342 Levin
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Kevin Folta: [00:00:00] Hi, everybody in today on talking biotech, we'll take several different directions in the area of developmental biology, primarily developmental plasticity. Now, what does plasticity mean? It's when the ability of an organ or tissue, or sometimes a whole organism can undergo this dramatic shift in form and function.

Think about the tail of a lizard. What happens when that falls off the cells at the new end of the lizard? No, to grow, to produce new blood bones, vessels nerves, to create that new tail. So those cells show a kind of plasticity taking on a new mission. How did those cells know that they're at the end of the tail, you know, where the tail came off?

And if we can understand these processes, can we enable regeneration of human limbs and, and, and possibly be able to solve problems for amputees, this kind of thing. And today's guest. He runs an eclectic research program at [00:01:00] Tufts university. And all of this kind of has a common theme around electrical signals and cells and cell to cell communication with implications in limb regeneration and understanding the nervous system and even in cancer.

So we're speaking with Dr. Michael Levin, he's in the department of biology at Tufts university, and a welcome to the podcast. Mike, thanks 

Michael Levin: so much. It's great to be here. 

Kevin Folta: Yeah. It's cool to have you on, I I've known of your stuff for a while. And I, and I always thought I should invite you to be a guest, but you publish like a maniac and I can't believe how prolific you are.

And I look at the, this, and I kind of like, don't like to invite those people because I figure they'll never come on. But then I've heard you on with Vance Crowe and Vance and I are pretty good friends and I really appreciated, you know, what you brought to the table there. And I would like to focus more on some of the recent scientific findings and and we can roll with that here today.

So. You know, when I mentioned that you have a diverse. Program in terms of research, can you give me a little bit of a [00:02:00] back of the envelope sketch of what are the commonalities shared between these diverse subject areas? What are some of the areas where you're currently investigating? Sure. 

Michael Levin: My group has a variety of different types of people.

We have a developmental biologists, we have engineers, we have computer scientists and we operate at this intersection between cell and developmental biology. Computer science and cognitive science and all those sound like kind of three odd things to put together. And the reason they work together is because what, what I'm really interested in is diverse embodiments of mind.

So I'm interested in how it is the different types of things, including brains, but also including various types of non brain tissues cells, single cell organisms. Slimer. Maybe even synthetic organisms artificial intelligence is all of those things, what they have in common, in the ability to have some kind of cognition, to make decisions, to have memories, to have goals and so on.

And the way that that th that's a very deep problem. It's not just [00:03:00] biomedical. This is, this is why it relates to things that computer scientists study. Right? For example, Alan Turing famously was of course interested in intelligence and artificial intelligence, but he also had a really remarkable paper on morphogenesis on the formation of shape and pattern.

And he understood that these are basically the same problem. So that's what we're, that's what we're interested in. And it has lots of implications of course, for, for biomedicine, but also for artificial intelligence for robotics. 

Kevin Folta: Yeah. Well, help me build that bridge. When you say the connection between shape and cognition from these two things do kind of seem kind of separate in my head.

So yeah. So, so how do you connect those dots? 

Michael Levin: Yeah. Yeah, they, they, they seem separate for, for, for a lot of people and they are treated separately by, by funding agencies, by departments, by journals. They're kind of the same problem for the following reason. Let's just, let's just step back from the perspective of of, of medicine here.

Think about the fact that. Well, basically all medical needs with the [00:04:00] exception of infectious disease would be solved if we knew the answer to one simple thing, how it is that collections of cells make decisions to create one body structure versus another. So birth defects traumatic injury. In other words, regenerating after something is lost or damaged cancer aging, degenerative disease, all of these things would cease to be a problem.

If we had the ability to tell cells to build a healthy new organ of a particular shape. Now that leads us to the very important question of, well, how is it? That is how is it that they know what to build in the first place? And so one way to think about this problem is to look at the activity of cells as a collective intelligence.

In other words, like. And many other collective intelligence is which include, for example, ants in a, in a, in termites, in a colony. It also includes us. We are a collective intelligence. You and I are in an important sense. We are a bags of neurons that these neural cells that have to work together towards specific goals.

And you know, the, we, we, we have our own [00:05:00] memories, our own goals, our own preferences that belong to us and not to any of the individual cell. So this ability of individual cells to work to, to some whole combined to scale up into a higher level intelligence is a fundamental. And where did brains learn that trick?

They evolved from other non neural cells, more and more ancient cells that were already using this. They were already using a specific mechanisms in particular bioelectricity electricity, which I'm sure we'll get into to coordinate themselves towards a higher purpose in the, in, for the, in the case of morphogenesis to, to create a particular organ or structure.

So all of these things are a collective intelligence problem. How do you get competent pieces like cells to work together to build one coherent? 

Kevin Folta: Yeah, see, I totally loved this, but so my background is really, I do have a background in development. I think about things in development, maybe with a little more of a time angle here, that when, so when you're thinking about you're building structures from cells and how [00:06:00] did they have a collective intelligence and nowhere to go.

I always think about this as part of a continuum, that development is occurring. The reason you have a liver and a brain and a heart and a spleen is because at the right time, some cells differentiated often to these early pre clusters of cells, which then at that time in the right gradients and the right hormones and the right stuff, that's floating around that cocktail, that, that snapshot in time.

And that chemistry was what facilitated the development and the specific differentiation into those specific organs. So is it the kind of thing, but where we're cells or cells that are there now that are fully differentiated? And, and I, you know, I think I know the answer to this. If they're fully differentiated, can they go back and do that again?

Michael Levin: Let's let's back up for is w we'll we'll come back to that. Let me, let me back up a w for a minute, because you said something very important, which is, you know, one way to look at development is as simply the progressive unrolling of various biochemical states [00:07:00] are driven by information in DNA. That a basic, basically this is a kind of a feed forward emergent view of development.

And that's, that's what, that's what we learn in, in developmental biology class. That's what's in all the textbooks, that's the standard view of development. I want to push back on this because, because I think, I think it's, it's, it's a very limiting view and I think a lot of future regenerative medicine is going to hang on this.

So let me, let me kind of mention a couple of things that, that relate to that basic development, which is, which is very kind of reliable, really obscures. What's actually important yet obscures the intelligence in this process, because if you just look at normal development, if you look at the normal course of events, you really do get the idea that boy, it's just a set of chemical signals that all follow each other in, in space.

There's not, there's not room for kind of any freedom. Each, each chemical state leads to another chemical state. And in the end, you, you, you know, you get some kind of embryo all of that starts to fall apart a little bit when in fact it falls apart a lot. When you. When you look at the ability of that [00:08:00] system to adjust to novelty, which by the way, let's remind ourselves the, the definition of intelligence by William James is the ability to reach the same goal by different means.

