274 | Gizem Gumuskaya on Building Robots from Human Cells

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Sean Carroll

Welcome to the Mindscape podcast. I'm your host, Sean Carroll. You know, there's a lot of excitement these days about artificial intelligence and computers and technology more generally, possibly changing the world in a dramatic way. We talked about that in a recent solo podcast, as well as with other people. But the other thing we mentioned in the solo podcast, the Royal we, of course, me, is biology, because biology has not gone away in its dramatic effects on what we can do to ourselves biologically, not to mention how we can program and build and design biological organisms to do interesting things for us.

The basic idea is that when you. Want to build some technology to either affect things on very, very small scales, or do things very, very delicately or very precisely, or to do them in a biological context within a person, right, to cure diseases, to deliver drugs or something like that, very often Mother Nature has been there first, has figured out a way to do these things that you want to do, and so you don't have to invent from scratch how to do them. DNA and cells and metabolism with mitochondria could always be very, very useful in these precise contexts. So it's very exciting to contemplate what's coming down the road in terms of ways that we can manipulate biology and use biology to help us in a bunch of ways. And a recent breakthrough along exactly those lines is the subject of today's podcast.

Sean Carroll

Gizem Gumishkaya is a researcher who recently got her PhD. She's now a postdoc, and she works in the lab, same lab as Michael Levin, who was on the podcast before. And Gizem's thing is something called anthrobots. This is a subset of something called biobots. Biobots are basically little robot like things, but made out of cells of one form or another.

And as you'll see from the podcast, it's still in a very, very early form. It's not like we have many different pieces that we're designing and putting them together in an intricate way. But the point is, you can take cells, and in the case of anthrobots, you can take human cells and you can sculpt them, you can nudge them into a particular configuration. And then some of them won't do what you want to do, but others will. And you can keep the ones you want and discard the ones you don't want.

And what they can do is pretty amazing. They can heal things inside your body. They could, like we said, deliver drugs. They could be used as sensors to figure out what's going on inside you. And it is just the very beginning of this process.

This is different than DNA, robots, or synthetic biology. When you are designing the genome, this is just using the cells that you already have and putting them together in very interesting ways. So I think that what comes through in this conversation is both that what's already been done is extremely amazing and exciting, and that this is just the beginning, that we're going to be going places with this kind of technology that it's hard to foresee the impact of. But certainly the impacts are going to be big. We do briefly talk on are there any dangers here?

But I think for the most part, the possible impacts here are going to be pretty awesome for humankind. It's a wonderful landscape of opportunities out there, and we're going to be exploring it. I'm very excited. So let's go.

Izam Gumeshkaya, welcome to the Winescape podcast. Thanks so much for having me. It's so exciting to be here. Let's just start with the very big picture here so that people know sort of how to orient themselves. What are you doing?

Like, how do you think of your task or your project biologically? Is it designing better robots, or is it manipulating life, or what is your self conception there? I think there are a couple different layers. Two big layers are, well, science and engineering. So number one goal is really engineering new systems by leveraging what nature has to offer in terms of us being able to create new types of structures and living architectures that are not necessarily evolved, but designed by us pushing the boundaries of what we can do in terms of harnessing nature's unique properties when it comes to construction.

Gizem Gumuskaya

So this is like regeneration, healing, replication of constituent building blocks, self construction, ability to sense and respond, the environment. These are all really amazing properties we would love to have in artificial structures, but they have been so far exclusively reserved to natural structures. So bringing those hallmarks into engineering through synthetic morphogenesis is sort of the first layer. And then in doing that, in the second scientific layer, we're understanding how morphogenesis happens in nature, how these amazing structures arise in nature in the first place, what are the rules there? What are the knobs we can turn?

So understanding system to create new things with it. So really those are the two legs of this pursuit of synthetic morphogenesis. Well, you use the phrase synthetic morphogenesis, which I think we're going to have to define. Probably I can figure out what synthetic is genesis. Probably morpho is shape.

Sean Carroll

But what do you have in mind? So it's really starting with the concept of morphogenesis, which is this amazing thing that happens in nature, basically developmental form in nature. This process of a single cell building itself into this functional multicellular organism. The process of morphogenesis is seen across all kingdoms, essentially from simple biofilms, like a single bacterium giving rise to self replicating, giving rise to this amazing biofilm all the way up to higher order mammals. So, it is the development of form in nature, the business of morphogenesis.

Gizem Gumuskaya

And the synthetic part is, well, as I sort of unpacked at the beginning, understanding how this happened and then steering it into new ends. So it's really bringing this goal oriented design, which is something that does not exist in nature. It is a human construct merging that with this sort of trial and error and bottom up construction that nature uniquely reserves, bringing the two together to have nature build itself into and designed by us humans. So I have very long thought, and I'm sure that I've said this many times on the podcast before, that nature has a huge, obvious advantage over technology, because usually when we build things technologically, we build them out of metal or whatever is the minimal thing to do, the shape we want to do. And as a result, the things are very brittle.

Sean Carroll

Like, if my car breaks down, I have to take it to someone to fix it. It doesn't fix itself, or as nature has the job of fixing itself. So, in that sense, it's kind of an obvious place to look to build better things, to sort of piggyback off what nature does, right? Yeah, absolutely. And I think why?

Gizem Gumuskaya

This hasn't really been accessible to us. I mean, we all admire nature, right? That's the sort of genesis of science, trying to understand nature, trying to understand how all these processes happen. And it really looked to us like magic, because it has this magical quality due to its bottom up sort of nature, but sort of for the first time, really, in science, in history of science, we are really trying to understand now, what's the logic behind that magic? And, you know, we've had the genetic code sort of started being sketched out in the 20th century.

