Chris Anderson: Mike, welcome. It's good to see you. I'm excited for this conversation.
Kris Anderson: Majk, dobro došao. Dobro je videti te. Uzbuđen sam zbog ovog razgovora.
Michael Levin: Thank you so much. I'm so happy to be here.
Majkl Levin: Mnogo ti hvala. Srećan sam što sam tu.
CA: So, most of us have this mental model in biology that DNA is a property of every living thing, that it is kind of the software that builds the hardware of our body. That's how a lot of us think about this. That model leaves too many deep mysteries. Can you share with us some of those mysteries and also what tadpoles have to do with it?
KA: Većina nas ima sledeći biološki mentalni model da je DNK svojstvo svih živih bića, da se radi o nekakvom softveru koji gradi hardver našeg tela. Tako mnogi od nas razmišljaju o ovome. Taj model ostavlja suviše suštinskih tajni. Možeš li da podeliš sa nama neke od tih tajni, kao i kakve veze punoglavci imaju s tim?
ML: Sure. Yeah. I'd like to give you another perspective on this problem. One of the things that DNA does is specify the hardware of each cell. So the DNA tells every cell what proteins it's supposed to have. And so when you have tadpoles, for example, you see the kind of thing that most people think is sort of a progressive unrolling of the genome. Specific genes turn on and off, and a tadpole, as it becomes a frog, has to rearrange its face. So the eyes, the nostrils, the jaws -- everything has to move. And one way to think about it used to be that, well, you have a sort of hardwired set of movements where all of these things move around and then you get your frog. But actually, a few years ago, we found a pretty amazing phenomenon, which is that if you make so-called "Picasso frogs" -- these are tadpoles where the jaws might be off to the side, the eyes are up here, the nostrils are moved, so everything is shifted -- these tadpoles make largely normal frog faces. Now, this is amazing, because all of the organs start off in abnormal positions, and yet they still end up making a pretty good frog face. And so what it turns out is that this system, like many living systems, is not a hardwired set of movements, but actually works to reduce the error between what's going on now and what it knows is a correct frog face configuration.
ML: Svakako. Da. Želeo bih da vam pružim drugi pogled na ovaj problem. DNK, između ostalog, specifikuje hardver svake ćelije. Dakle, DNK saopštava svakoj ćeliji koje bi proteine trebalo da ima. Stoga, kada imate punoglavce, na primer, vidite baš ono što većina ljudi smatra nekakvim progresivnim odmotavanjem genoma. Naročiti geni se uključuju i isključuju, i punoglavac, kako postaje žaba, mora nanovo da sklopi lice. Oči, nozdrve, vilica - sve mora da se pomeri. A način da se o tome misli je bio, pa dobro, imate nekakav urođen skup pokreta gde se sve ove stvari kreću okolo i daju vam žabu. Zapravo, pre nekoliko godina, otkrili smo prilično neverovatnu pojavu, a to je, ako napravite takozvane Pikaso žabe - radi se o punoglavcima kod kojih vilica može da bude skroz s profila, oči su ovde gore, nozdrve su pomerene, dakle, sve je izmešteno - ovi punoglavci izrastu u uglavnom normalna žablja lica. Sad, ovo je neverovatno jer svi organi započinju na abnormalnim mestima, ipak, i dalje na kraju daju prilično dobra žablja lica. Ispostavlja se da ovaj sistem, poput mnogih živih sistema, nema urođen skup pokreta, već zapravo radi na umanjivanju greške između onoga što se dešava sada i onoga za šta zna da je ispravna konfiguracija žabljeg lica.
This kind of decision-making that involves flexible responses to new circumstances, in other contexts, we would call this intelligence. And so what we need to understand now is not only the mechanisms by which these cells execute their movements and gene expression and so on, but we really have to understand the information flow: How do these cells cooperate with each other to build something large and to stop building when that specific structure is created? And these kinds of computations, not just the mechanisms, but the computations of anatomical control, are the future of biology.