So I'm going to describe a couple of scenarios and you, and you'll be able to see the stress that, that puts on this kind of a, a standard view of development as a, as a, as a feed forward process. One thing that's been known for a long, and by the way, these examples that I'm going to describe, they don't feature in any standard, developmental biology textbook, or any of the accounts of what we know, because they kind of blow up the, the, the standard paradigm.

So, so here's one piece of information. If you, you, you have a salamander. And the, the, the most basic thing that people know is that they're, they're incredibly regenerative. So, so they will regrow limbs, eyes, jaws portions of the heart and brain spinal cord. If you amputate them, they grow them back.

So that's interesting. The most interesting thing about it. Actually they grow back. Exactly. What's needed no more, no less. So for example, if you [00:09:00] amputate the limb at the wrist, they will grow back from the wrist upwards. If you amputate at the shoulder, they grow back the whole limb and then they stop now, how do they know when, how does the system know when to stop?

It's actually not, not understood because when they stop is when a correct salamander limb has appeared. So already you start to see this kind of homeostatic process. That's not just, we roll forward the way it is, and then it's one and done. It actually is context sensitive. It will continue to pursue the goal of having a proper limb despite deformations of different types.

So you're already starting to see this. There's some, there's some interesting kind of homeostatic decision-making going on here. That then it gets a lot better. What you can do is you can. You can make notes that are polyploid by that, that, that have ex extra copies of all the chromosomes. And what happens when you do that?

When you force that the cells get bigger, physically, the cells, are we talking about embryos, the cells get physically larger. So that's already kind of interesting. Gee we've we've we've duplicated or triplicated, or you know, five, six times the normal genetic material, you still [00:10:00] get a nude out of it.

That's amazing. You know, why, why, why is the amount of genetic material not matter, but with the most incredible part, is this, when the cells get bigger, you let's let's think of, for example, a kidney tubules. So you've got this, they've got this little, little tubule that goes to the, to the kidney that tubule has to have a certain diameter.

When you make these cells gigantic the size of the animal doesn't. Right. The, the cells are bigger. The animal is the same size, which means that you have to use now fewer cells to do the same job. So, whereas before it was, let's say eight to 10 cells that work together in some kind of cell to cell signaling scheme to make a cross section of a tubule.

Now you've only got four or five cells because it only takes four or five to make that size tubule so that's, that's also interesting. You've got this, you've got the ability of this process to adjust, not just to injury, not just to something that normally happens in nature, where somebody, you know, bite your leg off, but actually to a really bizarre probation of a change of your internal parts.

We don't have any technology where now my parts are, you know, all the parts are three times the size and everything still works [00:11:00] exactly the same way. The most amazing part of that is. If you make the cells so gigantic that you can't fit more than one in the cross section of the tubule one single cell will bend around itself, give you the same exact tubule.

Now look at what look at what's happening here without any evolutionary preparation, without any need to train for it. In, in real time that developmental process figures out that my parts are way bigger than they should be. It knows exactly how big a tubule should be. And in order to achieve that goal with completely different parts, what it will do is it will call up a different molecular mechanism, meaning instead of cell to cell communication.

Now you've got some sort of cytoskeletal bending, right? It calls up a different molecular mechanism to achieve the same high level anatomical goal. So this, this, that, that context sensitivity, that ability to on the fly use different molecular pieces of your toolkit is, is if you were going to try to reproduce it, let's say know.

That's [00:12:00] some sort of robotic technology, or you were just trying to understand it in a cybernetic sense. We were trying to model it is a completely, you, you need a completely different set of tools to understand this than you do for a simple feed forward process that just follow step after step because of this, if this of this plasticity, this ability to deal with novelty, not just injury, not just, you know, not just stress, but actually really, really bizarre circumstances.

And we can talk about many of these different things we can we, we have, we have all kinds of examples that, you know, zettabytes and things that's, that's just, that's just one. And then the other thing that we, we should talk about is the role of the genome in this whole process where you know, when, when, when people ask what determines the shape of a particular organism, everybody immediately sort of says, well, the gene or the genome does now, there, there are, there are numerous examples of.

Plasticity where, where the genome doesn't, doesn't tell the whole story. And one really good example of these planaria. These planaria are flatworms that are highly read. We should talk about them many times. They're highly regenerative. [00:13:00] They are pretty much immortal. They don't, they don't seem to age and so on.

And the thing about planaria is that at least some speeds. They reproduce by splitting in half. So they tear themselves in half, either the, the tail regenerates a new head, the head regenerates a new tail, and now you've got two worms. And the significance of that is that unlike the rest of us, where if we have a mutation in our body that that, that occurs during our lifetime, that mutation doesn't get passed onto our children, right.

That the children don't inherit the mutations in the, in the Soma. So that's, that's, Weissman's barrier. The distinction between the germline and the rest of the body. That's fine. These planaria at least some species don't do that. So that means that every mutation that doesn't kill the. Makes it in his, in his in fact proliferated into future generations.

Now, the, the genomes of these planaria bear witness to this 400 million years of keeping every mutation that doesn't kill you, they are genetically heterogeneous to the point where they're called mixer ploy, because every, every cell can have a different number of chromosomes, right? There [00:14:00] are genetic nightmare.

If you saw, if you saw something like this in the tissue, you would say, this is, this is a very advanced tumor because, because the genome is, is, you know, basically basically gone to heck and yet they are championed regenerators 100% accurate a rock solid morphology, every time you cut them. And so, right.

And so, and so now this, this story is really interesting because the genome is all over the place. The anatomy is rock solid. And so what enables that to happen is some of the software. He actually the policies that guide morphogenesis in these groups of cells that are extremely tolerant, not only to changes in the outside world, not only to mutations, not only to changes in cell size and things like this, but even to changes in the genetic material itself, that that is is that, that, that the, the ability of evolution to produce bodies that, that do this really suggests that we need to be thinking about this very differently than, than simple feedforward the steps.

Okay. 

Kevin Folta: Yeah. See, that's what I was hoping for. I was hoping for you to shatter all my preconceptions, but here's an [00:15:00] interesting point though. So in plants if you use certain cell cycle mutans, you can have cells that are larger and the plant gets to be exactly the same size, just like you were describing.

It knows where it's supposed to be in space, but if you make polypoid plants in most polyploid plants, you'll have larger organs, larger tissues, larger flowers, larger. Hm. And so this is a, kind of, exactly the opposite of what we're talking about. A middle, like the strawberries you buy in the grocery store are actually Lloyd.