So what we are really doing in the 21st century is looking at that and understanding that systemics behind it and then essentially recoding it in order to still retain those magical qualities that only nature has to offer, like self construction, regeneration, but bring sort of that engineering, coding mindset and trying to get it to do something specific. And biobots are just sort of the first example or one of the examples of where we can take this. And I could imagine that somebody could just take inspiration from nature, but more or less design from the ground up, maybe. That's very hard, and you don't want to waste all your time rediscovering things, but if I understand correctly, what you're doing is literally starting with cells and pushing them around to make robots. Yes, that's an excellent distinction, and one I actually tried to clarify often in my sort of explanation of what we're doing.

So there is in being inspired by nature, and that is something we've been doing for hundreds of years, literally since the ancient times, right? Looking at nature, admiring it, building architectures like ionic columns that look like nature. But in doing that, we are still exclusively using the top down methods that us humans have developed, where everything needs to be manipulated one by one, sort of. It lacks that autonomy. And still, to this day, in the 21st century, we're doing things like this.

I mean, a lot of sort of in biodesign, there is sort of like molding things, or even 3d printing, to a degree, is just sort of a contemporary version of that. You know, building things top down in order to approximate the final product, to sort of what we might be observing in nature. But what we are saying. Excuse me, what we are saying is, let's take some of what we have developed as humans, again, goal oriented thinking, all the sort of engineering principles of modularity, robustness, and marry that to what nature uniquely has to offer, mainly self construction. So, yeah, I am literally working with cells and recognizing that in those cells, there actually exists a morphogenetic code that we can work with and that is amenable to human design.

So I think just that combination of the two is really sort of a nascent field and is going to go to really exciting places. Okay, let's be more specific about this biobot idea that you've already mentioned. Apparently, the earlier thing, before we get to your particular anthrobots, there were xenobots. And again, if we have a classical education, we can probably figure out what those mean a little bit. But tell us about the xenobots, if you can.

Yeah, so xenobots were the sort of first fully cellular biological robots, as we call them. So, prior to this, the field of biobots existed. A lot of what was being done in the field, though, is precisely what we're talking about. Sort of a hybrid between sort of gels or scaffolds or things that could support the cells. And then on top of that, you can add cells in order to sort of optogenically induce them or harness some of the biological qualities.

So they were sort of hybrid biobots with xenobots, which were developed in my patient advisors, Michael Levin's laboratory, in collaboration with Josh Bongard's lab in University of Vermont. By Sam Krigman and Doug Blackiston. Xenobots were the first fully cellular biological mass. There is no scaffold, no support. It is created using frog embryos, by extracting tissue from frog embryos, and by surgically manipulating.

So there is still that top down manipulation aspect. It's not quite self construction, but it's sort of one step forward in my definition of where we're trying to go, which is quite literally building self constructing robots and structures. So it was definitely one step forward in that axis. And how they are built is that cells are extracted from frog embryos and sculpted into spheroids with cilia covering their surface. And it was discovered that these xenobots are able to sort of move around in different patterns and able to do useful work, like aggregating loose cells.

And it was really exciting because now we're, you know, with that work, it was really sort of in the field of biobots, we were able to see that we don't need any type of inner materials. We can use only nature, and we can work with it to get it to sort of show up as a new architecture. These were stem cells they were starting with, I think. And so maybe you should tell us what a stem cell is and why that mattered. Right.

So these cells were from frog embryos, of frog embryonic stem cells. And why stem cells are important here is because stem cells have huge potency in terms of the different types of tissues and structures they can become. So they have a high degree of anatomical plasticity, as we call it. What that means is that a cell or a tissue's ability to become different things. For example, as a adult, your morphology is locked in, I think.

Sean Carroll

So, yeah. You don't really have a ton of plasticity, but at the sort of embryonic state that adult adult grows. So that adult has a lot of different tissues. And every single cell in that adult's body is coming from one original cell. So every single cell in the body is sharing the exact same DNA, but they have all different kinds of properties.

Gizem Gumuskaya

So our cells in our eyes and our kidney have the exact same genetic makeup in terms of DNA, but have completely different functionalities, shapes. Well, this is because that original cell in the embryo had a huge degree of sort of morphological plasticity. It could become a lot of different things. And during the process of morphogenesis, through differentiation, as cells self replicate, one becomes arm, one becomes leg, one becomes hair, one becomes skin. So there is that ability to become different things in embryonic stem cells.

And in xenobots, they have essentially leveraged that in order to build new architecture that has a completely different shape. And function than that of a frog embryo. So that was sort of really exciting to see. Want to know one of my favorite sounds? Here it is.

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Get up to 60% off@babbel.com. Mindscapes spelled babbel.com mindscape. Rules and restrictions may apply. And you use the word or the phrase sculptor cells. And I would like to know what that means.

Sean Carroll

Are you sculpting individual cells? Are you sculpting how they fit together? And how does one sculpt at the level of cells? Right. So it's sculpting a multicellular tissue, sculpting an aggregate of cells.

Gizem Gumuskaya

It is a very fine surgical operation that our surgical genius in the lab, Doug Bleckiston, is able to sort of put together. I myself, I'm obsessed with self organization, so I actually don't do any sculpting. And if you gave those styles to me, I cannot make you a xenobot. But, yeah, Doug has a really sort of fine hand, as you call it, and he was able to put together, and he has these really beautiful videos. I encourage listeners to go look them up for how he builds them, and he can also build them in all kinds of different shapes, different sort of protrusions and inlets.