Ovaj vid donošenja odluke, koji podrazumeva fleksibilne odgovore na nove okolnosti, u drugim kontekstima nazivali bismo inteligencijom. Trenutno ne treba samo da razumemo mehanizme po kojima ove ćelije izvode svoje pokrete i ispoljavanje gena itd, već zaista moramo da razumemo tok informacija: kako ove ćelije međusobno sarađuju kako bi izgradile nešto veliko i kako bi prestale da grade kada je ta naročita struktura gotova? A ovi vidovi proračuna, ne samo mehanizmi, već proračuni anatomske kontrole, budućnost su biologije.
CA: And so I guess the traditional model is that somehow cells are sending biochemical signals to each other that allow that development to happen the smart way. But you think there is something else at work. What is that?
KA: Pretpostavljam da je tradicionalni model da ćelije nekako šalju biohemijske signale jedna drugoj koji omogućavaju da se taj razvoj desi na pametan način. Ti, ipak, smatraš da je još nešto na delu. O čemu se radi?
ML: Well, cells certainly do communicate biochemically and via physical forces, but there's something else going on that's extremely interesting, and it's basically called bioelectricity, non-neural bioelectricity. So it turns out that all cells -- not just nerves, but all cells in your body -- communicate with each other using electrical signals. And what you're seeing here is a time-lapse video. For the first time, we are now able to eavesdrop on all of the electrical conversations that the cells are having with each other. So think about this. We're now watching -- This is an early frog embryo. This is about eight hours to 10 hours of development. And the colors are showing you actual electrical states that allow you to see all of the electrical software that's running on the genome-defined cellular hardware. And so these cells are basically communicating with each other who is going to be head, who is going to be tail, who is going to be left and right and make eyes and brain and so on. And so it is this software that allows these living systems to achieve specific goals, goals such as building an embryo or regenerating a limb for animals that do this, and the ability to see these electrical conversations gives us some really remarkable opportunities to target or to rewrite the goals towards which these living systems are operating.
ML: Ćelije svakako komuniciraju biohemijski i putem fizičkih sila, ali još nešto se dešava što je veoma interesantno, a to se u suštini naziva bioelektricitetom, ne-neuronskim bioelektricitetom. Ispostavlja se da sve ćelije - ne samo nervi, već sve ćelije u vašem telu - međusobno komuniciraju upotrebom električnih signala. A ono što vidite ovde je tajm-laps snimak. Prvi put, trenutno smo u mogućnosti da prisluškujemo sve električne razgovore koje ćelije međusobno vode. Razmišljajte o ovome. Upravo gledamo - Ovo je embrion žabe u začetku. Ovo je nakon oko osam do 10 sati razvoja. A boje vam pokazuju stvarna električna stanja koja vam omogućuju da vidite sav električni softver koji radi na ćelijskom hardveru definisanom genomom. Dakle, ove ćelije u suštini razgovaraju jedna s drugom ko će da bude glava, ko će da bude rep, ko će da bude levo i desno i sačinjava oči i mozak, itd. Dakle, ovaj softver omogućava ovim živim sistemima da ostvare specifične ciljeve, poput izgradnje embriona ili regeneracije uda kod životinja koje to mogu, a sposobnost da vidimo ove električne razgovore nam pruža neke prilično izvanredne mogućnosti da ciljamo i nanovo ispisujemo ciljeve prema kojima se ovi sistemi upravljaju.
CA: OK, so this is pretty radical. Let me see if I understand this. What you're saying is that when an organism starts to develop, as soon as a cell divides, electrical signals are shared between them. But as you get to, what, a hundred, a few hundred cells, that somehow these signals end up forming essentially like a computer program, a program that somehow includes all the information needed to tell that organism what its destiny is? Is that the right way to think about it?
KA: U redu. To je prilično radikalno. Sačekaj da vidim da li sam razumeo. Kažeš da kada organizam počne da se razvija, čim se ćelija podeli, električni signali se razmenjuju između njih. Međutim, kad stignemo do stotinu, nekoliko stotina ćelija, nekako ovi signali na kraju tvore nešto u suštini nalik kompjuterskom programu, programu koji nekako uključuje sve potrebne informacije kako bi saopštio organizmu njegovu sudbinu? Je li ovo razmišljanje ispravno?
