, it doesn’t work, but we don’t know what actually happens in terms of those genes turning into proteins and making the cell go.

0:02:51.2 SC: So it is an amazing frontier, where we’re making progress but there’s so many things we don’t know. So Elizabeth and I talk about how this stuff works, why you’re looking for the minimal cell at all, how it actually happens in the lab with designing the DNA and so forth. And then, we speculate a little bit about what this means about the origin of life. The fact that the minimal cell has quite a few genes in it, hundreds of genes, makes an interesting question arise, right? How did that come about out of something that wasn’t a cell at all?

0:03:25.1 SC: But even more importantly, perhaps for practical purposes, what is this kind of technology going to be good for in medicine, in drug design, in sensing what is happening in the body. This is one of Elizabeth’s specialties, is imagining that we can figure out how your body is doing by inserting little sensors into it that we’ve constructed synthetically as cells in their own rights.

0:03:47.2 SC: So I don’t know what to say about this, I’m not a biologist, but it’s extraordinarily exciting. And the prospects are practically limitless. And I think that in the decades to come, we’re going to be seeing the payoff from this kind of research, and it’s gonna change lots of things in interesting ways. So let’s go.

[music]

0:04:22.9 SC: Elizabeth Strychalski, welcome to the Mindscape podcast.

0:04:25.7 Elizabeth Strychalski: Thanks so much. It’s a pleasure to be here.

0:04:29.6 SC: So as a physicist, what we’re trained to do, what I’m trained to do is tear things apart to their constituent pieces, whether it’s an atom or a solar system or something like that, and look for the basic underlying laws. And I know that a lot of people in biology, or at least I get the impression, that there’s a conventional wisdom that there are no such underlying laws in biology.

0:04:49.4 SC: Biology is just a mess. Every organism is different. You have to go piece by piece. So is that the right impression to have? Or is the search for fundamental underlying laws still a good thing that we should try to do?

0:05:01.2 ES: Personally, I think that even if there are no fundamental laws that look like the fundamental laws we might be used to finding, even the search itself is worthwhile. There’s nothing wrong trying to strip something to its essential elements, to try to ask, “Is there an essence there? Or how much of this object that I understand or want to be essential in some way, is actually the result of relationships between the different parts?”

0:05:29.6 SC: And do you find in your… I’m just gonna peek ahead a little bit, but do you find in your work that that’s true? Are we discovering little ideas that might someday grow up into laws of biology?

0:05:40.6 ES: Wow, such a great question. It is my sincere hope that we find laws. And personally, I’m hoping that we find laws that look more quantum mechanics in the wild, or applied quantum mechanics, where we arrive at a recipe book that allows us to do practical things. And so maybe biology would look less like synthetic biology and more like engineering biology. And again, these are words, but words matter. Matters what you call things.

0:06:14.1 ES: And so we have some real challenges in the world right now that we face, and I think we should bring all of our collective knowledge and capability to bear on these, and one exciting toolset that we have is synthetic biology and engineering biology.

0:06:29.4 SC: Right. Well, in fact, the words that you’re using are reminiscent of the metaphor I was going to ask about. In some sense, what you do is kind of like the enthusiast for the latest smartphone who tear them apart when they appear and try to figure out what all the pieces are. We have some working gizmo, but in your case, it’s a cell or an organism and you’re trying to tear it apart, right?

0:06:52.0 ES: I love that analogy. And I came originally as a physicist, I grew up through the experimental high energy physics community. And so what a lot of what high energy physicists try to do is to smash apart the basic building blocks of matter to understand what is there. And so for me, it makes perfect sense that you wanna smash apart a biological system to understand what’s there and how those parts interact.

0:07:18.7 ES: Now, of course, once you arrive at those laundry lists of parts and relationships, there’s still some secret sauce that we don’t understand, this science around emergence and complex systems, and what’s that spark of life that suddenly you no longer have just a pile of stuff, you have a pile of stuff that is, air quotes here, alive. [chuckle]

0:07:46.3 SC: Right. Well, actually, your statement makes me realise there’s something very fundamental and simple that I don’t understand. I understand when a person dies or any higher organism dies, there’s a whole bunch of processes that go on between the cells that no longer happen. So we don’t… It’s very similar set of atoms and molecules, but it’s no longer a living being. What happens when a cell dies? Do cells die? Do they just sort of grow old? [chuckle]

0:08:19.5 ES: Yeah, so some cells die, some cells grow old in certain ways. I should mention as an aside that I am emphatically not a cell biologist, I merely play one on TV. [chuckle] It’s always good to have a cell biologist on your team when you’re working in this field. And I should mention too that what’s really exciting about the way biology moving forward around questions of minimal life, synthetic cells, is you find yourself on these larger collaborations where you need deep knowledge in lots of different fields, all coming together [0:09:00.7] ____ of those fields to make it happen. So I bring the physics and engineering perspective, but coming back to your question about…

0:09:06.6 SC: Actually…

0:09:07.9 ES: Cells dying… Yeah.

0:09:09.0 SC: So you’ve opened a little Pandora’s box there, I gotta dig into this more. So you and your team and your collaboration that you’re working with, are literally building cells. So to someone like me, that makes you a cell biologist. So maybe…

[laughter]

0:09:25.1 SC: How do you classify yourself? What are the different kinds of people who have to work together to make something like this happen?

0:09:30.2 ES: One of the really exciting things about working in the life sciences right now, and specifically in synthetic biology and engineering biology, some people call it “cellular engineering”, I wanna make sure that I say a lot of the different buzzwords so that folks could go google these later if they wanna learn more.

0:09:45.7 SC: Yeah. Perfect.

0:09:47.6 ES: It’s that we’re taking these well-developed, deep bodies of knowledge from what used to be siloed disciplines, and we’re basically mashing them all together to see what sticks. So for example, you mentioned control of biology earlier. So if I take control engineering as we understand it from say, radios and computers or building a car, and then overlay that with cell biology, what might be possible?

0:10:20.5 SC: Right.

0:10:21.0 ES: And this is one thing that folks are trying to understand right now. So typically, you might have somebody who has biophysics knowledge, you need people who have knowledge of the different measurement techniques that you need. For example, maybe electron microscopy or fluorescence microscopy or DNA sequencing. You might need an automation specialist, because as we know, biology labs are looking less and less like someone standing next to a bench with a pipette in their hand and a white coat, hopefully goggles too as well.

[chuckle]

0:11:00.7 ES: Please, everybody to the extent that you’re in your garage biohacking, please take safety seriously.

0:11:04.1 SC: Wear the goggles, yes.

0:11:06.8 ES: And it’s starting to look more and more like laboratories filled with robots. So you might have… We have a mechanical engineer who’s part of our team in my laboratory, for example. We work with folks who are experts in machine learning, because as you automate these measurements in these experiments, you’ve got a whole lot of data out. More than it’s easy even to think about. [chuckle] It’s a lot.

0:11:36.4 SC: Sure.