Essentially. It is very much like sculpting, very much like kind of almost like playing with dough and giving it into both scalpel and under a microscope, but giving it the shape that you want it to have. So it has that advantage. The collection of cells this shape, or you're literally shaping an individual cell. No, it's a collection of cells.

You're shaping a multicellular aggregate okay, very good. And so you in the xenobots, anyway, you basically are nudging the stem cells together to make specific shape. Do you do any more than that? Do you edit the DNA or give it chemicals? Or how do you make it a bunch of cells into a biobot?

Right? So in that case, they also supply the system with different inputs. I believe they use a notch inhibitor. And so they have a matrix in the 2021 paper, I believe it is. And based on the different environmental inputs you give to the system, it is able to sort of acquire different shapes and properties.

They haven't really edited the sort of DNA or integrated different genes to make xenobot. Once you have your xenobot and same thing with anthrobots, you can use it as a platform to add in different genes. So it is still very much, and I think we should get to this, different approaches to synthetic morphogenesis and genetic circuit approach versus this more morphological, anatomical plasticity approach. The two are complementary. So once you have your Biobot platform, you can still add genetic circuits, which has been the predominant approach in synthetic biology so far.

And they have done this, too, in xenobots. They added an optogenetic receptor that enabled them to communicate with xenobots through light. And I believe that's also in the second or third paper.

But to make is, you know, but you do not need genetic circus or you do not need to change the DNA. Okay, very, very good. And one sort of quasi philosophical question before we jump into the anthrobots in particular. So this is like, this biobot is a new kind of thing. It's not an organism, but it's not a robot either, right?

Sean Carroll

I mean, has anyone, maybe philosophers or maybe someone else, sort of opened their eyes and said, oh, my goodness, you've created not just a new thing, but a new kind of thing. I don't quite know if it's a new kind of organism, because, I mean, this kind of goes into, like, how do you define organism all the way down to how do you define life? I think it's more like expanding the sort of palettes of stable morphologies that we can create using things that we call nature. Right. Using cells that are evolved.

Gizem Gumuskaya

We did not build those frog embryos. They are natural in that sense. But by using them, we're able to create a stable, fully cellular, morphological steady state structure. So it's, you know, I don't think it's a new organism quite. And maybe that's not even, like, the useful question to ask, but in terms of why they are robots.

In general, I think the field of biobots is using the term robot, maybe not with the utmost rigor. I think, in general, starting with earlier hybrid biobots, xenobots, anthrobots call them robots, because there is some degree of programmability. So programmable anatomy, I think, is sort of the justifying factor there to call it robot. But they're definitely. There is a lot of side discussion going on for terminology and how should we refer to them.

Mike has a whole blog post about this. I also encourage readers to check out his blog. Read on that if that's of personal interest. But the biobots, at least so far, do not reproduce themselves, right? There's no natural selection going on just within the biobots?

Correct. So, for xenobots, for paper number three, what they have done is to show that these xenobots that move around so far mindlessly, because we haven't really seen otherwise, so doesn't mean they can't be. It's just we haven't seen otherwise collected cells together, sort of aggregated individual cells that are sort of free floating in the dish. And they were able to show that these cellular aggregates themselves were able to then move around, because they also have cilia on their surface. And this went on for three generations.

So in that sense, I think they, you know, there is a kinematic software application, although that is that sort of like, reminds me of, you know, machines that make sort of 3d printers that print parts for more 3d printers. So, you know, bots aggregating cells to create aggregating bots that aggregate cells. So it's kind of that, like, recursive nature of it, maybe, is what making it look like software application, but sort of that's the. I think we've dipped our toe on the software application water in that way with xenobots, but not with antrobots. Anthrobots, they can aggregate cells together like xenobots, however, because they're sort of modus operandi, is not through aggregation, but through self construction, that aggregation itself doesn't create a new anthrobot, or.

We're not making that claim. Okay, I think it's probably then, time to tell the audience what an anthrobot is. A xenobot. The xenobot experiments, we'll link to papers in the blog post, but they were made of stem cells from a certain type of frog. The anthropots.

Sean Carroll

You just dig up little cells from human beings. Yeah. So not from embryos. Spoiler alert. So, yeah, so when I started in the lab, 2018.

Gizem Gumuskaya

We wanted to make mammalian versions of these xenobots. However, it is not. So two major differences, like, difference. Number one, you cannot just take, you know, and we ideally want to make these from human cells because we're interested in using these in medicine, potentially. So you can't just take human embryos and, you know, pick cells and, like, play with them and then put them together and see what they do.

Like, that is just not gonna happen. And even if that was allowed, I actually personally think there is a lot of merits in trying to get these bots to build themselves from single cells, to sort of recapitulate, like, go even one step further, not just use fully biological cells, but also have them bring to the table what they can uniquely do. So I can sculpt a lot of different things, but I can't make anything build itself unless it's of biological substance. And just to be clear, when you say that you can't do that, you're legally not allowed to do that. Take little human embryos and sculpt them.

Exactly. Poke rand. I mean, I think up until day 14, I believe, is allowed not to poke them, but to run experiments. But beyond a certain sort of legally defined threshold, you are obliged to shut down the experiments. And, yeah, so it is more like a legality and ethical issue rather than science.

I mean, there is no reason why you can't take cells from anywhere, and there's no reason why you can't physically do that. But, yeah, that's just not something that is done. And even then, I think that, as I said, like sculpting, we just want to try a new construction modality. So. And I mentioned at the beginning, I do have a background in architecture, so I actually came to synthetic biology from architecture, civil engineering space, in order to sort of explore some of these potentials that biological systems have in terms of how they build everything we see in and around us.