The ones that are in the field are deployed and little tiny things as big as the end of your pinkie. So it, so it it's saying that biology is having maybe there's some sort of a selective pressure to making larger organs when you're a plant and stuck in one place versus when you're a mobile animal and can get away from stresses and other other issues may make you a better competitor to be able to resist those mechanisms that can find your space.

You know, our district, your spacial [00:16:00] plasticity. 

Michael Levin: Yeah. Yeah. Right. That makes sense. So that's entirely possible. And of course we know biology is really good at at a variety right. Of doing different things. So I'm not, I'm not claiming that every, you know, every, every species solves these problems the same way.

I wanna there, there are kind of two to two other examples that, that I think are really important to think about with respect to to what you just said and the evolutionary process think about thinking about tadpoles. So tadpoles, they've got eyes and a mouth and jaws, and then. They gotta become a frog in an order for a tadpole to become a frog.

There is a set of deformations or rearrangements of the head that need to happen. So specifically the eyes have to move forward. The nostrils have to move the jaws, have to move all this estimates. And previously it was thought that, well, somehow what evolution does is provide some information in the genome where each component of the head is going to move in a certain direction in a certain length.

And if you do that, you go from a standard tadpole to a standard frog. So what we did a couple of years ago to start taking a look at this, because, because we, we thought that the, this, this was probably a much more intelligent process than that. What we did was [00:17:00] we made so-called Picasso tadpoles, where basically everything's in the wrong place.

So so, so the eyes are off on the side of the head. The jaws are up uh, you know, off to the side, as the nostrils are moved back, like everything is just in the wrong location. And the amazing thing is if you do that, You get largely quite normal frogs because all of these organs will move in from, from the wrong starting position.

They will move a novel paths that they normally don't take. They will go. Sometimes they go too far and they have to double back, but they will keep moving relative to each other until they get to a correct fraud phase. So now this is very important because what the, what the genetics actually gives you is not a hardwired machine that goes from a tadpole to a frog.

It actually gives you an error minimization scheme. It gives you a machine that can reduce error in unexpected circumstances and get back to what, in some sense. And I think we actually know how this works to some extent, so we can talk about that. It goes, in some sense, it has a set point. It's anatomical homeostasis.

It's it's traversing, anatomical space, meaning the space of all configured possible configurations of the face [00:18:00] and it, and it, it, it, it, it knows the area it wants to end up in, and it has some degree of conflict. And navigating to that space, even if you started off in the wrong location. So, so already you starting to, starting to see that evolution is not giving you a solution to a specific problem, how to be a tadpole and then how to be a frog.

It's actually giving them a machine that can solve a wide range of problems, like how to get to be a frog from not from every possible condition. I mean, of course you can make birth defects and, you know, defective embryo embryos, that never correct. That's absolutely possible, but from a wide range of starting.

It gets to be a correct correct place. And, and the last kind of thing I want to, I want to throw in here, since, since we're talking about this, this evolutionary bit is this we wanted to ask the question, what, what happens? What, what, what do skin cells typically want to do? Right? What, what is their default behavior?

Now, if you look at a frog embryo or at any embryo, you would say that, well, what their default behavior is to sit, have this like boring life, a two dimensional life as a surface layer on the [00:19:00] outside of the body. Keep out the, keep out the pathogens, right? That's that's what skin is good at doing? Well. It turns out that if you take skin cells off of an early frog, embryo, you don't add anything.

No, no, no new genes. No, nanomaterials no weird. You know, kind of a weird reprogramming or anything, you just take them off of the normal embryo, you subtract something it's sort of sort of programming by subtraction. You're, you're removing the normal influence that the other cells have on them, what they do by default, given their own chance to sort of reboot multicellularity and do their own thing.

What they do is they form these little structures. We call zettabytes is the name of the frog. So we call them Zina bots. Now, now these cells could have done many things they could have, they could have died as some cells do. When you take them out, it's in vitro. They could have spread out in a two layer, a flat 2d culture.

They could have sort of wandered off. Instead, what they do is they collect two together. They form this little ball that is covered by silly. A cilia are little multi-level hairs that normally. Mucus along the surface of the, of the tadpole. And they use the cilia now to roll [00:20:00] like little tiny oars against the water.

And they start running around the Petri dish. They start to move around, they move on their own. They have all kinds of interesting behaviors, singly in groups. They they, they, they navigate amazes and other shapes, they, they heal damage. They even make copies of themselves through a kinematic replication, which we can talk about, which no other animal does.

Now. Now here's the here's. Here's why this is interesting evolutionarily. There's never been selection to be a great Xenobi because there's never been any Santa pots. So if you ask the question, what determines the shape of an organ. Yes. Yeah. The genome and prior selection of course plays a huge role, but they don't play the only role.

What they provide is not just the genome that knows how to do one thing. They, they, they create the seed that that genome is the seed for a machine that can solve problems in different spaces. We're talking metabolic space, a transcriptional space, more, you know, morphological space can solve these problems in completely novel circumstances.

That evolution has never seen before. These are [00:21:00] totally wild type xenopus Leyva cells. They're creating a little creature. That's actually quite different from, from a frog or a tadpole. They have their own you've watched them over several months. They transform into this weird thing that you know, it doesn't look anything like that we've seen before they have their own developmental sequence.

You know, you can ask that question, where did this come from? Sure. As heck didn't come from selection to be a good Xenobi like that. That's one of the huge you know, open, exciting, open areas in the future is how is it that evolution. That we normally think of as being like blind and short-sighted and, you know, always picking immediate payoffs and so on.

How is it that evolution actually makes these machines that are great at solving problems in novel environments? You know, that's, that's a, that's a deep puzzle. 

Kevin Folta: Yeah. So it sounds like, like some sort of restriction was removed from the cells in their, in their identity. So that would allow for these kinds of changes in plasticity, from tadpole to frog or say regeneration of a tail or something like that, that something is different about, because those that wouldn't happen with animal cells necessarily.

I [00:22:00] would shouldn't animal cells, mammalian cells probably, and maybe even with insect cells, but let me be asked, maybe ask it this way is where are the. Behaviors loss or these abilities to read, to regenerate or to create zettabytes or, you know, whatever mammal bots, where are those lost? And are there any of these things that we retain as humans, maybe even developmentally at some point, the ability to regenerate or to re.

New structures that from plasticity of cells. Yeah. 