0:11:37.5 ES: What that does is it lets you ask new and different kinds of questions about biology, because you can bring to bear all of this incredible computation power that you get from machine learning.

0:11:50.1 SC: Okay, so I interrupted you when you were explaining how cells can die. What is the process inside that no longer happens to that collection of atoms and molecules?

0:12:01.2 ES: Well, the easiest thing to say, I think, is that it’s no longer doing the things a living cell does. I know you’ve had other guests on your show who have spent time talking about what is life, or even about building synthetic cells. I think for me, as somebody who comes from more of a physics and engineering standpoint, I like to think of life and death as kind of a spectrum.

0:12:28.9 SC: Okay.

0:12:29.3 ES: In the same way that I think of a spectrum from chemistry to biology. And depending on what you want to build or do, or what capability you wanna have, you might wanna situate yourself at different places on the spectrum. So for example, I might want to bio-remediate something, which would mean that I’m going to engineer something biological and then release it. Well, do I really want it to be able to reproduce?

0:12:56.6 SC: Right. [chuckle]

0:12:57.4 ES: Maybe not. [chuckle] Right?

0:12:58.7 SC: I’ve seen that movie. It doesn’t go well.

0:13:02.2 ES: No. You know, it never does. It never does. A couple of years ago, I was actually trying to convince some funders that we need to try out terraforming technologies on an asteroid or something, off Earth, because that way when we need it here, it’s not our first go.

0:13:25.0 SC: Right. Right, right, right, yeah. Well, okay. So that is very interesting. Like you said, we’ve had people on the show who talked about, “What is life, what is a cell?” Kate Adamala, who I guess is a collaborator of yours, or at least in the same big group, talked a little bit about synthetic biology, but maybe some of the people listening right now haven’t even heard that.

0:13:43.8 SC: And so what I’m guessing is, everyone knows that cells have membranes and a little nucleus inside with DNA, and the DNA converts its little parts into proteins which then go do things. Do we need more knowledge than that for what’s about to come when we talk about building a synthetic cell? I mean, what about how the cell works, is the basic knowledge platform that we’re gonna have to build on here.

0:14:08.2 ES: There’s so much fundamental knowledge we still need to gain. And just to make sure, for completeness that we cover this, there are two main paths forward that people are walking down to arrive at something like a synthetic cell or a minimal cell. So you can take the bottom-up approach, where you take non-living parts. If you’re a purist, I guess you would start with chemistry, not even biochemistry, and you would try to assemble bits and pieces until life happens. So this has not been done yet, to the best of my knowledge. Although lots of folks are working in this area and making great progress.

0:14:58.7 ES: The other path forward is more of a top-down approach where you start with something that is already a living cell, and you take parts out until it dies in some way. Now, it’s really simple to say these things, but when you actually go about trying to do them, the devil is in the details.

[chuckle]

0:15:23.9 ES: And with regard to the minimal cell work that I’ve been doing recently with just wonderful collaborators at the J. Craig Venter Institute and other places, and I wanna give a shoutout to my co-authors, James Pelletier and Lijie Sun. They’re just fantastic to work with. So what we’ve been doing there is, you start with something called an obligate parasite.

0:15:51.8 SC: Okay.

0:15:53.9 ES: And what that means is it’s an organism that can’t live outside of its host. It still has all the cellular machinery that it needs, but it’s adapted to live in a very stable, very specialised environment, which means that it hasn’t needed to retain a lot of the genetic information or proteins or other bits of itself that it needs to respond to a changing environment.

0:16:16.1 SC: But this is one cell we’re talking about, unicellular organism?

0:16:20.2 ES: That’s right, that’s right. This is a kind of mycoplasma.

0:16:22.3 SC: Okay.

0:16:25.2 ES: And it’s a goat tuberculosis, I guess. So I had to sign up outside my lab for a long time saying, “If you have a pet goat, don’t come in here.”

[laughter]

0:16:38.9 ES: So the scientists developed a way to scramble parts of the genome and then grow the cells that resulted, and then you can sequence the DNA that’s left from the cells that grew well. So you can guess that if any of the genes were scrambled and so couldn’t be expressed, they must not be essential for life, so cut them out. So you can take that empirical approach.

0:17:03.7 ES: You can also take an approach where you look at related organisms, and you can kind of guess what the function of different genes might be and guess whether or not a certain gene is essential or not. Now, you’ll notice I’m not saying essential for what. Because when folks talk about minimal life or minimal cells, what’s implicit in that is that you’re minimizing to some criteria. You’re putting some boundary conditions on this thing.

0:17:34.8 ES: When the JCVI and collaborators published in 2016, the minimal cell, this was JCVI-Syn3.0. What they did was they minimised the criteria of the cell growth looks normal at the colony level. So when you looked and you could even see these by eye, you got this beautiful… If you’ve ever seen a mycoplasma colony, it looks a little bit like a fried egg and, but small.

0:18:00.3 SC: I probably never have.

[laughter]

0:18:04.6 ES: And so it looked totally normal. And the other thing that they wanted was they wanted the cells to grow fast enough, again air quotes here, that it was useful for work in the laboratory. Nobody wants to sit around for a week while their cells finally get around to double. It’s just not practical. It really slowed down your research. So they wanted to keep genes that would keep the cells growing fast enough to be useful.

0:18:31.1 SC: Okay.

0:18:31.8 ES: Well, we took a closer look at what was happening. It turned out that none of these minimisation criteria paid any attention to what was happening at the single cell level, and so when we looked under our microscope, it was absolutely bonkers what was going on. I mean, crazy. We took some optical micrographs that showed videos of these things growing in microfluidic chips on a microscope.

0:19:00.9 ES: And you would start with this perfect, spherical, round, totally normal looking cell, and then you come back a little while later, and there are filamentous cells, branching cells, huge things that I don’t even know if it’s a cell or a huge vesicle. And it’s just crazy because if we try to understand biochemically what’s inside of these structures, what’s stabilising them, what about the biophysics of the membrane, for example, leads to these, we don’t actually know. And all of this is happening in the background. I was not even understanding what the division mechanism is for these cells.

0:19:46.7 SC: So your task was to fix the cell. So the Venter Institute had stripped away parts from mycoplasma and made a sort of minimal self-reproducing cell, but it didn’t reproduce very prettily and you wanted to give it a little bit more coherence somehow. Is that fair?

0:20:09.2 ES: I think that’s fair. It’s a mycoplasma, and so you may or may not care for your purpose, whether the cell looks pretty at the single cell level, your end goal might only want a pretty minimal cell that gives you this normal looking colony. But if you’re talking about cellular engineering and you’re talking about inserting new functions inserting new genes, understanding there are folks who are working on whole cell models of these cells to try to really drill down and understand what is each molecule doing, what is each gene product from each gene doing, so we can draw direct lines from genotype to phenotype, phenotype to gene.

0:20:58.1 SC: That is to say from the DNA, the genotype to the actual organism, the phenotype?