So the idea of getting cells to build themselves was really interesting. I think this is where, like, this is a really good case study, actually, for synthetic morphogenesis, because sort of the building of anthrobots, because our really first step was, what is our goal? What is our end? Morphology, which is a very much engineering problem. Right.

Like, or even in design. Like, you just start with, what do I want to see in the final system? What are my design requirements? So, for anthrobots, the list of design requirements is as follows. Essentially, in terms of structure, we wanted to basically replicate xenobots, so we already have a target structure right there, a spheroid bicylia on the surface so they can move around.

Or actually, that was another thing we were. So this is the side of that tension between science and engineering, right? Like, this is a very much engineering goal. I want to make a multicellular spheroid with cilia on the surface from, you know, human cells, because I want to make these bots that move around and that I can put into human body. This is all.

We're very completely talking about engineering here. But there's also this sort of underlying scientific question. Well, if I create a multicellular structure that looks exactly like a multicellular structure that is from a completely different kingdom. Right, from amphibians. Okay, will it move?

Will it do the same thing? What will the similarities be? What will the differences be? I mean, this is also sort of anthropots versus xenobots, and there are some minor differences, like anthropocene, smaller we can get into later, but essentially, in terms of their morphology, they're kind of like twins. They're both spheroids, multicellular spheroids with cilia on the surface.

And I don't think we've ever seen in the sort of history of life on this planet where two multicellular structures, or two structures of any kind looking so similar to one another, but from being completely different kingdoms. So recreating that in the lab and investigating their behavioral and morphological properties also, I think, really helped. It was a really exciting question and sort of really helped us understand some of these, like, morphogenetic rules that we are trying to crack. So this is just kind of an example for science engineering tension, but going through the list of requirements when we're building, so, metastatic spirits on the surface, human cells, and then self constructing. So we have our sort of target goal, right?

Target engineering goal, and we want to get cells to build this. So how do we go from here as a sort of synthetic morphogenesis project? So the traditional way to approach this project would be through synthetic circuits, which is sort of the dominant modality that is currently used in synthetic biology. What that end? It's fascinating.

Learning about synthetic circuits and finding out that we can do these things was the thing that sort of brought. Sucked me into biology from design to bring the two together. So it was, like, massively inspiring, but I was also realizing that maybe it was sort of coming to its limits. So with antrobots, then we have our list of goals, which is what any sort of engineering project starts. Where am I trying to get to?

And this is not how nature does it? Right. Nature is just trial and error across millions of years brings about something that works. But for us, grand timelines are not millions of years. So we do need to get to what we are trying to build, hopefully in the span of a PhD.

So, starting point, okay, we want spheroids, we want spirits covered with cilia, we want these from human cells, and we want these to build themselves. With that goal list in mind, if a synthetic biologist sits down for a synthetic morphogenesis project, traditionally what we do, and this is something in my work, in my master's prior to PhD, this is also the space where I learned all my synthetic biology knowledge is through synthetic circuits. So I'll just pause here and unpack a little bit what synthetic circuits are. So, synthetic circuits are very much like electrical circuits. Instead of though having transistors connect to one another with copper wires, you essentially have genes connect with one another through sort of proverbially chemical wires, you have this one gene getting expressed, and that could be a regulatory protein that goes and turns on or off another gene.

And so through these interactions, you can generate boolean logic in live cells. And that is a very much sort of electrical engineering sort of paradigm, bringing this to biology. So in the past, there has been some amazing examples of, for synthetic morphogenesis, creating synthetic patterns in space. A lot of things have been accomplished through genetic circuits. However, though, if you want to create something, sort of, these all have been in 2d or 3d fields.

So it has not quite yet gone beyond just creating patterns. And I don't want to say just because even that's like, fascinating getting cells to create large scale patterns, but if you want to do something quite large, as a multicellular spheroid, with function, so growing cilia on the surface and moving in one direction, which means there is a symmetry breaking event going on, there is directionality, there is axes. This is just not something we're going to yet be able to accomplish using just genetic circuits. Because even. Even if you can fathom what kind of a circuit would create this type of incredibly complex tissue organization event for us to build that circuit and deliver it into cells, just our technology is not there yet.

And, you know, biology community is a really fast moving community. So I think we'll get there in 50 years. Hopefully. My lifetime would love, like, love that idea of designing a structure and then compiling it into a genetic circuit and putting it into a single cell, and have that cell execute that circuit and start self replicating itself, proliferate into that structure, very much like the growth of a tree, and in doing that, also sort of copy those instructions that we've put in there and propagated into the progeny. So everybody knows what we're trying to build.

I mean, that is, I think, really the sort of hundred year view of synthetic morphogenesis. But we're not there yet, and I did have to get my PhD. So basically, we started thinking about, is there another approach to synthetic morphogenesis that we can think about? Why are we trying to build everything from scratch? We don't even yet understand fully how coelogenesis happens in nature.

Incredibly complex process. The pathways are not all even worked out. How are we going to take this and put into a sort of synthetic circuit? Now, why don't we just look at cells that already know how to make cilia? So instead of, just, by the way, the cilia, the little hairs that move around the right kind of cell.

Right, exactly. So cilia, little hair is exactly like they're in our. So there are three places in the body where cilia is found. So you have the mucosiliary escalator, which is in the trachea, that helps inhaled pathogens and particles to be sent back up. You have it in the brain ventrices, and then you also have it in the oviductal epithelia, helping egg to move around.