Michael Levin: I, I can tell you that, there's so there's some things I can't say yet because it's not published in peer reviewed, but the bottom line is that this is, this has nothing to do with being an amphibian. This has nothing to do with being an embryo you know, stay tuned for all that.

This is, this is, this, this plasticity is, is quite universal. And, and you know, I wanna, I wanna jump to an example having to do with, with with a large adult mammal that, that exhibits a couple of interesting things that we want to talk about here, [00:23:00] which are, which are dear. So dear, every year we'll regenerate their antlers.

And so the first amazing thing is that, yeah, here's the. A gigantic adult mammal that is able to regenerate up to a centimeter and a half of new bone per day. So these things, these things generate crazy amounts of, of new growth of bone, of vasculature innervation skin when they're regrowing these antlers very, very rapid.

So, so that's already interesting. So, so here's a, here's a mammal that has regenerative ability for this particular structure. There's a, there's another interesting piece of this, which is, which is called trophic memory. So, so these, these two guys named Bubeck. Starting work in the, in the sixties and, and they, they, they worked out up until I think up until the mid nineties, they were still at it.

What they showed was the following that in, in certain certain species of deer if you come along and certain species of deer make the same antler structure every year. Okay. So every year it's the same pattern for, from animal to animal. Every, every animal makes the same pattern each year, but for the pattern of branches, I mean, and, and, and by the way, just as a fun thing, I, I, I literally have [00:24:00] all these antlers in my lab because when, when diabetics sort of retired and decided that he had had had enough, I was one of the few people that had written about this work.

And he emailed me and said, do you want the, I said, yes. And we got, we got the 12 boxes of these labels, you know, these labeled antlers. And you'll see why this is such a unique data set. It's never going to repeat, be repeated again. I think basically what here's, what he found is that if you take it out.

And you, and you take a knife and you just make a, make a, make an you, you a wound into somewhere on the branch structure of the of the antler that you'll get a little callous. The bone will heal. You'll get a little catalyst and that's that by the end of the year, that whole antler rack. And then next year, when the new Andler req grows at the place where you made the damage last year, that's when a new ectopic tine is going to grow and this, and this goes on for about five or six cycles, and then eventually it disappears and goes back to normal.

So now, so any called that trophic memory. So now, now think about trying to make a model of this using our standard tools and molecular biology, which has [00:25:00] pathways. Here's what the, here's, what the cells in the scalp need to do. There was a, there was a damage somewhere along this branch three-dimensional structure, you need to, first of all, know where that was in code.

That somehow you need to store that information in the cells at the, at the scalp for months, then when it's time to grow. You need to let the bone grow, but when you reach that point in the brand structure, you need to instruct those bone cells to, by the way, take a detour and grow a separate a separate time.

I mean, I don't, I, you know, I don't know about you, but, but, but it makes my head hurt trying to come up with a, with a, with a pathway of, you know, the, the kind of thing you see in figure seven of, of, of a cell paper is like this arrow pathway, right. Of, you know, these genes turn each other on and off, and you try to make a model of trophic memory with those, with those tools.

I mean, I don't, I don't know how you would do it. So so, so, so when you, you know, when you talk about where does this, where's the stop? I don't believe that it fundamentally stops anywhere. I think that what evolution has done and we can talk about [00:26:00] why it is that humans are not as regenerative as let's say a salamanders and whatnot.

I think that what evolution has done. Optimized for particular lifestyles, but it does that by basically by, by, by bullying the cells into, into submission. I mean, the reason that skin cells normally make two dimensional skin and nods zettabytes is because the other Salesforce. Right. Their baseline behaviors to make zettabytes, but in vivo, they get these instructive signals from the other cells.

And so all, all of those instructive signals and, and, and this is like an important and important difference in how you think about this as an engineer, you, when you work with passive materials, you have to micromanage. Where everything goes, because the only thing you can really rely on is that they sort of hold their shape or conduct to, you know, electricity or something like that.

What evolution works with and what regenerative medicine is supposed to work with. And what synthetic morphologies is gonna work with is a kind of a gentle material. It's a material with an agenda. So when you, because your cells, they used to be individual organisms. There's a [00:27:00] million things. They know how to do.

There are, they have preferences. They have little tiny goals that they try to execute when you. Make a, an organism. You don't start from scratch, putting everything where it goes. What you're really searching is the space of signals, the space of incentives, the space of communications that you can have across these cells to, to try to get them to do whatever it is that you want them to do.

It's a, you know, it's a, it's a different way. It's not a bottom up micromanagement kind of approach. It's a, I have this, I have this a gentle material. It's, it's not even just an active materials, not even just the computational material. It's, it's, it's much, it's much deeper than that because these things used to be independent organisms.

So I don't think it stops. I think it just sort of temporarily held under wraps by other constraints that evolution likes. And it's 

Kevin Folta: kind of interesting. I mean, one of the reasons I asked him about, you know mammals in college, I was a bartender as cutting bar fruit. And I chopped the end of my finger off kind of a 45 degree angle, you know, at the end of the nail.

And it hurt like hell, cause it was limes and Nail. [00:28:00] I had like a flat spot on my finger for a while, but it grew back to exactly where it was. And it always seemed like it seemed kind of odd that, you know, here, this tissue on me at this time in my life would be able to do this. And it knows exactly where to stop as you mentioned before.

So maybe just another good example of that, that there's a little bit of this alive and Wells, even in us as humans. 

Michael Levin: Yeah, absolutely. And, you know, as an adult doing that as an adult is, is kind of an unusual case children. It's, well-known the children somewhere below. I mean, it usually stops by about seven to 11 or so.

Children will regenerate their fingertips and, and it used to be much more common in the seventies. I guess the fan, the, the metal fans had Neff little, little grates on them or something that kids used to kids used to have their fingers fingertips chopped off and a singer. And this guy Illingworth realized that when you have that.

Don't so the skin over and you just sort of keep it clean and leave it alone. They will in fact regenerate cosmetically very, very, very well. And you know, it's thought that that kind of Peters out with adulthood, but it sounds like, it sounds like you [00:29:00] still have it. Yeah, 

Kevin Folta: it sounds. I seem to remember a lot of kids getting their hands slammed in car doors.

Like they're really big, heavy seventies car doors. That would seem to be a thing, but it, maybe fans are good example too. But we're, we're speaking with Dr. Mike Levin, he's at Tufts university and we're here on collaborative talking biotech podcasts, talking about plasticity and organ development. And when we come back on the other side of the break, we're going to talk about what are maybe some of the signals that are providing these instructions that help establish shaven boundaries and really interesting stuff.