0:21:05.1 ES: That’s right. And so, as an engineering tool, cell size and shape, it’s one of the most basic aspects of cellular life. Maybe we should understand this, guys.

[chuckle]

0:21:23.8 SC: And so JCVI had declared victory, and in many ways it was a great victory. They developed a lot of impressive techniques that have pushed the field forward, but I thought it was really important and I’m glad they thought so also, to take a closer look at division in these cells, trying to understand these different phenotypes, these different morphologies and sizes and shapes.

0:21:47.4 SC: Let me actually back up because I think there’s probably a lot of details here that would be fascinating to the audience. When you say that you take the DNA in one of these cells and you chop it up and you turn off or scramble some genes, number one, how do you do that? I think there’s probably a lot of people have in mind that you have tweezers and you stretch out the DNA and then you like, chop off the ones you don’t.

0:22:13.1 ES: Well, you just reach out and you do it, you just use your fingers, right?

[laughter]

0:22:16.6 SC: I mean, these are very tiny molecules, these DNAs.

0:22:19.8 ES: This is a great point, and again, as a physicist and I have a great interest in mechanical systems, I love thinking of of tweezers. But in this case, the tweezers are… Well, this is what makes Lijie’s work in particular so heroic, and the other scientists at JCVI, because they’re the ones who really develop the capability to reach into this minimal cell and genetically modify it. So what you can do is… So first of all, actually, let’s back up a little bit here.

0:22:58.3 SC: Yeah, please.

0:23:00.6 ES: So the minimal cell, I mentioned it was called JCVI-syn3.0. Well, there was a 1.0, and 1.0 involved printing DNA on a machine, so this DNA had never been in a living organism, and then what you do is you take a cell, make its such that it’s no longer expressable. So essentially you have a zombie cell now, you kinda take out its brain.

0:23:30.0 ES: So you got this zombie cell, and then you take your printed synthetic DNA, synthetic genome, and you kind of… Well, we don’t know exactly how the genome transplantation process works. This is something that’s still an open question.

0:23:43.6 SC: Okay.

0:23:45.2 ES: But it does work. The yield isn’t great. So this is something that personally I would like to work on more to understand, because I think if we could print, just as an aside, if we could print any DNA we wanted, and insert it into any cell whose genome we’ve inactivated, think of what would be possible. Because you wouldn’t have to go through any living intermediates, you wouldn’t have to make these kind of adiabatic incremental changes to your cell to arrive at what you want. You could just print it. This blows my mind.

0:24:18.4 SC: 3D print your life form. Yeah.

[chuckle]

0:24:22.3 ES: Anyway…

0:24:23.5 SC: But we can’t… We almost can? There’s some sort of hacky way of doing it probabilistically or something? What do they do?

0:24:30.3 ES: So we tried to do it in micro-fluids but the yield was too low for us to see what was happening. But they think that part of the secret sauce is that you have your cells growing up in a fluid, in their, basically in the broth that they grow in. And then you add a polymer peg, polyethylene glycol, of a certain molecular weight at a certain time in the growth, at a certain temperature. And the moon is in the right phase.

[chuckle]

0:24:58.3 ES: And you’ve got the person doing [0:25:00.1] ____. And by the way, [0:25:01.2] ____ are actually a broader issue, with regard to reproducibility in the bio sciences. So it’s a thing. And what happens is the peg makes cells kind of slam together, so they slam together with this DNA that you want inside of them.

0:25:21.2 ES: We think there’s something like a big syncytial cell that forms, and then at their next growth cycle, they kind of divide apart. And so a syncytial cell is one where it has multiple genomes inside of it, so think of all of these cells forming one big membrane together, and then when they grow apart again, some will have the new genome that you’ve printed, that’s synthetic. Some might have the old inactivated genome.

0:25:51.1 ES: But at any rate, once you grow them up, you now have your zombie cells come back to life with the new genomes. And part of the process of putting together these synthetic genomes was that Dan Gibson and folks divided that genome up into different pieces. Because it’s hard to manipulate a whole genome at once.

0:26:13.3 ES: If you think of like… Imagine a really, really long piece of cooked spaghetti. I mean really long. If you wanted to pick it up and move it somewhere, chances are, it’s gonna come apart in your hands, you might get some breaks or you might nick it somewhere. All of that would mean if it were a genome that it’s not going to express in the way that you want anymore.

0:26:36.7 ES: So they were able to manipulate this genome in yeast using very interesting techniques that I don’t fully understand but I’m thankful that they did. [chuckle] And one of the reasons I’m thankful is that one of those segments, we call this Segment 6, ended up having… So first of all, these segments gave us handles for looking at the gene content in each of these segments, to try to understand, “Well, does this segment have the genes that affect shape and size of the minimal cell?”

0:27:05.9 ES: So one of these segments, Segment 6, actually… So it did seem to have these genes, and so what we could do then is narrow down our search to a much smaller number of genes, and then through a much more systematic approach, testing groups of genes and then single genes, we drilled down on seven genes that seemed to together reconstitute control of cell size and shape in the minimal cell.

0:27:40.2 ES: So now there’s this JCVI-syn3A strain, that I think something like 43 different labs are using around the world to study the minimal cell. So we call it a nearly minimal cell because it does have more genes than syn3.0, but what you get in return is that you have cells that are much better behaved at the single cell level.

0:28:04.6 SC: So you had what was judged to be the minimal cell, then you added in seven more genes and that helped it reproduce in a aesthetically pleasing way.

0:28:14.3 ES: You know what the real kicker is here too? That those seven genes, included two genes that are known to be involved in cell division, FtsZ and SepF. But the next one is a hydrolase with some unknown substrate, and then four of the genes, we have no idea what they do. We think they might encode membrane-associated proteins, but we have no idea what they’re doing.

0:28:42.2 ES: So even in this most basic aspect of cell physiology, we run across these genes of unknown function. They are really an elephant in the room when you talk about these whole cell models people are trying to build, or cellular engineering and synthetic biology in general, there’s so much of the genome that we aren’t able to tie back to some function.

0:29:05.8 SC: But you do… You have convinced ourselves that if you didn’t include every one of these seven genes, it wouldn’t do what you want it to do, so you’re not sure why, but you need all seven of these genes?

0:29:16.9 ES: That’s right. And one thing we haven’t mentioned is that this is an absolute tour de force, this reverse genetics approach that we took. I think since I got involved in the project, I think it was seven years until we published. Which is long even for biology.

[laughter]

0:29:37.9 SC: It’s short for particle physics, as you know. Okay, so I’m gonna ask an even dumber question that I ask for every cellular molecular bio-type person I have on the podcast, what do you mean when you say a “gene”? I know what a base pair is in DNA. I have this vague feeling that a gene is a group of base pairs that does a thing. But how do you operationally pick out which part of the DNA strand is the beginning of the gene and then the end of the gene? Who says? How do you figure that out?