It is essentially locomotive appendage, one of the locomotive appendages. There are different ways of locomotion in the body. So very fascinating, very complex. Then, really, this new approach to synthetic morphogenesis is asking the question, can we leverage what cells already know how to do and have them do as much of the help them deliver as much of the final engineering goals as possible, and then, without really interfering at the genomic level, only by sort of engineering their environments, nudge them, so to speak, towards the designed goal. So this is really a shift from looking at how morphology develops in nature.

I think the traditional view is very sort of gene centric, and this is something Mike's lab has been working on for a very long time. The traditional view is everything is encoded in the genome. I mean, if you read my work prior to anthropots, it's also very much like, okay, with Geneva editing, how are we building this? And so the PhD has really sort of gave me the room to think about this sort of more extensively, and really started realizing that the morphogenetic code encompasses more than just the genetics. It also has these added layers of environment and epigenetics.

And by changing things, tuning things at these levels we can also change the final morphology. Mike has this fascinating work, double headed worm. So he took a worm. This is years before I joined the lab. If you cut the head, head grows.

If you cut the tail, tail grows. So they cut the head and changed a sort of bioelectrical signature at the cut point and managed to get a tail grow instead. So you have two tailed worms and two headed worms. And there are a bunch of different examples like this where by just changing the environmental inputs you can change the morphology. So for then building anthrobots, we've asked the question which cells in the human body already know how to make cilia?

So we can go with brain cells, we can go with tracheal cells, we can go with ovidactyl epithelium. We've just decided to go with cells from trachea because cells just more available, more widespread research on lung diseases started with a single cell from the epithelium NHB's and looked at different ways to get these cells to create cilia. Already there are protocols out there for getting slated epithelium to build itself so we can study. And this is again where sort of science and engineering is splitting up in science we just want to create these things so we can better study and better understand the native tissues. So the goal is really sort of in the field of organoids, the goal is to recapitulate tissue architecture.

We don't want multisylated spheroids running around because that doesn't look anything like what's in the human body. So there wasn't anything.

So basically just kind of like looking at what type of culture methods are available. So there was one really interesting culture method that helped these cells to grow into spheroids. But cilia is looking inside. So this is a traditional airway organoid method. We take cells from human trachea, culture them in an environment with a dense matrix, and then they grow something that's very similar to what's seen in the human body, this lumen with cilia lining it.

So that's great, except that's the exact opposite of what we're trying to do. Cilia is looking, it's a spheroid with cilia inside. We're like, no, this is not going to move around, you know, spread visually outside, but look at how close we are. I mean, I think that's why it's really powerful to look at what these cells can do on their own readily before kind of like jumping on genetic circuits and trying to build it from scratch. Can I ask just very quickly, when you say spheroid, we have this collection of cells we're talking about, like, I don't know, 100 cells maybe?

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Gizem Gumuskaya

So, yeah, a very varying number, but, yeah, from hundred, it could be. It could go up to thousands, but in the order of, like, hundreds. Yes. And the spheroid is empty inside. It's just the container.

Sean Carroll

It's not. Or just the shell, I suppose. It's not a solid ball. Exactly. So it is very much like the trachea.

Gizem Gumuskaya

It's a empty inside. There's a lumen, and it's filled with sort of mucus and other debris that the cilia is sort of moving around.

Some of them quite literally looks like a washing machine with, like, a empty hole. And then things are moving around there. So this was something that was. So it's basically like, the first step is to. Okay, here's my engineering goal.

Here are the things I need in my system. What already exists out there that does something similar to this, and then how can I not just in different ways, sort of explore all the different shapes and structures it can create? So I sort of, like, push it towards my engineering goal. So, with, again, as an example for antrobots, we had the array organoids. So we need to get these guys to flip.

I think this is where thinking about cells and their morphogenetic functions, what they like, what they don't like, what environmental inputs. It's known that the cilia grows in the middle and not on the surface, because the surface is this thick matrix environment. And Cilia likes to be closer to more phase, more water like environment, and that's that empty lumen or, like, filled with mucus. So, essentially, I mean, trying a bunch of different things. But the hypothesis that worked was that, okay, what if, once we have these cilia in airway organoids, if you remove the matrix from the environment, if you just melt it out, I mean, I say just.

But even this is like five months of research because you're like, okay, yeah, I know. How do I get just the matrix to dissolve, but keep the cells intact? And, like, ultimately developed a way to dissolve the matrix and keep the spheres intact, and when we put them then into a non adhesive environment, so not just in an especially non sticky environment, to really force those ciliated cells to come outside while bombarding the system with retinoic acid, which is also something cells known to kind of really thrive on. In a matter of seven days, I managed to get these spheroids to essentially flip inside out, which is really fascinating because that almost looks like gastrulation, which is an embryonic event, but unfolding in a structure that has nothing to do with the embryo literally taking from elderly patients. Again, just to be clear, you have this spheroidal collection of tracheal cells, and all the cilia want to be inside.

Sean Carroll

And you didn't convince the individual cells to get cilia outside. You just convinced the whole sphere to flip inside out. Exactly. Undergo this phenomenon called eversion, essentially what a bioengineer does at that point. Okay, here's my engineering goal.

Gizem Gumuskaya

Here's what's already available to me. Here are the kinds of structures that are either developed by evolution, meaning these are the natural structures available to me, or by other scientists. So, like the airway organoid. So a survey of what's out there, and then from there, finding the closest point to where you're trying to go and then asking, you know, not, we're not messing with the. We're not going sculpting, trying to get it inside out, like by hand.