ML: Yes, quite. Basically, what happens is that these cells, by forming electrical networks much like networks in the brain, they form electrical networks, and these networks process information including pattern memories. They include representation of large-scale anatomical structures where various organs will go, what the different axes of the animal -- front and back, head and tail -- are going to be, and these are literally held in the electrical circuits across large tissues in the same way that brains hold other kinds of memories and learning.
ML: Da, poprilično. U suštini, dešava se da ove ćelije, obrazujući električne mreže nalik mrežama u mozgu, one obrazuju električne mreže, a ove mreže obrađuju informacije uključujući šablonsku memoriju. One uključuju prikaz anatomskih struktura velikih razmera za smeštanje različitih organa, koje ćemo različite ose kod životinje - napred i nazad, glava i rep - da imamo, a ovo je bukvalno sadržano u električnim kolima duž velikih tkiva na isti način na koji mozgovi pohranjuju druge vidove pamćenja i učenja.
CA: So is this the right way to think about it? Because this seems to be such a big shift. I mean, when I first got a computer, I was in awe of the people who could do so-called "machine code," like the direct programming of individual bits in the computer. That was impossible for most mortals. To have a chance of controlling that computer, you'd have to program in a language, which was a vastly simpler way of making big-picture things happen. And if I understand you right, what you're saying is that most of biology today has sort of taken place trying to do the equivalent of machine code programming, of understanding the biochemical signals between individual cells, when, wait a sec, holy crap, there's this language going on, this electrical language, which, if you could understand that, that would give us a completely different set of insights into how organisms are developing. Is that metaphor basically right?
KA: Da li razmišljam ispravno? Jer se ovo čini ogromnim preokretom. Mislim, kad sam prvi put nabavio kompjuter, bio sam očaran ljudima koji su znali tzv. mašinsko programiranje, poput direktnog programiranja pojedinačnih bitova kompjutera. To je bilo nemoguće većini smrtnika. Da bismo mogli da kontrolišemo kompjuter, morali smo da programiramo nekim jezikom, a to je bio daleko jednostavniji način da se dese opštije stvari. I ako te dobro razumem, ti kažeš da se trenutno biologija uglavnom odvija pokušavajući ekvivalent programiranja mašinskim jezikom, razumevajući biohemijske signale između pojedinačnih ćelija, kad, čekaj malo, sveca mu, imamo ovaj jezik, ovaj električni jezik, koji, ako bismo ga razumeli, pružio bi nam skroz drugačiji skup razumevanja o tome kako se organizmi razvijaju. Da li je ova metafora u suštini tačna?
ML: Yeah, this is exactly right. So if you think about the way programming was done in the '40s, in order to get your computer to do something different, you would physically have to shift the wires around. So you'd have to go in there and rewire the hardware. You'd have to interact with the hardware directly, and all of your strategies for manipulating that machine would be at the level of the hardware. And the reason we have this now amazing technology revolution, information sciences and so on, is because computer science moved from a focus on the hardware on to understanding that if your hardware is good enough -- and I'm going to tell you that biological hardware is absolutely good enough -- then you can interact with your system not by tweaking or rewiring the hardware, but actually, you can take a step back and give it stimuli or inputs the way that you would give to a reprogrammable computer and cause the cellular network to do something completely different than it would otherwise have done. So the ability to see these bioelectrical signals is giving us an entry point directly into the software that guides large-scale anatomy, which is a very different approach to medicine than to rewiring specific pathways inside of every cell.
ML: Da, baš tako. Ako se setimo kako je programiranje rađeno tokom ’40-ih, da biste naveli kompjuter da uradi nešto drugačije, morali ste fizički da ispomerate žice. Pa ste morali da uđete i nanovo povežete hardver. Morali ste direktno da interagujete sa hardverom, a sve vaše strategije manipulacije tom mašinom bi bile na nivou hardvera. A razlog što trenutno imamo ovu izvanrednu tehnološku revoluciju, informacijske nauke itd, je što je nauka o kompjuterima preusmerila pažnju sa hardvera na razumevanje da, ako vam je hardver dovoljno dobar - a ja vam kažem da je biološki hardver apsolutno dovoljno dobar - onda možete da interagujete sa sistemom, ne lupkajući i menjajući hardver, već zapravo, možete se povući nazad i dati mu stimulans ili unos na način kako biste to uradili sa rekonfigurišućim kompjuterom navodeći ćelijsku mrežu da uradi nešto sasvim suprotno onome što bi inače uradila. Stoga nam vidljivost ovih biohemijskih signala pruža direktnu ulaznu tačku u softver koji upravlja anatomijom velikih razmera, a to je potpuno različit pristup medicini od ponovnog povezivanja specifičnih prolaza unutar svake ćelije.