0:30:12.0 ES: This is a fantastic question. Personally, I rely on the experts in this area, this is not my area of expertise, but there are databases you can go look at where people kind of parse genomes. It’s not all settled, also. People might say that, “Well, you gotta group these together, these base pairs together in order to form a gene that makes some protein,” and then somebody might come on and say, “Actually, you’ve gotta shift it a little bit this way or that way.”

0:30:46.8 SC: Okay. That makes me feel better ’cause I didn’t understand it. So if it’s not understood then I feel like less behind the curve a little bit. [chuckle]

0:30:54.3 ES: I defer to the experts in this.

0:30:56.0 SC: Right, okay. Very good. And I probably should footnote something, ’cause I think I mentioned the nucleus of a cell at the beginning, but of course, these are probably gonna be prokaryotic cells, there’s no nuclei in them. Right?

0:31:08.8 ES: That’s right. And I think that one of… It would be a really interesting capability to take this genome minimisation process that’s been demonstrated for this very simple obligate parasite, this mycoplasma, and apply it to an eukaryote, so a cell that does have a nucleus, maybe a yeast or maybe a mammalian cell, and see what we learn from that.

0:31:34.5 ES: Because this minimal cell, it isn’t just a thing, right? It’s not just JCVI-syn3A and we’re done. It’s also a whole repertoire of tools and tricks and measurements that we can apply to any number of biological systems.

0:31:49.9 SC: How many genes total in this minimal cell?

0:31:53.9 ES: So JCVI-syn3A has 493 protein encoding genes, and just for reference, an E. Coli has about 4400 genes and humans have about 20,000, although I think that’s, we’re still sorting that out.

0:32:11.9 SC: But then there are other… There are like dandelions or whatever, they have way more than human beings, right? Human beings are not the maximum number of genes or anything close?

0:32:19.0 ES: No, but it’s a natural point of reference for us. [chuckle]

0:32:21.8 SC: Sure, oh yes, absolutely. But I don’t wanna put us up too much on our high horses, we’re not the most numbered. We’re actually more efficient in some ways, right? Than some organisms?

0:32:31.6 ES: Well, I appreciate your comments, but I actually do wanna put us on our higher horses for a second here.

0:32:35.3 SC: Okay. Sure.

0:32:36.8 ES: Because when I was talking about the genome minimisation process, I mentioned that there were these arbitrary criteria that you’re minimising with respect to. And one thing that I find so fascinating about the creation of protolytes, synthetic cells, minimal cells, is how much of the scientist just unavoidably ends up in that process, in that product.

0:33:05.1 ES: It’s almost like it’s an art form in some ways, or a mirror, where we’re using this new medium of synthetic biology or engineered biological systems to hold a mirror up to ourselves. I’m hoping that, because there’s two ways to get past the N equals one problem of biological systems.

0:33:27.6 ES: So just to back up here a second, one of the challenges of creating synthetic life is that when we look around us, we really only have one example of cellular life, and that’s what’s evolved here on earth. So those are two ways, I think, that two main ways where we could get more examples, one can be to go out and find it somewhere else, hopefully we’ll recognise it. The other way is for us to build it.

0:33:53.8 ES: I’m hoping that we’re not so biased by ourselves in our cells that we aren’t able to imagine what else could be possible. This also brings me back then to your question about the rules of life and what are they. I think so much is unknown here, that as we go about engineering biological systems, it’s almost as if we’re not limited by the fundamental physics of it, right? The laws of the universe of it. At this point it’s almost like we’re limited by our imaginations.

0:34:33.2 SC: The minimal cell that you mentioned with almost 500 genes, I presume that once again, we have a high degree of confidence that if we removed any one of them, it wouldn’t work anymore, right? That’s what it means to be minimal?

0:34:46.8 ES: That’s right, and I should note that there are about 100 genes of unknown function left in that cell.

0:34:52.9 SC: So we don’t know what they do, but we know that if we didn’t have them, things would go wrong?

0:34:56.8 ES: That’s right. There are also, though, some subtleties in this too. So imagine if you have an airplane and you wanna take parts off that airplane until it’s not able to fly anymore. So let’s say that I remove an engine, I’m gonna say that’s not essential because I’ve got another engine. [chuckle], but what if I remove both engines, right? So the way that…

0:35:18.6 ES: The process, it’s sort of path-dependent. You’re a physicist, right? So it matters how you get there to the minimal cell and you can find yourself accidentally deleting genes that were essential, like we did when we developed 3.0 and we needed to put genes back in to get control of cell size and shape.

0:35:37.5 SC: And even though the actual DNA was synthesized, if I understand it correctly, it was all based on real genes that appeared on living organisms. No one is yet going in and building base pair by base pair, new functional genes. Is that right?

0:35:55.4 ES: Wow, that would be incredible if we could do that. We are not there yet. But there are a number of challenges still, and for minimal cells, I think that we need to know what these… We need to learn what these genes of unknown function are doing. I think that we need to arrive at a more genetically tractable minimal cell.

0:36:18.0 ES: What I mean by that is that we have tools where, not just the properly indoctrinated and practiced folks at JCVI, but anyone is able to very easily to medically modify these cells. So right now, they’ve put something called landing pads into the genome, where you can add genes easily at those places. So that does help a lot.

0:36:46.6 ES: But for right now, if you want to delete genes, you have to go through this docking the genome in yeast, manipulating it there, and then doing this genome transplantation process to arrive at the modified genome. Now, for right now, there aren’t so many people working with this cell that JCVI won’t generously offer to help you with this. [chuckle] But at a certain point, I think our hope is that more folks will take up this system so that… ‘Cause there’s so much to learn and there’s so much to know.

0:37:24.6 SC: Clearly, yeah.

0:37:26.9 ES: Other challenges for the minimal cell is how do we generalise that minimisation workflow for other organisms. And then what is close to my heart, because I work at the National Institute of Standards and Technology, so I’m a metrologist, I study the science of measurements. I would like it if we could make it easier to measure the current minimal cell.

0:37:50.1 ES: This thing is really small, it’s about the same size as the wave length of light. So it’s really hard to see. I was talking with my collaborators and I said, “Well, can we just make this thing bigger?” If we really can just engineer the size and shape, can we just make it bigger? Well, maybe. Are there techniques to swell the cell?

0:38:16.2 SC: So if this set of genes is needed, we think minimally, at least it is, let’s say A minimal set, if we move anything from that set, like you say, it wouldn’t work anymore, but maybe there’s another set that is containing different genes that is also has the feature that if you remove anything, it wouldn’t work either, right? Maybe there’s more than one way to be minimal?

0:38:37.6 ES: That’s so important, and I’m so glad you brought that up, because… And this is why I wanna focus on that workflow of minimisation, ’cause I think at the end of the day… Can I say this? I don’t wanna get in too much trouble. But mycoplasma is not that useful for people.

0:38:53.5 SC: Got it. Yeah.