None of that. Those are all sort of like very much top down construction methods, but asking ourselves, what kind of morphogenic functions can I get these cells to engage in? What kind of functions can I execute in their morphogenetic code? So I get the system to build itself towards my target morphology and the morphogenetic function there was. Eversion is the sort of terminological name to get it to flip inside out.

And then you sort of do a bunch of things to the spheroids to get them to do that. And then you have a really. Yes, developing the protocol is very painstaking, but once you've done it, then you have the system that. So antibodies build themselves in the matter of, like two weeks from single cells to multicellular structures, and then one more week for an mtFlip. So three weeks.

And in this, like, in the course of these three weeks, we just feed them twice and then essentially, like, melt out the matrix. So, like, change your diaper.

And we go from thousands of cells to thousands of pots. I mean, there are, like, thousands of them just, like, running around. And that's the, I think, like, real beauty of self construction. Beyond that, sort of like, intellectual bleeding edge, you know, trying to that, like, architect side of me. Beyond that, it's just very economical, like, high throughput.

Right. You just do the same. So it's not like 3d printing. When you're 3d print, you have to print them one by one. It's not like molding or casting.

You have to, like, create individual molds for each thing you're trying to. So I think that's why it's really exciting to sort of ask the question of, can we really get this unique construction framework of biology to work for us towards our design ends? So you have these multicellular collections, and you've nudged them. You nudge them chemically, not mechanically, to make sure that they can move around. They have Cilia outside, but they're not.

Sean Carroll

Just to be fair, they're not programmed to do any particular thing. Right. I mean, they're not robots that you sort of designed for a purpose. You made them to fulfill some requirements, and then you're gonna, like, watch them go and see what happens. Right?

Gizem Gumuskaya

Like, the goal there is to make a spheroid that moves around like that in and of itself. And you can kind of argue that you program the system to reach that goal. So that, like, program. I think that, like, creating artificial anatomy part is the. Yeah.

Is the reason why, like, in general, people call these structures robots. But. But here's the interesting thing. Or. Sorry, was there a question at the end of that?

Or. I'm just trying to make sure that the audience understands, like, what the current capabilities are. Like, this is not a robot that has a computer memory that you can give it instructions to. You've basically built a thing and are sort of just doing science on it, asking how it moves around and what functions it could possibly serve. Yeah.

And I think that's a really exciting thing. Like, when you do that with biology by leveraging sort of this, like, emerging dynamics, because in the traditional way, you would just expect that. Okay, now I have these spirits that move around, do this. One thing that I wanted to do, except that what we saw is that they're all doing different things. Like, what is moving in circles, when is going shape, one is wiggling in place.

One is making arcs. And I think there sort of lies the cue to further programmability. If each one of these guys are doing something different, there must be something categorically different about them. Or is there? I mean, that really became the next question for us, because you look at that dish, you made the mistake of getting them to self construct.

So now you have thousands of them, and it's overwhelming, and you want to characterize the system. So what we did is to ask the question, like, are there any emergent patterns here? Are there cues to like? Because all we wanted to do was to make these things kind of move around so they can go through live tissues and sort of see what they can do. Like, that was the degree of control we wanted to have.

But then now we are seeing they're all doing different things, and now we want to understand, well, what are the differences between these different bots here? And the first thing we did was to do, like, a large scale time lapse and look at the world population. This is, again, really interesting. So when you look at. So biology, does this.

This idea of, like, variation on a theme? Yes. They're all ciliated, they're all multicellular. So they all look like each other, but none two bots are the same and sort of like fingerprints, right? They all kind of look similar, but none two are the same.

And turns out, actually, FBI has a whole way to categorize fingerprints, so each one has a fingerprint type. I believe there are eight categories we can double check, but, like, so really on their website. So I'm like, wow, like, this idea of character formation. So are there different categories in how these bots move? Was sort of the first question.

We collected this mass time lapse data and tracked them and added a PCA. So shout out to Simon Garnier from New Jersey instead of technology. He helped us a lot with the stats on this, and my student, Pranjul Srirastava. So the three of us really sort of tackled this question of, can we find categories here? And turns out there are four statistically significant, distinct categories in this sort of chaotic system.

You have bots that go in circles. You have bots that go straight. You have bots that go in arcs, and then you have bots that are sort of, like, random and eclectic and just kind of noise. So that was really interesting, because now sort of getting to that question, right? Like, okay, well, what else can we tune during their developmental trajectory that we can now start to sort of program the population to maybe always go in circles.

Always go in straight lines. Or, like, do 50 50. So what are the engineering knobs in the system. Um, and our sort of first, uh, hypothesis was, well, it's got to be about morphology, because we know that in nature. Well, in architecture school, they tell you form follows function in in in biology, I learned, uh, function follows form in nature.

So if these functions are different, uh, something's gonna be different about their form. So then, uh, we did something. Whoever, you know, people who work with confocal microscopy will understand something heroic, 3d scanned, like 300 anthro bots. So with the confocal microscopy, we basically shoot the tissue with lasers to create a 3d reconstruction without really harming the bots themselves. So shout out to Ben Cooper and Hannah Lesser, two of my students.

So we've tackled that problem next and then created this massive data pool of all different anthrobots and then collected also motility data from a subset. So what they enabled us to do is actually the next thing. But with this morphology pool, we ask the same question, are there stable patterns? And it turns out there are three stable categories, like three different flavors of anthrobots. You have these bots that are a little smaller and cilia everywhere, like fully ciliated, and you have these other bots that are larger and sort of like a patchwork cilia.