CA: And so in many ways, this is the amazingness of your work is that you're starting to crack the code of these electrical signals, and you've got an amazing demonstration of this in these flatworms. Tell us what's going on here.
KA: Dakle, na razne načine, tvoj rad je neverovatan jer ti počinješ da dešifruješ kôd ovih električnih signala, i imaš sjajnu demonstraciju ovoga kod ovih pljosnatih crva. Kaži nam šta se ovde dešava.
ML: So this is a creature known as a planarian. They're flatworms. They're actually quite a complex creature. They have a true brain, lots of different organs and so on. And the amazing thing about these planaria is that they are highly, highly regenerative. So if you cut it into pieces -- in fact, over 200 pieces -- every piece will rebuild exactly what's needed to make a perfect little worm. So think about that. This is a system where every single piece knows exactly what a correct planarian looks like and builds the right organs in the right places and then stops. And that's one of the most amazing things about regeneration. So what we discovered is that if you cut it into three pieces and amputate the head and the tail and you just take this middle fragment, which is what you see here, amazingly, there is an electrical gradient, head to tail, that's generated that tells the piece where the heads and the tails go and in fact, how many heads or tails you're supposed to have. So what we learned to do is to manipulate this electrical gradient, and the important thing is that we don't apply electricity. What we do instead was we turned on and off the little transistors -- they're actual ion channel proteins -- that every cell natively uses to set up this electrical state. So now we have ways to turn them on and off, and when you do this, one of the things you can do is you can shift that circuit to a state that says no, build two heads, or in fact, build no heads. And what you're seeing here are real worms that have either two or no heads that result from this, because that electrical map is what the cells are using to decide what to do.
ML: Ovo je biće poznato kao planarija. Radi se o pljosnatim crvima. Oni su zapravo prilično složena bića. Imaju pravi mozak, mnoštvo različitih organa, itd. A neverovatna stvar kod ovih planarija je da su veoma, veoma regenerativne. Pa, ako je isečeta na komadiće - zapravo, na preko 200 komadića - svaki delić će dograditi tačno šta je neophodno da se sačini savršen crvić. Razmislite o tome. Radi se o sistemu gde svaki delić tačno zna kako prava planarija izgleda i gradi odgovarajuće organe na odgovrajućim mestima i potom staje. A to je nešto najneverovatnije kod regeneracije. Mi smo otkrili da ako je isečemo na tri dela i amputiramo glavu i rep, i samo uzmemo ovaj središnji fragment, a to vidite ovde, iznenađujuće, imamo električni gradijent, od glave do repa, koji nastaje i koji kaže tom delu gde idu glava i rep, i, zapravo, koliko glava ili repova bi trebalo da ima. Mi smo naučili da manipulišemo ovim električnim gradijentom, a važna stvar je da ne upotrebljavamo elektricitet. Umesto toga, uključujemo i isključujemo malene tranzistore - u stvari to je kanal jonskih proteina - koji svaka ćelija izvorno koristi da bi podesila ovo električno stanje. Sada imamo načine da ih uključimo i isključimo, a kada to radite, nešto što možete je da promenite strujno kolo u stanje koje kaže, ne, gradi dve glave, ili, zapravo, gradi bez glave. A ovde vidite stvarne crve koji imaju dve glave ili nijednu koji su rezultat ovoga jer je električna mapa ono što ćelije koriste da bi odlučile šta da rade.