0:38:55.8 ES: It’s good as a research platform, but it’s not that useful. And so if we can empower people to make minimal versions of their own cells of interest, minimised according to their own criteria, imagine what we could learn? I think it would be really empowering.

0:39:14.6 SC: And even if this particular species is like you say, not that useful, can we nevertheless relate this set of genes, the 400 and some genes in this cell, are the same genes elsewhere? Do they also exist in other kinds of cells so we feel like this is an instruction set that is common to all kinds of life? Or is it not?

0:39:36.3 ES: That’s true for a lot of the genes that are in the cell, and this is a common technique that cell biologists use, where they look at related organisms, or even not so related organisms, and try to guess what the functions of different genes or proteins is. This is one of the reasons why it’s a little vexing that we still don’t understand the mechanism behind cell division in these cells.

0:40:04.4 ES: ‘Cause we can’t point to a mechanism from, so far, from another cell and say, “Oh, our mycoplasma is dividing like that other cell.” But one reason why mycoplasma was chosen is that it comes pre-minimized by nature as an obligate parasite, so it’s been kind of singled out for a while as a candidate hydrogen Adam of biology, if you will.

0:40:33.9 ES: And I wanna mention too that this idea of the minimal cell is really not new. Way back in ancient times, philosophers loved to think about the building blocks of matter, including life. But more recently, in the 20th century, I believe the 1930s, a bunch of scientists got together, physicists were involved, I think even in a leadership role, and they decided that the minimal cell could exist, and you know what, maybe it aught to exist.

[chuckle]

0:41:03.4 ES: Because it can do three things for us, and it still can do three things for us. It can tell us, maybe, how cellular life came to be. Maybe we can learn something about the history of life. It might offer a platform for understanding life today. So for understanding the present cellular life, including ourselves.

0:41:23.1 ES: And more recently, especially with the work that I’ve become involved in, I think that it can offer a platform for the future, for what life could be. And more specifically, what could we, engineer of cellular life, we’re at this really exciting time where we have the ability to hopefully soon make make… We need agnostic life. And this is a term that I’m stealing from Drew Endy at Stanford.

0:41:51.0 ES: I heard him use this term and it was just such an eye-opener for me, because up until now, every cell has come from another cell, but now, that doesn’t need to be the case anymore. So what does that mean? What do we do with that? How do we understand that?

[chuckle]

0:42:13.4 SC: You actually raise a challenge that I hadn’t quite appreciated before about the origin of life, which you mentioned something that we can try to learn something about. If the minimal cell has almost 500 genes and genes have lots of base pairs in them, that sounds like there’s quite a gap to be bridged from a bunch of macro molecules to a living functioning cellular organism. Yeah?

0:42:39.4 ES: It’s gonna be a while yet, I think. And so stay tuned, hopefully in our lifetimes we will get there. This gap is one that we’re trying to close from both ends, we’re using this bottom-up approach and this top-down approach. And the challenge that the bottom-up folks have… I know I shouldn’t pick favourites, maybe I am here a little bit. But the bottom-up folks, they, there hasn’t been success yet, and so it’s very difficult to focus their efforts. Whereas if we start from something that’s already alive, we’re good at killing things.

[chuckle]

0:43:16.0 SC: Yeah. Or even injuring them, yes.

0:43:19.0 ES: One way forward, I think, in the top-down approach, is to use those capabilities of automation and the laboratory machine learning to make lots of different versions of the genomically minimal cell and then put them in lots of different environments. Because they’re minimised in a specific environment, you can’t separate those two.

0:43:43.6 ES: In the same way that we are nice and alive in our offices right now, breathing the air around us, you take that away and you might say, “Well, maybe they’re missing the gene that they need,” but really you just needed something in your environment. [chuckle] But if we can massively parallelise and automate this process of minimisation, maybe that’s a path forward for learning new and interesting things about the minimal cell.

0:44:16.7 SC: Maybe that addresses what I was gonna ask next, which is, if we have this minimal cell with 400 some genes, and as you’ve very provocatively emphasised, we don’t know what some of them do, how are we gonna learn that? Is it just a matter of taking one by one and seeing what fails? Or because they do interact with each other in such crucial ways, do we need to be more subtle than that?

0:44:42.1 ES: Up until now, learning the function of each gene, it’s really been a hard won. And I’ve experienced that personally with these seven genes that we’ve identified in the minimal cell over… I even made a t-shirt, it says, “Seven genes, seven years.”

[laughter]

0:44:54.9 SC: Alright. We need to speed things up a little bit, I guess.

0:44:58.4 ES: You know what? We really do. And now that we’ve gone through this process once, there are all kinds of things that we would do to speed it up. Use automation, use proper design of experiments. So for you biologists out there, or other folks who don’t know that this is a thing, please know this is a thing.

0:45:18.1 ES: Where you can more efficiently design your experiments to get better answers on a fewer number of threads. We can do that, we can work with our machine learning colleagues to interpret the data. Because numbers are great, but if you can’t get any meaning from them, what are they worth?

0:45:37.1 SC: Yeah. This might be jumping outside of what we’ve been talking about, but there’s the issue of how the genes come together to make a reproducing cell, but then there’s also in bigger organisms, the issue of how cells come together to make an organism and cells differentiate in interesting ways. Is there a parallel track where we get to learn about how cells interact to make morphology and things like that, based on what genes they have?

0:46:05.0 ES: So even just last week, I was at a conference with those folks. So there’s this whole ecosystem of different groups of researchers and I have spent some time having interesting conversations and interactions with the build-a-cell folks, and the minimal cell folks, and the synthetic cell folks. But then there’s also the tissue engineering folks who interface with the stem cell differentiation folks, and the organoid folks, and the soft robotics folks.

0:46:39.5 ES: You can kind of step your way through all of these adjacent related very interesting fields, and it’s just the most fun you can have. I’m hoping we can all learn from each other, because you’re absolutely right, at the end of the day, wouldn’t it be fantastic if we could build capabilities, not just at the cellular level, but also at the multi-cellular level, so that we can engineer life at all scales, and even extend it a little bit further to become much better at interfacing biotic and abiotic systems.

0:47:14.4 SC: So I glean from your answer that even though this can be very, very exciting and we should try to do it, we don’t know that much yet. We did have Michael Levin on the podcast, from Tufts, and he talked a little bit about how organisms seem to have some kind of memory of what their shape was supposed to be. Like if you move the eye of something, it’ll move back, and so forth.

0:47:35.3 SC: But roughly speaking, I get the impression this is all kind of mysterious. We don’t know… Even if we don’t know how a specific cell regenerates happily, then knowing how a macroscopic organism is gonna do that, it’s gonna be a much harder challenge.

0:47:48.4 ES: How wonderful that there are these interesting questions for us to investigate.

[laughter]

0:47:56.1 ES: There’s fantastic progress in all of these areas. Again, I’m not the best person to speak to them. I guess I’ll just put an advertisement for the life of a scientist here and just invite anybody, just warmly, please come investigate these with us. It’s a wonderful community, and everybody’s ways of thinking about different ideas and approaching the problems, they all bring a unique perspective.