This is the talking biotech podcast by collabora, and we'll be back in just a month. And now we're back on the talking biotech podcasts by collabora. And we're speaking with Dr. Michael Levin. He's a developmental, I don't even know how I'd characterize your developmental wizard. Thinking about really interesting questions in.

Developmental biology and developmental plasticity and a, with an overlay of engineering and computational [00:30:00] intelligence that are allowing us to rethink the way that we think about animal development. And when we're back on the other side of the, of the break, we were talking about these ideas of where to establish borders and how to think about how cells communicate with each other in space.

Well, we didn't talk about communicate yet, but you talked about this idea of instructional signals that are there between cells and what do we know about what those signals are? So how, when something is missing, do those cells suddenly signal each other to potentially change their further plasticity and re differentiation into new stress?

Michael Levin: Yeah. I, I love the I love the fact that, that you weren't sure how to characterize what I do. I think, I think that's very fair. I have no idea how to, what to call it, because I think that the the borders between the different fields are, are very artificial. And to be, to be completely honest, I think what I do is a branch of computer science it's done in biological [00:31:00] means.

As opposed to Silicon, but I actually think that this is all fundamentally part of a company of the science of computation and just in, in different media. How, how do cells how do cells communicate? So, so, so as far as we know, I mean, there are three main things that people study and then there's some exotica, the main types of modalities that people study are forced, biochemical signals and chemical gradients people study biomechanics.

So, so forces like strains and stress and pull, you know things like that. And and bioelectricity, which is what we focus on now. Now there are also ultra weak photon emissions and things like that, that I think actually pretty interesting, but much less is known about that. So for us, we, we really tend to focus on bioelectricity.

Of course we have to link it to known canonical pathways. So we always have to say, how does it change gene expression and how does it change chromatin modification and so on. But fundamentally there's some really interesting things going on in all of your body cells talking to each other electrically.

Kevin Folta: That's really interesting stuff. So let's talk a [00:32:00] little bit about that electricity part and bio electricity. And we know we all know about electric yields and things like that. Really obvious places where bioelectricity is, is a very real thing, but how are cells generating electricity and what, what are we really looking at when we're talking about bioelectricity, let's start.

Yeah. 

Michael Levin: The, the one, one easy way to think about this and I'll get into the details momentarily, but what one, one easy way to like big picture, way to think about this is just to ask yourself, where did neurons come from and what is, what exactly is a neuron? So, so in your, in your nervous system and in your brain, you've got a network of cells that we all know communicate electrically and people are trying to read that it's called neural decoding to read that electrical activity and try to guess what, what the cognitive apparatus is doing.

And you can, you can just realize that these neurons didn't appear out of nowhere. They basically just speed optimized things that cells were doing long before muscle and nerve appeared. Okay. [00:33:00] Evolution discovered that electricity was a great, very convenient way to process information and to compute back around the time of bacterial biofilms.

So there's been some great work on bacterial biofilms and looking at electrical coordination there, and cells have been using this since then long before we had to move around in three-dimensional space. Cells had to figure out how to find their path in first metabolic space and then transcriptional space and eventually anatomical morphous space.

And these, this, this bioelectrical of these bioelectrical networks are great as a. That are kind of cognitive glue. What I mean by that is they bind the ability of individual subunits, meaning cells to do little tiny homeostatic goals, like keeping their, their med metabolism, their pH, all of these things in the right on the right states bioelectricity allows those mechanisms to be scaled up so that collections of cells can, can think about very large goals, like making a hand or a liver or an eye.

And ultimately what evolution did is pivot again and use [00:34:00] those exact same tricks to let you think about movements in three-dimensional space and in terms of canonical behavior and, and, you know, running around and trying to eat, pray and not get eaten. So it's, it's the, it, it works basically just like electricity in the brain, which, which one of the, one of the fun things I sometimes do with my students is.

Take a P pick up a paper and it'd be like any paper in neuroscience and put it through Microsoft word and do a find replace. And anywhere that it's as neuron, have it replaced with the word sell and anywhere that it says millisecond, have it say hour and that's it. And then read the paper again as a developmental biology paper.

And it's, it's quite remarkable because, because not only are the mechanisms conserved, but, but also the the, the algorithms are conserved, meaning that others, other tissues in your body are using these electrical networks to store memories, to make decisions, to organize information across space. They just happen to be decisions about shape, not decisions about movement and behavior and where bioelectric [00:35:00] by electric signals come from is that every cell much like neurons, every cell has these little proteins on their surface called ion channels.

They can open it. And these ion channels let through or not different types of charged molecules. So we're talking about sodium potassium, chloride, protons in, in and out, and by, by opening and closing in a particular way, they result in a, in an imbalance of charges, usually negative. Usually inside you have a lot more negative charges than you have outside that results in a voltage potential.

So your cell is basically a little battery, but it's a little battery that that is, is, is very clever because these channels are themselves kind of like transistors because they open and close based on among other things, the voltage. So you can have these really clever feedback loops where a channel opens and it changes the voltage, which in turn, causes the channel to open more and which in turn changes the voltage and so on.

So all of these things bind the S and then of course there are the electrical synapses known as gap junctions and all of these, all of these components, bind [00:36:00] cells in every tissue into a large electrical network that can process. 

Kevin Folta: And so you're seeing effects of, and I guess I know the answer to this because we see it in plants.

You can induce an electrical response at one end, just as non nerve cells and still be able to see some sort of a transmission or communication between cells, even inside an organism. 

Michael Levin: Yeah. Yeah. This is, this is a very interesting aspect of bio electrics. It's highly non-local which again, in the case of the brain, shouldn't be a big surprise.

That's what, that's what the electricity is for in the brain. You can I'll, I'll give you a few examples in the, in the cancer case. So, so we've got this, we've got this example where you take human AKA genes and you inject them into a, into a, a frog embryo and they'll make a tumor. And that tumor is in part, it arises because the cells, one of the first things that oncagenes do is get cells.

Depolarize meaning reduce their membrane potential and electrically disconnect from their neighbors. And so when they do that, they basically roll back to their unicellular amoeba like lifestyle. Once you're no longer plugged in [00:37:00] to the electrical network that makes you part of a larger computational agent.

You can't remember what you were, what you were working on anymore. You are self becomes tiny that that boundary between self and world shrinks before you were part of this giant network that was working on a, you know, a liver or in fact the whole embryo. But now that boundary is, is right at the surface of the cell.

So as far as you're concerned, the rest of the body's just environment to you, your, your enemy. But what do we mean by is like to do while they like to become to me? And they like to go where life is good and that's metastasis. So, so the reason I'm telling this story is, is because what we discovered is that if you if you, if you put in, if you put in that oncogene and then you also put in a.