And so what you're seeing here are live two-headed worms. And, having generated these, we did a completely crazy experiment. You take one of these two-headed worms, and you chop off both heads, and you leave just the normal middle fragment. Now keep in mind, these animals have not been genomically edited. There's absolutely nothing different about their genomes. Their genome sequence is completely wild type. So you amputate the heads, you've got a nice normal fragment, and then you ask: In plain water, what is it going to do? And, of course, the standard paradigm would say, well, if you've gotten rid of this ectopic extra tissue, the genome is not edited so it should make a perfectly normal worm. And the amazing thing is that it is not what happens. These worms, when cut again and again, in the future, in plain water, they continue to regenerate as two-headed. Think about this. The pattern memory to which these animals will regenerate after damage has been permanently rewritten. And in fact, we can now write it back and send them back to being one-headed without any genomic editing. So this right here is telling you that the information structure that tells these worms how many heads they're supposed to have is not directly in the genome. It is in this additional bioelectric layer. Probably many other things are as well. And we now have the ability to rewrite it. And that, of course, is the key definition of memory. It has to be stable, long-term stable, and it has to be rewritable. And we are now beginning to crack this morphogenetic code to ask how is it that these tissues store a map of what to do and how we can go in and rewrite that map to new outcomes.
A ovde vidite žive dvoglave crve. Kada smo stvorili sve ovo, obavili smo skroz blesav eksperiment. Uzmete jedan od ovih dvoglavih crva i otkinete obe glave, i ostavite samo normalni središnji fragment. Sad, imajte na umu, ove životinje nisu genomski modifikovane. Apsolutno ništa u vezi s njihovim genomima nije drugačije. Njihov genomski niz je potpuno prirodan. Dakle, amputirate glave, imate fin, normalan fragment, a onda pitate: u običnoj vodi, šta će da se desi? I, naravno, standardna paradigma bi glasila: ako ste se rešili suvišnog ektopičnog tkiva, genom nije redigovan, dakle, trebalo bi da dobijemo skroz normalnog crva. A neverovatno je da se to ne dešava. Ovi crvi, kada se ponovo i ponovo iseku, u budućnosti, u običnoj vodi, nastavljaju da se regenerišu kao dvoglavi. Razmišljajte o ovome. Šablonska memorija po kojoj se ove životinje regenerišu nakon oštećenja je trajno izmenjena. I zapravo, sada možemo da je vratimo na staro i da ih vratimo na jednoglave bez bilo kakve izmene genoma. Ovo ovde vam govori da informaciona struktura koja saopštava ovim crvima koliko glava bi trebalo da imaju nije direktno u genomu. Već je u dodatnom bioelektričnom sloju. Verovatno je i štošta drugo. I mi sada imamo sposobnost da to menjamo. A to je, naravno, osnovna definicija memorije. Mora da bude stabilna, dugoročno stabilna i mora da bude podložna redigovanju. A mi trenutno počinjemo da dešifrujemo ovaj morfogenetički kôd kako bismo ispitali kako ova tkiva skladište uputstva za rad i kako mi možemo da uđemo i da izmenimo uputstva radi novih ishoda.
CA: I mean, that seems incredibly compelling evidence that DNA is just not controlling the actual final shape of these organisms, that there's this whole other thing going on, and, boy, if you could crack that code, what else could that lead to. By the way, just looking at these ones. What is life like for a two-headed flatworm? I mean, it seems like it's kind of a trade-off. The good news is you have this amazing three-dimensional view of the world, but the bad news is you have to poop through both of your mouths?
KA: Mislim, to se čini kao neverovatno ubedljiv dokaz da DNK nije jedina koja kontroliše stvarni krajnji oblik ovih organizama, da imamo nešto potpuno drugo što se dešava i, čoveče, dešifrovanje tog koda do čega bi još dovelo. Usput, samo posmatrajući ove. Kako izgleda život dvoglavog pljosnatog crva? Mislim, čini se kao nagodba. Dobre vesti su da imaju neverovatan trodimenzionalan pogled na svet, ali loše vesti su da moraju da kake kroz oba svoja usta?