0:48:28.2 ES: Clearly, the way we’ve been thinking about it so far with the information we have, we’re not there yet, and so maybe you can come and bring your ideas and lead us all to the “aha” moment.

0:48:41.4 SC: Good. So let’s get back to the cell or the individual cell. You’ve hinted at the idea that one of the motivations for building this minimal cell is that we can then de-minimalise it. We can sort of do things with it. We can start adding things that we wanted to do. What are your favorite potential applications? And we can be a little speculative here, this is not a grant proposal review. We’re thinking about what the future might hold.

0:49:09.1 ES: This is a great time for me to put in the obligatory mis-disclaimer, so nothing I say here represents an official position of the US government or implies endorsement of any company, commercial product or service. [chuckle]

0:49:20.0 SC: Very good.

0:49:24.6 ES: So in some ways, what we’re talking about here is, and I’m gonna use this term on purpose, even though it is provocative, this idea of gain-of-function. So in some ways you could… Typically, people use that around infectious disease research, but if you take it literally, gain-of-function is engineering biology, and if you talk about building a minimal cell or life from scratch, that’s almost the ultimate gain-of-function research.

0:49:54.9 ES: So I’m imagining that we learn enough and maybe the minimal cell gives us a path forward with this, where we can build up best practices, maybe some rules, design rules, rules of thumb, protocols, where for different classes of function, we understand how to put those back into a cell. Which functions play nicely together and which don’t. How do we manage resource utilisation in the cell?

0:50:23.0 ES: And all of these bring us back to that idea of control in biology. You’ve been using the term “engineering biology” and “cellular engineering”, but unless and until we have a rigourous control engineering for biological systems, it’s kind of an aspirational title to say that it’s engineering.

0:50:44.3 ES: And so one thing that my lab works on is building sensors, so if you imagine a control loop, let’s say, one that you might be familiar with from the cruise control in your car, or the thermostat in your house, what you have is you have some desired output of a system, and there’s a controller, then that controller might do something to actuate some change in the system that leads to some output.

0:51:15.9 ES: Well, if you can close that loop with a sensor, with something that measures that output, you can then feed that error back into the controller to make sure that you stay at your desired output. So what my lab does is it uses biological parts to make living measurement systems or sensors inside of cells. Because biology is measuring itself all the time, seems like we aught to be able to make measurement tools out of biology also.

0:51:49.4 SC: Okay, so when you started talking about that with the thermostat analogy, I was going to ask, well, so why have biological sensors if we have perfectly good physical ones? But I guess you’ve already answered ’cause you said you’re putting them inside the cell. So, what are you trying to sense inside the cell? If it gets sick or if it’s stressed or if it’s happy?

0:52:12.5 ES: Absolutely, you’re spot on. So I wanna give a shoutout too to the communities who are, they are trying to put miniaturised physical sensors inside of cells, so they look like nano machines or all kinds of bright and interesting things, and that maybe falls more under the biotic/abiotic interfacing research of the cellular level.

0:52:34.4 ES: Now for us, we’re engineering proteins, for example, to measure small molecules in a cell’s environment, or you can imagine measuring the stress state of a cell. And one place where this matters is, imagine that you have a company and you’re growing vats of bacteria that you’ve engineered to make a small molecule product or a medicine.

0:52:58.6 ES: And so you might wanna know, ’cause you have a lot of money tied up in that vat, and as we know, biology can do strange things sometimes for inexplicable reasons. [chuckle] Because we don’t understand it well enough yet. So you might wanna have sensors built in so that if you have a physical sensor outside of the cell, you might just know that maybe the pH is off. Or the yield of your product has changed in a way that you’re unhappy with.

0:53:27.0 ES: But imagine having a sensor in each cell. In fact, imagine having that control loop in each cell, so that when the yield output from that cell does something you don’t like, that actuator in that control loop then kicks that cell into becoming a high producer again, so that you can maximise your profits, and then fund more research with your profits.

0:53:53.9 SC: So that is bringing it closer to this true gold engineering, rather than just sort of building an individual cell, putting it to work in more specific ways.

0:54:02.7 ES: You can think of biology as one of the most advanced manufacturing platforms that we can imagine. And there’s a place, of course, for industry the way that we built it up up until now, but imagine if we could grow our products the same way we grow corn. Or imagine instead of a 3D printer that uses melted plastic in your house, you have something that looks more like a bread maker and you actually grow the products that you want. There are lots of visions here. And I think that we don’t know yet what it’s going to look like.

0:54:41.6 SC: Presumably… Well, so for one thing, I wanna get on the table that as far as you know, no one is putting 5G networks into vaccines or anything like that, right? ‘Cause it sounds very close. [chuckle]

0:54:55.3 ES: No. No, no one is. And the vaccines, the way they are now, are just such a marvel of biotechnology. I’m almost personally offended that you’re almost minimising this achievement by saying that… Not you, but people minimise this achievement.

0:55:17.9 SC: Conspiracy theorists, yeah.

0:55:19.5 ES: At the same time, there’s absolutely nothing wrong with questioning technology. If you don’t question, if you don’t feel like you can ask, then how will you learn?

0:55:26.2 SC: But I presume that fighting disease would be an obvious target for these engineered cells?

0:55:34.0 ES: Absolutely. So there are cellular therapies out there already. You have party therapies, and this idea… So I wanna be clear here that the idea of control is important because that is… In one important way, because that leads to safety. So if you know you have a well-controlled cell, now you can be more confident about selling a cellular product, and you can be more confident that every cell that you sell to someone is going to behave in exactly the way you programmed. So that you’re actually curing someone’s cancer instead of giving them cancer.

0:56:15.3 SC: Kind of important, yes. [chuckle]

0:56:20.2 ES: And we’re used to… I’m gonna go back to an airplane. We’re used to stepping on airplanes and being confident that we’re going to arrive safety. I would love it if we could get to the point where we don’t even think about cellular engineering or engineering biology as separate from just engineering. Because it’s so predictable, it’s so reliable, it’s so robust, it’s so safe, and it’s such an integral part of making people’s lives better. Because that’s what we’re after at the end of the day.

0:56:49.6 SC: Well, as a good example of that, quite a while back, I heard a famous scientist speculate about the possibility that we would be able to engineer cells, mono-cellular organisms that we could release into the atmosphere and they would eat up CO2 to help solve global warming or something like that.

0:57:08.2 SC: Now obviously, there is a problem with the run-away, you don’t wanna get away with all the CO2 in the atmosphere. But beyond diseases in our bodies, is that kind of large-scale engineering something that we could imagine as part of the future of cellular engineering?