And then you have this third category, again, larger, but only cilia on one side and not the other. And we keep getting these sort of frequencies, the same frequency in the population. So it's really cool that the system is self organizing into different attractor states in terms of its morphology and its behavior. And then next, a million dollar question. Is there a correlation between the two?

Like, can we map the frame? Not necessarily causation, but at least correlation, because from there you can hypothesize about causation. But is there any correlation between, and turns out the ones that are sort of house related, health bold are the ones that always go in circles, ones that are large and sort of patchwork, right? Like if you have a rowboat, and then if you're only roaming on one side, you're going to go in circles. If you're sitting in a robot and have both sides of roaming, you're going to go straight.

So these larger bots with patchwork cilia, sort of checkerboard pattern, always go straight. And then the small guys, even though they have cilia all around in their surface, actually are the ones that are wigglers. They don't really go anywhere because their surface is not large enough to have enough many cilia to generate thrust. So, yeah, I mean, once we kind of figured out that there is a correlative mapping between morphology and shape. I think sort of that's where the future efforts to program will flow, because now you can kind of nudge your system to go one way or the other.

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Sean Carroll

Ctmobile.com dot and because I'm sure that the audience cares about this, the anthrobots, they don't reproduce, and they have a finite lifespan, right? They're not going to take over the world. Probably, no. Probably no. So I have yet to see it.

Gizem Gumuskaya

I have seen like thousands and thousands and thousands of anthrobots. It could be more than like 20,000 now. Never seen one that never disintegrated. So every single time they disintegrate into individual cells after sort of a month, five weeks to two months period. So that differs from bot to bot.

And basically, it would just sort of, if we are talking about inoculating these bots into the human body, after a certain time, they would just disintegrate and get sort of, wouldn't be the different end of the brain in your body. We're characterizing right now in a follow up paper for their modes of disintegration. But, yeah, but nevertheless, we're sort of burying the lead here because even though the anthrobots just sort of wander off in different directions and move in different ways, you found that they did have a potentially beneficial effect on nerve cells. Right. So once we did this characterization, I was like, okay, well, we build the thing.

We want to build, let's put it, you know, let's do it like we then did. The whole reason why we wanted to use human cells was so that we can put these things into human tissues and then see if, well, what do they do? If they can sort of, at the very least, go through the tissue, sort of traverse, not navigate, but like, move across. So we put these into human cortical, neuronal, monolayer differentiated tissues. So these are neuronal tissues or monolayer tissues differentiated from human induced neural stem cells.

HNSC. After differentiation, we basically make a scratch, so damage the tissue in different ways, the scratch assets standard. And when we put the bots on there, we saw not only that bots moved across, but that the bots that had different motility profiles moved across differently. So the bots that had circular tendencies tended to sort of explore the edges of the scratch more, and the bots that had sort of more straight tendencies just kind of went right through. So you can imagine, like a scenario where, based on your application, if you want your bot to, for example, dispense a drug, like high doses of a specific drug in a particular tissue, maybe you're going to want to use your circular bot, so they spend more time there.

Or if you want sort of larger coverage, like, if you want these bots, like patrol, patrol the tissue and collect information a certain way, maybe we're going to want to use the linear bots. So it's also sort of useful in terms of application beyond just like morphological characterization. And then, yeah, when we put the bots into scratches, they just went right through. However, in parallel, we were experimenting with, like, can we make larger structures using these bots? And we had discovered that at a very specific point.

So when you first dissolve these from the matrix before they evert, before they go inside out, if you constrain them a lot, they actually start to fuse together and form this, like, massive bot. And then that bot then actually continues local eversion at different points and then becomes motile. So you can have these, like, very large kind of superbots that are motile. So when we put these things into the scratches, they didn't, of course, move quite as well because they're giants. They're not like the small guys that just go right across.

But what they did was to function as a bridge on both sides of the scratch. So sort of connecting the two sides of the t shirt. And then what we saw is that at the end of a three day period, they enabled the neurons underneath to sort of fix themselves. We don't know if it's like neurons. Most likely explanation is that there is some migration event happening, and that gap is sort of closing in that way.

And now migration event might be either due to Selton release from the bots or due to some sort of, like, electrical transport. We have different hypotheses that we're testing, so we don't know why they are fixing this tissue, the neurons, but we know that when we put another type of, I don't know, like a heck cluster, like a spheroid made from this kind of like, hex cells, which are very off the shelf, we've tried that and we didn't see the same effect, so. And we also just try. So that's controlling for different tissue types. And then we've also just put a piece of agarose and also didn't see the same effect.

So it's also not just mechanical loading.

Yeah, we're investigating the mechanisms, but that was very surprising. Some spheroids that could move around and without even trying to program it too much, they went in and started to heal some neurons, which is pretty promising for what happens when we get better at it. Yeah, I mean, I think that's why the idea of anatomical plasticity and trying to leverage what cells already might be doing is very exciting. And this is a complementary approach to synthetic biology. So from here, we can now add synthetic circuits to these bots, and now we have the room for the payload, because we're not using any of that circuit budget on trying to get them to create this morphology and function.

So I think a really exciting next step is to put different geometric circuits into these bots and see how we might be able to expand their abilities. So, basically, rather than trying to program the bots, you can program something using synthetic biology or whatever. And the bots are just easy to make and are, I don't want to say smart enough, but able to find and locate certain features in the body where you want to dump your payload. Right. I think finding where they go.