ML: So, the worms have these little tubes called pharynxes, and the tubes are sort of in the middle of the body, and they excrete through that. These animals are perfectly viable. They're completely happy, I think. The problem, however, is that the two heads don't cooperate all that well, and so they don't really eat very well. But if you manage to feed them by hand, they will go on forever, and in fact, you should know these worms are basically immortal. So these worms, because they are so highly regenerative, they have no age limit, and they're telling us that if we crack this secret of regeneration, which is not only growing new cells but knowing when to stop -- you see, this is absolutely crucial -- if you can continue to exert this really profound control over the three-dimensional structures that the cells are working towards, you could defeat aging as well as traumatic injury and things like this.
ML: Crvi imaju malene tube koje se nazivaju ždrelom, a tube su otprilike na sredini tela, i kroz njih izbacuju izmet. Ove životninje su skroz održive. U potpunosti su srećne, verujem. Problem je, međutim, što dve glave ne sarađuju tako dobro, pa oni ne jedu tako dobro. Ako, pak, možete rukom da ih hranite, živeće zauvek, i, zapravo, trebalo bi da znate da su ovi crvi praktično besmrtni. Ovi crvi jer su tako izrazito regenrativni, nemaju starosno ograničenje, i saopštavaju nam da ako dešifrujemo njihovu tajnu regeneracije, koja nije samo razvoj novih ćelija, već i znanje kada se zaustaviti - vidite, ovo je apsolutno ključno - ako u kontinuitetu možete da ispoljavate ovu suštinsku kontrolu nad trodimenzionalnim strukturama koje ćelije pokušavaju da postignu, mogli biste da pobedite starost kao i traumatske povrede i slične stvari.
So one thing to keep in mind is that this ability to rewrite the large-scale anatomical structure of the body is not just a weird planarian trick. It's not just something that works in flatworms. What you're seeing here is a tadpole with an eye and a gut, and what we've done is turned on a very specific ion channel. So we basically just manipulated these little electrical transistors that are inside of cells, and we've imposed a state on some of these gut cells that's normally associated with building an eye. And as a result, what the cells do is they build an eye. These eyes are complete. They have optic nerve, lens, retina, all the same stuff that an eye is supposed to have. They can see, by the way, out of these eyes. And what you're seeing here is that by triggering eye-building subroutines in the physiological software of the body, you can very easily tell it to build a complex organ. And this is important for our biomedicine, because we don't know how to micromanage the construction of an eye. I think it's going to be a really long time before we can really bottom-up build things like eyes or hands and so on. But we don't need to, because the body already knows how to do it, and there are these subroutines that can be triggered by specific electrical patterns that we can find. And this is what we call "cracking the bioelectric code." We can make eyes. We can make extra limbs. Here's one of our five-legged tadpoles. We can make extra hearts. We're starting to crack the code to understand where are the subroutines in this software that we can trigger and build these complex organs long before we actually know how to micromanage the process at the cellular level.
Jedna stvar koju treba imati na umu je da mogućnost izmene telesnih anatomskih struktura velikih razmera nije tek uvrnuti trik planarija. Nije nešto što samo deluje kod pljosnatih crva. Ovde vidite punoglavca s okom i crevom, a mi smo uključili veoma specifičan jonski kanal. U suštini smo prosto manipulisali ovim malenim električnim tranzistorima koji su untar ćelija, i nametnuli smo stanje nekim od ovih crevnih ćelija koje je obično povezano sa izgradnjom oka. I kao rezultat, ćelije će sagraditi oko. Ove oči su potpune. Imaju optički nerv, sočivo, mrežnjaču, sve ono što bi oko trebalo da ima. Usput, mogu da vide na ove oči. A ovde vidite da pokrećući subrutine za izgradnju oka u fiziološkom softveru tela, lako mu možete saopštiti da izgradi složen organ. A ovo je važno za našu biomedicinu jer ne znamo kako da do sitnih detalja upravljamo izgradnjom oka. Smatram da će poprilično potrajati pre nego što budemo u stanju da od nule sagradimo oči, ruke itd. Međutim, ne moramo jer telo već zna kako da to uradi i imamo ove subrutine koje mogu da se aktiviraju putem specifičnih električnih nacrta koje možemo da otkrijemo. A to nazivamo „dešifrovanjem biolektričnog koda”. Možemo da pravimo oči, dodatne udove. Ovo je jedan od naših punoglavaca s pet nogu. Možemo da dodamo još jedno srce. Počinjemo da dešifrujemo kôd kako bismo razumeli gde su subrutine u ovom softveru koje možemo da aktiviramo i gradimo ove složene organe mnogo pre nego što zapravo naučimo da detaljno upravljamo procesom na ćelijskom nivou.