An artificial an exogenous ion channel that forces cells to be hyperpolarized despite what the, what the oncogene is trying to do, then there's no, there's no tumor the cell, even though the onco protein is blazingly expressed, the cell continues to performance, job and making nice you know, skin or mesenchyme or whatever it's doing.

Now, what we found is that you can put that channel [00:38:00] on the opposite side of the animal. It does not have to be in the same cell. That decision of what you're going to do is not made independently by a single cell. It's a network, it's a network property. And so in that case, there's another case where we, where we used bioelectric and control of iron channel activity to repair brain defects.

When you do that, when you repair brain defects, same thing you can repair brain defects in the, you can repair defects in the brain by putting special ion channels on the gut on the opposite side. Of on the opposite side of the animal and many, many, many cell diameters away. So, so these, these biological networks are really good at integrating information across space.

The not just local, 

Kevin Folta: this is, so this is, you mentioned dictyostelium. And so is that kind of behind the whole organization of multicellularity? Is that the coordination of that dictated by electrical 

Michael Levin: signals? You know, I, I don't know. And actually, when I said slime mold, I meant the other kind will Pfizer arm, which is a, you know, something else.

But Dick, Dick, Dick to steal him is super interesting. People do, I think men's [00:39:00] owl and some other people have studied electrical accused and dicta Sealy. I'm I'm I'm actually, I don't think we know enough, but I wouldn't be surprised at all. Bioelectric is, is one of the key things that orchestrates multicellularity in invertebrates.

And it's entirely possible that it's doing that in Dixie as well. I 

Kevin Folta: just, I just happened to mention that cause it's something that I always thought I was totally cool, but, and I know we're kind of dancing around a couple of different places here because there's so many things I'd love to get to, and I know time is short, but let's talk a little bit about this idea of, of, of the electric ceuticals of the compounds that you can use to affect these trends.

Potentials inside cells and their communication with each other and how that may be applying to cancer. And you had an interesting breast cancer. You were a collaborator in a breast cancer study, not too long ago, which really talked about communication between left and right side with electrical and then potential disruption of that by electricity ceuticals.

So could you touch on that 

Michael Levin: for a bit? Sure. Yeah, the, the whole concept of Electra ceuticals is simply is simply this[00:40:00] the ion channels on the surface of cells in a tissue form, a kind of programming interface. It's if they're like a keyboard, they're basically giving, I mean, think of how we program computers in the 1950.

The way we program computers was by physically moving wires around. Right. I have this great picture that I show at the beginning of my talks, which has this, this, this lady. And she's sitting there programming an ancient computer, and she's literally pulling wires and reconnecting and other places.

That's the hardware is how we reprogram things in the in the forties and fifties. And when I say to my students, Hey when you change from, let's say Photoshop to Microsoft word on your laptop, I want you to get out your soldering iron and start rewiring. And they, they laugh. Everybody. Laughs.

It's very funny. And then I say, you know, what, why, why is it so funny? And it's funny because we now we are so used to this idea that if your hardware is good, You don't need to rewire it. You, you, you control it with inputs, with stimuli, with signals, right? And and, and my point is that that, you know, 20 years from now, people will be looking at the molecular medicine of today, which is all about the hardware.

It's all about [00:41:00] genomic editing and, and you know, modifying protein structure and, and rewiring pathways. What we're going to be looking at this the exact same way, the same way that, that, that, that we now look at these at, at programming by pulling wires. And we, we think it's hilarious. And so, and so what, what, so, so then you have to ask, right?

If I'm telling you that the biological hardware is, is of course, as you know good enough to, to allow this kind of reprogramming, you want to know a couple of things you want to know, what's the interface, how is it that we're going to, we're going to provide the signals to reprogramming, and you want to know what the sub routines are?

What do we get to do. Like, what does it know how to do that? We can, that we can trigger or suppress. And so, so the interface are these ion channels. What you want to be able to do is open them and close them in a very particular way to give rise to the correct bioelectrical states that do what you want.

So an easy way to do that is through ion channel drugs. That's what I mean by electric. Ceuticals now other people, there's a, there's a whole effort by GSK and so on that, that think of electrodes and electrical stimulation as electroceuticals. And that's fine. There are [00:42:00] some things you can actually do that.

But it's just the tip of the iceberg because the what's what's really easy to do with electrodes is to spike neurons, excitable cells like neurons. So you can, you know, you can, you can do those things that they do, like triggering the the, the, the, the various peripheral nerve, the vagus nerve and things like that to, to get immune responses and so on.

But, but most cells, you can't, you can't change their, their long-term resting potential with electrodes. You have to do it by opening and closing channels, which means drugs. Something like 20% of all drugs are ion channel drugs. Many of them are already human approved. People take them for epilepsy for, for cardiac syndromes for, for various kinds of disorders and all of those drugs form this incredible tool kit of electric ceuticals.

Plus of course, new, new, new channel drugs that will be discovered later, they form this incredible class of electric ceuticals, which if we knew which ones to choose, we could use them to play this. Like a, like we do a computer and a to program them. And [00:43:00] the way you choose is with computational tools.

So, so we've started making some of the first predictive platforms that tell you which channels and you need to be opened or closed to achieve specific effects, which means, which means knowing that that tells you which drugs you need. Yeah, we had that paper in breast cancer where there was another paper that just came out from our lab as to do with glioblastoma and using, using electro suitable drugs against glioblastoma.

And that was a couple of weeks ago. The idea is to choose to use this computational process to choose. That would optimally reconnect the cells to a network that could remember what the correct pattern was supposed to be. So not individual cells, not a random tumor, but actually whatever the correct pattern is supposed to be in.

That is going that, that general strategy is going to, I think, is going to work with regenerative medicine of all kinds of not just reprogramming tumors, but inducing, you know, we have, and I should, I should say here a disclosure, right? We have we have David Kaplan and I have a spinoff company called Morphis ceuticals, which is taking what we've done in frog, which [00:44:00] is learned to trigger leg regeneration and taken into mammals and basically use that same, that same kind of kind of strategy for a wide range of regenerative medicine indications.

Kevin Folta: Well, let's talk about that frog example really quick. I know we get a little short on time here and You had reported last year in collaboration with the team, this ability to give a cocktail of compounds to a frog amputated limb, and be able to enhance the regrowth of the structure. Scooch, could you touch on that for a bit?

Sure. 