0:57:23.4 ES: I think people are imagining that, and there are people out there thinking about how to best bring to bear biotechnologies to any of the big challenges we face collectively, and climate change is of course, one of them. Food security is another, reshoring our supply chains is another. You don’t necessarily need to release cells to get them to gobble up CO2 for you, why not change our bio-manufacturing processes so that they are carbon neutral or carbon negative?

0:58:00.1 ES: Up until now, we’ve been very much unlimited by energy, we’ve been worried about how much energy does it take to manufacture something, but what if we switched our thinking and thought instead about, “Well, how much carbon… What’s the carbon budget of my manufacturing process?”

0:58:13.5 ES: People are engineering plants or trying to figure out better ways of growing plants so that they lock more CO2, for example, in bigger root structures, and so over time they’re sequestered less. There are a lot of ways to think about doing this that don’t necessarily go straight to just blanket the world in it. [chuckle]

0:58:33.2 SC: Okay. And the other potential application that I’ve heard a little bit about, which I wanted you to comment on, is building either little robots or computers out of either DNA or cells. I have my own questions about this, but maybe I’ll let you say, is that one of the things that you can imagine we’re gonna be pursuing?

0:58:55.7 ES: I think that the idea is one that is worthwhile. I don’t know that it’s going to look like computers that we have already. I mean, silicone is very good at what it does, but biology is not silicon. One of the things my lab is working on is we’re building these sensors, but then how do we process that information from the sensor?

0:59:26.4 ES: So up until now, a lot of folks have been working on building logic inside of cells, so that’s very similar to the kinds of logic that your computer is doing. But there are other ways that we know to make computers think. Air quotes again. What if we could put a different kind of information processing inside of cells? Maybe we could…

0:59:50.7 ES: So for example, there are folks who use DNA strand displacement circuits to make neural network-like computations. Could we put that inside of living cells? Maybe we wouldn’t use DNA, maybe we’d use a different kind of unknown thread. There are different ways of thinking about how to put information processing inside of cells.

1:00:14.1 ES: You know, the cells are doing it all the time, so maybe we should start, instead of by trying to jam computers into cells, maybe we should just invite the cell to tea and say, “Cell, tell me about yourself, how are you processing information?”

[chuckle]

1:00:32.1 ES: And this is, this goes back historically to this rift between physics and biology. When I was a young scientist, the physicists were great at going up to biologists and saying, “We’re here to solve it for you.” Well, that’s no way to make friends. [chuckle]

1:00:45.3 SC: No, no. They’re still great at that.

1:00:48.8 ES: And so, I think what we’re seeing now is people coming together and taking a moment to really learn what the other knows, see the value in it, and try to put together the quantitative approaches from physics and engineering with the incredible descriptive knowledge that we find in biology.

1:01:10.2 SC: Well, and something that… One of the reasons why I was questioning this particular goal is because as a physicist, I’m impressed by the fact that the environment inside a cell is so very, very different than the environment that we have in our daily lives or in a computer, right?

1:01:25.3 SC: The thermal motions of molecules are huge compared to other things that are going on. It’s a very noisy, hard to be predictable environment. Does that get in the way of trying to build computer-like things on those scales?

1:01:43.5 ES: You know, I prefer to think of it as a feature instead of a bug. [chuckle]

1:01:45.1 SC: Okay.

1:01:48.1 ES: So, I think you have to be willing to see it not as a liability, but as an asset. So in a previous life, I built small monofluidic staircases and crammed long DNA molecules in very tight confinement at the top of the staircase, and they would walk, basically. They would jiggle around in this environment and they would [1:02:09.8] ____ for weeks, so there’s an entropy gradient for the DNA molecule in this staircase.

1:02:16.0 ES: And they would come out… And we were thinking about, Well, who cares about this? It’s kind of a cool widget, I suppose.” But we were thinking about…

1:02:21.5 SC: So it’s like a slinky going down the staircase?

1:02:25.7 ES: Nano-slinky, absolutely, yeah.

1:02:26.1 SC: Nano-slinky, okay, good.

1:02:30.4 ES: And when I came to engineering biology, I never really lost that vision of molecules moving in ways that seem controlled, but are driven by random processes.

1:02:42.4 SC: Right.

1:02:44.5 ES: Right. And so, how is biology… How are biological systems arranging themselves such that they’re taking full advantage of the biophysics or just the physics, the thermodynamics of what’s happening in their system. Because if I were a cell, I would probably be lazy. I wouldn’t wanna use more energy than I would need, and so I would wanna harness everything that is just gonna happen naturally with minimal effort.

1:03:13.9 ES: So when I think about minimal life, and I know that Jeremy England has also talked about this. So how would I harness the gradients, the various gradients that I’m experiencing anyway, and then only modify those that are worth it to me because they give me some fitness advantage?

1:03:31.8 SC: And in some sense, this is a place where the relationship between energy and information comes to light, right? Even I’ve written papers about this. This is very… A frontier right now, statistical physics, non-equilibrium dynamics. There is some sense in which biological organisms use information to do work, to make things happen.

1:03:57.9 SC: I’ve always been curious and I’ve no strong opinions about when that happens, like at what point do you say, “Oh, this is using information, rather than this is just rolling down a hill in this sort of a mindless way.”? Do you know the answer to that or do you have opinions about it?

1:04:11.7 ES: I love talking about this stuff. Again, I defer to the experts. I would love to sit down and think about different experiments to do. As we think about our capabilities with putting together engineered systems, whether we might use an element of nanotechnology in our experimental design, a little biology, whatever pieces you wanna put together to control the system in a way that you’re able to ask and answer very cleanly some of these questions that you’re posing.

1:04:43.4 ES: I think we just need to find the right people who have the right friends, with all of these expertise together. I don’t know yet what those experiments would look like, but I think they’re coming.

1:04:54.2 SC: Sounds like a good topic for a workshop at the Santa Fe Institute. I might have to propose something like this.

1:05:00.4 ES: Sign me up. [chuckle]

1:05:00.5 ES: Alright. Very, very good. So the last topic I wanted to talk about, unless you wanna put others on the table is, we’ve been talking about cells the whole time, but in fact, I get the impression that a fraction of your research is on the idea of cell-free synthetic biology, like break out of the boundaries of the cellular membrane, but still do biology. So what is that even all about?

1:05:25.9 ES: Great question. I mentioned earlier that you can consider life on a spectrum. So if you have a spectrum with chemistry on one end and full-blown, naturally evolved, let’s say mammalian cell on the other end. A human cell. There’s a lot of space in the middle. So, if we kind of walk along that spectrum, we might find we can go from chemistry to something called a pure system where people have reconstituted certain molecules, and you can get protein expression.

1:05:57.7 ES: If you walk a little further, there are folks who grind up cells or mush them up and get rid of all the spatial organisation and just keep it components in a tube and can express proteins or do other things with that.

1:06:12.8 ES: So you can still do biology, even though you’ve smushed its organisation to smithereens?

1:06:18.3 ES: For example. You can keep walking down that spectrum and you can come to a minimal cell and etcetera, etcetera. But to stop at the cell-free system… It’s such a bad name.