So that gets into navigation. I think, actually, that's where we might really make use of genetic circuits, because right now their movement is random. We did very little chemotaxis studies to see if they have an toxic behavior towards anything. So we want to expand those to see if they naturally gravitate towards anything. But, yeah, I think navigation and actuation will be the areas where we can now incorporate genetic circuits and really expand the abilities of sort of morphogenetic engineering as a whole.

Sean Carroll

Is this is where your architectural background comes in and you try to fit different pieces together to do fun things. Yeah. So I think, like, number one is to try to see how we can create new ways of building. New ways of creating structures. Because in architecture, it's all top down.

Gizem Gumuskaya

You have to stack the bricks to build the thing. But here we actually have this technology just sitting out there, nature, where the bricks are self replicating and stacking themselves. It's just a question of speaking their language to get them to build the thing that we want them to build. That's one, then, really. I'm also interested.

Obviously, medical applications are one avenue, but I'm also really interested in climate tech, whether we can use biological, sort of self construction and morphogenetic engineering towards building more sustainable building blocks. Because right now, close to half of all greenhouse gases causing global warming is coming from construction industry. Just humans trying to build things, versus you have this national paradigm that builds amazing things and sequesters carbon, and now we can get it to build the things that we want built. I think there's a great opportunity there for sustainability as well. That sounds very good.

Sean Carroll

I suspect that you would have told me if you thought that it was going to be able to cure cancer, but it does sound like there's therapeutic medical applications as well. Right, right. So neurodegenerative, sort of, you know, diseases are, I think, one area where we could start testing this sort of healing behavior and see in actual disease models what happens. But. Right.

Gizem Gumuskaya

So, beyond that, I think this is sort of more like a. And this is. It's not just answer bots. I mean, honestly, a lot of different biobots can be envisioned. The answer bots are just sort of one example, and you don't need cilia for biobots to move.

Like, you can also do crawling behavior. So, really, the idea is to use nature as a palette to draw these features from, to build engineered systems. So, once you have that system based on what your therapeutic goal is, you can envision different properties. So if you want to chase some bacteria in the gut, you would engineer your system. Maybe you want it to move in 3d, because bots only move in 2d.

But if you're trying to bulldoze mucus from cystic fibrosis patients, then this ciliary crawling is a better locomotive paradigm, really. The idea is to create these platforms and adapt them to different types of therapeutic applications. So this paradigm shift of. We think of drugs as these inanimate chemicals that just do things in the body. But what about living drugs?

What about living medicine? So I think that's sort of what morphogenetic engineering will enable us to experiment with in the therapeutic space. I guess it's my job to just ask, what are the dangers of this? Whenever we do something dramatic and biological, you have to worry that it's going to fall into the wrong hands or that the terrible mistake will be made. You said that they actually sort of self dissolve after a while, but maybe that's just the first generation, I don't know.

Exactly. Yeah, I think so. This is where if they're just able to explore their native abilities and leverage what they do naturally and deployed in different and unique ways, like in the neuro healing case, I think the concern is less because. Excuse me, because then the bot is carrying the human DNA 100%. But if you're getting into sort of integrating genetic circuits here and you know how bots carry payloads, I think that's where maybe some off target effects might be observed.

But this is something synthetic biology community tackles with, like, a lot. And there are a lot of sort of different strategies for this. For example, kill switches. The bots, or whatever genetic payload is being deployed in the body could be deactivated by a molecule that's orthogonal to everything else in the body, and specifically targets to that targets that genetic circuit and basically deactivates the whole thing. There are definitely some failsafe mechanisms that we could bring into the bots, but that's why I think bots are really exciting, especially ones that don't require genetic editing, because then you're able to just put a piece of tissue that has the exact same DNA as the patient.

Sean Carroll

Human cells. Yeah, exactly. So if you were to make your cells, your bots, we would just take a cheek swab and then go from there, and then we would never touch the DNA. And then when we put those Shawn bots into shine, once the bots are done, what they're doing, they would just kind of disintegrate and the body would never even know. That's the advantage, staying under the radar of the immune system.

Gizem Gumuskaya

But, yeah, once we expand this to include genetic circuits, I think we're going to have to think a bit more about off target effects with the genes and incorporate some of that synthetic biology safety literature and protocols. So this last question is not even a question, but just a statement that it seems like this is just the beginning of something truly big. I mean, when you combine ideas from gene editing and synthetic biology to this sort of robot building that you're doing, it almost makes a physicist like me think that the 21st century will be the century of biology. Yeah, I mean, I think it's just really exciting to see how much we can do. I think there is this, and we still haven't been able to shake it.

I feel like there is this view of nature as this thing sitting outside, waiting to be understood and mapped and decoded. And of course we need to do that. But as we do that, we're also discovering that this is a whole active design medium that we can build completely new things with. So, yeah, it is definitely. I mean, to a degree that, as a designer, just sucked me in and just before I know it, I became a biologist.

So I think there's like, huge opportunities for design and engineering and to create things that are truly unique and have the whole acts of biology, 21st century and beyond. Yeah. We always like to give some ideas out there to youngsters who might be listening to the Mindscape podcast, thinking about what they could do research wise for a living. And this is certainly a very, very exciting field in which to do them. So, Jizem Gobuskaya, thanks so much for being on the Mindscape podcast.

Thanks so much for having me, Sean. I've been a. I remember listening to your podcast late at night in the hood, running experiments, so it's full circle for me. Hope I didn't ruin it. No, no, you motivated them.

Sean Carroll

Excellent. All right, thanks. Thank you.

Gizem Gumuskaya

Thank you.

274 | Gizem Gumuskaya on Building Robots from Human Cells

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1: Introduction

2: Anthrobots Explained

3: Technical Challenges

4: Future Applications

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