Michael Levin: Yeah, we we've had, we've had a, a number of papers on, on this topic starting off with, with electricity nickel kinds of triggers in young froglets and ending the last paper, which was this year was, was, was full adults that are, that are highly non regenerative as far as their limbs go.

What we discovered was that, and it wasn't, it wasn't only, I mean, there's a lot of things still in the works, but what the papers that are out now include other things that are not necessarily bioelectrical. The idea is that right after amputation, there's a, [00:45:00] the, the, the cells need to make a decision about what they're going to do.

Are they going to scar or are they going to do nothing? Are they going to grow a new leg? And what we found is that you can, you can Push on that decision tool, you can push them towards regeneration. The way we do it is we put drugs into a wearable bioreactor. This is what a David Kaplan's lab, but makes us these a, these wearable bioreactors they're filled with with a, kind of a silk gel, which contains our drug payload.

And that all goes on the wound that stays on the wound for 24 hours. Just one day. After that you take it off, you don't touch the, the, the animal again that gives you, it gives you a year and a half of leg growth that just a 24 hour trigger. So, so the reason we're doing this is because we, we firmly believe that the road to regenerative medicine is not bottom up.

Micromanagement is not going to be figuring out how to control all of the gene expression to make an adult leg. It's not about being able to put in all the right factors or all the right stem cells that have to be everywhere in the right place at the right. [00:46:00] That's way too complicated and that's not how the biology does it.

It's not through bottom of micromanagement. We need to identify triggers, for example, a trigger of build, whatever normally goes here, right? That's a nice high level, a signal that you might give to the system to get it, to do something that you don't, you don't know how to micromanage that. So we discovered some of these triggers and in the frog, we discovered a really great one that basically causes it to, to, to, to rebuild the leg.

That's functional. The leg in the end is, is multi-religious it can feel and so on. And so yeah, the next step is of course trying the same trick and mammals and hopefully eventually been biomedical lab. 

Kevin Folta: Yeah, the, the figures are really nice. And when you look at the figures in the paper that you can see the untreated frog versus the ones that have been given this cocktail of putative morphogen I guess they are morphogen is in some cases for 24 hours, it actually develops a, almost a normal looking leg.

Like you know, you can see little toes kind of poking on things like that there too. 

Michael Levin: [00:47:00] Well, thank you. There's two amazing things about it. One is aside from the fact that you can turn on regeneration in an animal that that whose adult does not regenerate one, one is that I don't know if it's clear from, from that paper because we, we didn't really stress that, but, but it's, it's an important point.

This is our first choice of cocktail. Like this is not cocktail 89 from, from 300 things we screened. This is the first thing we tried. So what that tells us, right? What tells me because, because you know, we, we, I don't buy lottery tickets and so on. So, so that tells me that this isn't just the luckiest choice in the world.

This is, this means that the, the, the optimized, this isn't the best. We can do the optimized cocktail after we, after we really optimize it, the results are going to be amazing. This is the, this is this is this impressive outcome. That's the first, that's the first thing we try. That's the first cocktail.

So we didn't, we didn't even get to play with different combinations, different dosages, different timings. This was a first. Already works like this. So, so I've really high hopes for, for the rest of it. The other thing to say is that, and [00:48:00] this goes back to our earlier point about intelligence as the ability to, to get the same effect through different means.

When we, when, when in, in previous work, when we worked with young froglets and we got them to regenerate, one of the amazing things we saw is that the path that the limb takes to get to a nice frog leg is not the developer is not the normal developmental path. In other words, those, those regenerating frog legs do not look like a developing frog legs.

And so they found another way that cells found a different way to navigate that more for space to get to the correct final outcome, not in the way that they normally do in development. 

Kevin Folta: But they know where to go. That's it. And so let me guess your research is sponsored by the frog leg industry or 

Michael Levin: how are you?

That's a great idea. I should reach out to them. No, no, no, no, no funding from them yet. Yeah, because 

Kevin Folta: then it would do it satisfy the animal rights people because you'd have it. You wouldn't be killing any animals. You wouldn't be sacrificing a frog to obtain frog legs. You could just keep growing [00:49:00] new ones on the same 

Michael Levin: ones.

Oh, that's an interesting, it's an interesting. No, you heard it here 

Kevin Folta: first. Okay. So you can have regeneration in a frog that has had a leg amputated, but how might this apply to other types of birth defects and the ability to maybe initiate correction of those early in the. 

Michael Levin: Yeah, one, one of the, one of my sort of one of our flagship examples that I, that I really am interested in and really proud of is this this, this, this project that we did on, on fixing fixing brain defects.

And what we were able to do is find out that of wide variety of disruptors, of development. So alcohol and nicotine, and in fact, mutations, even mutations of really important genes like notch. One of the ways that they screw up brain development is by messing with the, with this bioelectric pre pattern that normally tells the cells how big and what shape the brain should be.

And what we did was to the, and this was, this was worked with our collaborator, Alexis PAETEC who created a [00:50:00] computational model. That basically explained the, the, the electric patterns we see. And then what you can do is you can ask the model questions, for example, what channels would I have to open and close to get back to the correct state?

And the model suggested a particular channel called HCN two. And we later were able to show that either by putting in new HCN two or by opening the native HCI into using drugs in particular human human anti-epileptic. It basically resolves the problem. These animals not only get their, the shape of the brain back, but their their, the gene expression in their IQ.

So their learning rate goes back to normal, even though they have this for example, this dominant mutation in this really important neurogenesis gene notch. So the ability to, and I'm not, and I'm not saying that bioelectric is, is going to repair. Every genetic defect are plenty of genetic defects, you know, enzymes and things like that, that, that bioelectricity is just not going to have any impact on, but, but for, for many things that can be fixed as quote unquote in software, this, this kind of [00:51:00] intervention is, is really powerful.

I mean, getting back a comment. Oregon like the brain. And again, we did not have to micromanage it. We didn't have to put in all the information that it takes to make a proper fraud brand. I mean, that's a huge amount of information with no idea how to do that. What we do know how to do is to sharpen the electric pattern to the correct state, where it tells the cells exactly what to do to make a proper brain.

And so I'm, I'm in particular, very excited about this and the ability to someday to basically fix incipient birth defects by appropriate electroceuticals. Now that has all kinds of interesting difficulties in terms of reaching the clinic, because how do you test things on, on, on, you know, in pregnancy?

We, we're not, we don't, we don't have a path worked out, which is kind of weird because we, we do have a national Institute on Joe child health and human development, which funds a lot of the great developmental biology. So one of the big things in this field is to develop a path forward from these basic decisions.