[laughter]

1:06:30.3 ES: There it is. Sometimes they’re called cell-free expression systems or transcription-translation systems, these are all words to go Google. TSTL systems. What’s really nice about them is they allow you to use the machinery of biology without that said system needing to be alive. And so for example, if you’re making a product, you don’t need to figure out how to transport that product outside of the cell across the membrane to then go separate it out and sell it to someone.

1:07:00.3 ES: You can start thinking about doing chemistries that would be lethal to a cell, and the cell-free system might not care. The whole system is open, and so you can literally just stick your pipette in and put more of whatever you want into it. More energy, more molecules, to more [1:07:24.1] ____, or whatever you want. You can just stick it in. People are using cell-free systems as a bio-manufacturing platform for those reasons.

1:07:37.2 ES: Another way people are using cell-free systems is as a stop along the design build-test-learn cycle. It’s a workflow in biology. If you’re engineering biology, that’s one way to think about your workflow. So I might start by saying, “Well, I want a cell that does X, function X.”

1:07:57.8 ES: So I’m gonna design the DNA, I’m gonna order it from the DNA store, it’s gonna come to me, I’m gonna assemble it, and I’m going to put it into a cell. For example, I might put it on a plasmid and subject my cell to a high voltage, such that the membrane breaks down partially, and the DNA goes in. [1:08:17.3] ____ And then, let’s see if we get function X. Well, very often you don’t.

[chuckle]

1:08:26.0 ES: And so, what went wrong? And in the meantime, you’ve been going through this workflow where you’ve been waiting for cells to grow, that takes time. It’s much faster if you can take an intermediate stop and use a self-rate system to just quickly test your DNA. Because it doesn’t have to grow. You’ve got your cell loop in your minus 80 freezer, just pull some of that out, that you’ve made previously, put your DNA in and say, “Well, that does it blow?” or, “Can I do a test that will tell me that I can be reasonably certain this is going to work in vivo, if I test it out first in vitro?”

1:09:08.3 ES: The idea is that it would make your workflow faster because you’re not needing to do everything in cells. Now, we, just like for cells, we don’t have a great understanding of everything that is in that cell-free system often, especially if it’s lysate-based, if you’re making it from the guts of real cells. People are working on it, we do have some good models, but there’s room for improvement.

1:09:43.1 SC: This makes me think about, once again, this origin of life question. Typically, when I wrote my book, The Big Picture: On The Origins Of Life, I repeated what I was told, which is that you need compartmentalisation, reproduction, and metabolism to qualify for life. Compartmentalisation always seemed like the odd one out there, right? I can see what the advantages are, but the necessity was a little bit more obscure. Is it…

1:10:13.3 SC: Following what you said at the beginning of the podcast, that we should be open-minded about other kinds of life, could we imagine that if we go to other planets, life does not happen in cells, but is just more of a continuum that sort of smushes together in interesting ways?

1:10:27.4 ES: I think that’s a wonderful thing to think about. Some folks think that life might have arisen in bots where there are very small chambers. I think there’s also a lot of room in engineering biology for figuring out how to put back in engineered compartmentalisation, or ways where you can gather up molecules of interest in closer proximity, so that they react in ways that are more advantageous for you.

1:10:53.4 ES: That might look like some other really interesting liquid-liquid phase transition work that folks have been doing inside of cells. Other folks are using microfluidic and nanofuidic chips, where you have these very small channels, in glass or silicon, where you’re confining biomolecules, maybe a cell-free system, and looking at how those behave under this engineer confinement.

1:11:24.1 ES: Also, spreading it on a chip gives you an easy way to image, so to measure what’s happening. So I think there are different ways people are going about influencing or engineering back in something like cellular confinement or nanoscale confinement.

1:11:43.3 SC: There’s just too many good things that you dropped in there, in terms of questions we don’t yet know the answer to. I remember once, I told this story before, so maybe it appeared on the podcast. I invited a biologist, Bonnie Bassler, from Princeton, to come to give the physics colloquium at Caltech.

1:12:02.9 SC: She was talking about bacteria and quorum sensing, and my graduate students afterward were just shaking their heads with like, “It’s so easy to find questions we don’t know the answer to in biology, but we can do experiments to try to answer.” In particle physics, as you know, it’s just harder. It’s a more mature field. So I’m very excited about the frontiers that you’re working on.

1:12:24.2 ES: It’s a great time to be in this field. I do wanna mention that as a physicist, I very much grew up in the shadow of some of the physics greats who were involved in bringing about the nuclear age. This is the cautionary tale that we were all taught. I’m hoping, I’m very optimistic that synthetic biologists, engineering biologists, will learn from history and think long and hard, not just about what we could do, but what we should do. And the stakes are so high for us. We have to build trust if we’re going to arrive at a future where we can all thrive.

1:13:07.5 SC: I remember… There’s another story that I’ve often told. I do science consulting for Hollywood, and my wife Jennifer was the director of a consulting organisation. She set up for a movie a bunch of scientists, and they were tasked with, “If we wanted to build a terrible plague, a viral plague that would kill a lot of people, what would we do?” And the scientists came together, they came out going like, “Oh, we could totally do this.” [chuckle]

1:13:35.5 SC: And it is… I think physics has sort of passed that threshold where the research that is going on in fundamental physics now, Higgs bosons, or dark matter, or string theory, or whatever, is not in any danger of being weaponised in any moment. That baton has been passed to fundamental biology, where the number of things that could happen is pretty scary.

1:14:00.4 SC: But I always like to end the podcast on optimistic note, so give us your most optimistic reading of how the future is gonna become better because of synthetic biology and engineering biology?

1:14:10.7 ES: My hope is that our ability to apply bio-technologies to make people’s lives better than… It might look like new kinds of therapeutics. We’ve already seen it in new kinds of vaccines and cellular therapies. I’m hoping that it gives more people more access to ways of making things. You might have heard of the bio-fab movement?

1:14:39.6 SC: No.

[chuckle]

1:14:42.8 ES: So, you have like MakerLabs where people have a lot of tools for working with plastics and metal, electronics. Well, extend that to biological systems as well. At the end of the day, we are biological, and it’s so important for us to make sure that everybody has access to what we need to keep ourselves healthy and happy. Clean air, clean water, nutritious food.

1:15:17.1 ES: There’s so much upside to bio-technologies here. Again, I think that we’re limited by our imaginations. And then after that, how do we wanna prioritise what we could do.

1:15:30.7 SC: Well, it’s clear that…

1:15:33.3 ES: So that it works for everyone.

1:15:33.4 SC: Yeah. Things are happening very, very rapidly. It’s fun to look at the progress in real time. It is important, as you emphasised, to at the same time take a step back and think carefully about whether we’re doing the right thing, as we’re doing all of these fun things. So, Elizabeth Strychalski, thanks so much for being on the Mindscape podcast.

1:15:48.8 ES: Thank you. It’s been great fun.

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