To to the clinics so that we can actually test this big I'm, I'm, I'm fairly passionate about on birth defects research, [00:52:00] 

Kevin Folta: but it seems that there's no such thing as a free lunch, right? That you make this prediction based on computational algorithms that tells you to activate this particular set of channels.

But how do you know you go far enough or not too far? And what happens if you go too far? And so I can see the need for, you know, research clinically, but it seems like there's gotta be a lot more basic research first before you could make that jump. Or am I totally missing something? 

Michael Levin: No, no, no, no, no argument.

I'm not, I'm not saying that that today we're, we're ready to start testing it in in the field. No, of course, of course. Of course you need tons more basic research. Absolutely. However, I will, I will say one, one interesting thing. When you, when you work bottom up, in other words, when you are really trying to micromanage the situation, it's on you to get all the details.

In other words, there's lots of opportunity for side effects. There's lots of opportunity to go too far, too much signaling, not enough signaling all that kind of stuff. The benefit of going top-down signals is [00:53:00] that you are not providing the details. You're providing a very low information current. Input that says build an I here.

That's for example, that's it. And we've done that. For example, we figured out how to make other tissues in the embryo, including the gut to make a perfectly good eye. When you do that, we don't provide all the information of how to make an eye because of course we might get it wrong too. A man, too much retina to a little optic nerve, I'd say that's easy, but we don't specify any of that.

The trick is to to, to, to kickstart the process that the cells already know how to do and stay out of it after that. And so when you do that, then everything that size control all the different you know, having the thing stop when it's done, all of that is automatically. Is automatically handled.

That's the beauty of submarines. That's why we use them in computer science. That way. That's why we should be, we should be using them here. And so our work bears that out. You know, our, our very first work on tail regeneration. This was 2007. I think, showing that there's a particular bioelectric state that you can induce that causes tadpoles, that don't normally regenerate their tail, including muscle spinal cord, all that we got them to regenerate their tail.

And the way we did it was by [00:54:00] putting in a proton pump from. That we have no control over it. We had no idea how much proton had protons had pumps compared to what normally goes, goes, you know what the norm, what the native pumps in the, in the tackle that we didn't know how to turn it on. We didn't know how to turn it off.

We didn't do any of that. We just provided that very simple bio electric state that says build whatever normally goes. And bang it, it created a perfectly good tail, never a tumor, never something else. Exactly what it needs, because we weren't trying to micromanage those details. So I think to the extent that, I mean, of course, so, so, so bottom line, I totally agree with you.

All of this needs much more basic research, no doubt, but in the end, I think we're w where we're going to win. By acknowledging the strategy of not trying to micromanage all the details of which we'll probably get a lot wrong. And instead, talk to the system, using the signals that it already understands.

And once you say, make an I, and once it gets going, you'll leave it alone and you let the native sub routines do their thing. 

Kevin Folta: Okay. Now this is, this [00:55:00] fun takes us down on another funny path because on the podcast series, I spoke with Dr. Jack Horner and he was a, he's a he was an advisor to the to drastic park.

And as, as a paleontologist, he, one of his big interests is the developmental biology of birds and dinosaurs. And they're related to us. And he's been able to show that you can use gene editing and play with the hardware to make a bird grow teeth developmentally, and be able to grow fingers, but he hasn't been able to get a tail.

And maybe he's instead of playing with genes, these folks need to be playing with electric 

Michael Levin: ceuticals yeah. Could well be I'm not going to say instead, because I think what he's doing is, is, is, is quite interesting and important. I will say in addition to, and I'll give you just one simple example with these planaria.

So, so when, when these planaria regenerate, we found that there's a, there's a bioelectric circuit that literally holds the memory of how many heads of planarian is supposed to have. And there's a basic cause there's a few papers where we show that if you rewrite that electrical information, they make, they can make two, for example, two heads and [00:56:00] permanently continued to make two heads after other curricular cut.

And so one of the interesting things you can do with that is, is go further than that. And if you cut off, if you cut the fragment of the planarian and let them regenerate. In a solution of B basically it's, it's basically general anesthetic that, that, that basically just blocks the electrical connections between the cells for about 48 hours, that electrical circuit, when you, when you pull them out of that, that compound, that electrical circuit we'll come back to, we'll try to come back to a normal, normal state.

It sometimes makes it, and then you get a normal planarian with its normal shape head, but sometimes it lands in the wrong bioelectrical attractor and it ends up making a head that belongs to a different species of planarian. Now we've had, we've had right. We've had it make species of that are, that are evolutionarily about a hundred to 200 million years.

Oh, sorry. Sorry. A hundred to 150 million years. Distant. And that is without any genetic change, there's nothing wrong with the genome of these animals. It's just that the, the, the hardware [00:57:00] is normally it's pretty reliable and finding the right bioelectric attractor, but you can shift it. And sometimes it shifts on its own.

And in that case, it will make heads, including brain shape, distribution of stem cells. We don't know about behavior. We started testing it, but we never, you know, we haven't finished that yet of completely different species. So there's more than one way to explore the morphous space of that, of the species.

And of course, changes in hardware is one way, but changes in software. 

Kevin Folta: Well, at least in an hour, we've packed in discussion of what would normally be considered seven or eight scientific careers. I mean, each one of these things is totally fascinating. I really appreciate you taking the time to be with me today and we'll have to do it sometime when we get an entire day.

Michael Levin: Thank you so much. Yeah. Thanks for having me. It's a great conversation. I would, I would love to keep talking about it. 

Kevin Folta: Well, what if people want to learn more about your program? Where do they look on. 

Michael Levin: The easiest thing to do is is there's a website Dr. Michael levin.org. So Dr. Mike eleven.org that, that links to the various institutes and [00:58:00] centers that I'm associated with, that links to our our company webpages.

And you can also catch me on Twitter at at Dr. Mike 11. 

Kevin Folta: Yeah. And a really good Twitter followers too. So definitely do that one. Well, you know, well, thank you very much, Dr. Levin. I really appreciate you being on with me here today. Best of luck, best wishes going forward. And next time you have the next big break for, through that.

You want to share with this audience, please consider us first to share that news because it, we really do like this kind of stuff. So thank you very much. 

Michael Levin: Fantastic. Thanks so much. Thanks. 

Kevin Folta: And as always, thank you for listening to another episode of collaboratives talking biotech podcasts write a review on iTunes, but most importantly, share with other people, you know, in the science communication process, you got content, creators and amplifiers, and your job is critical as an amplifier.

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Thank you for listening to the talking biotech podcast. And we'll talk to you again next week.