CA: So as you've started to get to learn this electrical layer and what it can do, you've been able to create -- is it fair to say it's almost like a new, a novel life-form, called a xenobot? Talk to me about xenobots.
KA: Kada si počeo da izučavaš ovaj električni sloj i šta on sve može, uspeo si da stvoriš - je li u redu reći skoro nov, novi oblik života nazvan ksenobot? Pričaj mi o ksenobotima.
ML: Right. So if you think about this, this leads to a really strange prediction. If the cells are really willing to build towards a specific map, we could take genetically unaltered cells, and what you're seeing here is cells taken out of a frog body. They've coalesced in a way that asks them to re-envision their multicellularity. And what you see here is that when liberated from the rest of the body of the animal, they make these tiny little novel bodies that are, in terms of behavior, you can see they can move, they can run a maze. They are completely different from frogs or tadpoles. Frog cells, when asked to re-envision what kind of body they want to make, do something incredibly interesting. They use the hardware that their genetics gives them, for example, these little hairs, these little cilia that are normally used to redistribute mucus on the outside of a frog, those are genetically specified. But what these creatures did, because the cells are able to form novel kinds of bodies, they have figured out how to use these little cilia to instead row against the water, and now have locomotion. So not only can they move around, but they can, and here what you're seeing, is that these cells are coalescing together. Now they're starting to have conversations about what they are going to do. You can see here the flashes are these exchanges of information. Keep in mind, this is just skin. There is no nervous system. There is no brain. This is just skin. This is skin that has learned to make a new body and to explore its environment and move around. And they have spontaneous behaviors. You can see here where it's swimming down this maze. At this point, it decides to turn around and go back where it came from. So it has its own behavior, and this is a remarkable model system for several reasons. First of all, it shows us the amazing plasticity of cells that are genetically wild type. There is no genetic editing here. These are cells that are really prone to making some sort of functional body.
ML: Tako je. Ako razmišljaš o ovome, ovo vodi do zaista čudnog predviđanja. Ako su ćelije uistinu voljne da grade na osnovu specifične mape, mogli bismo uzeti genetski neizmenjene ćelije, a ovde vidite ćelije uzete iz tela žabe. Spojile su se tako da to od njih zahteva da ponovo zamisle svoju multicelularnost. A ovde vidite da kada se oslobode od ostatka tela životinje, grade ova sićušna nova tela koja, u smislu ponašanja, vidite da mogu da se kreću, da jure po lavirintu. Potpuno su različita od žaba ili punoglavaca. Kada upitamo žablje ćelije da osmisle kakvo telo žele da naprave, one urade nešto krajnje interesantno. Koriste hardver koji im obezbeđuje njihova genetika, na primer, ove malene dlakice, ove malene cilije koje se obično koriste za preraspodelu sluzi na spoljašnjosti žabe, one su genetski određene. Međutim, ova bića, jer su im ćelije u stanju da formiraju nove vrste tela, su otkrila kako da koriste ove malene cilije da umesto toga veslaju uzvodno i ona su sad pokretna. Dakle, ne samo da mogu da se kreću, već mogu, a ovde vidite da se ove ćelije spajaju. Sada započinju razgovore o tome šta će da urade. Ovde vidite svetlucanje, tj. razmenu informacija. Imajte na umu, ovo je samo koža. Nema nervnog sistema. Nema mozga. Ovo je samo koža. Ovo je koža koja je naučila da pravi novo telo, da istražuje okolinu i da se kreće naokolo. I imaju spontana ponašanja. Ovde vidite kako pliva niz lavirint. U ovoj tački, odlučuje da se okrene i vrati odakle je krenula. Dakle, ima sopstveno ponašanje, i radi se o izvanrednom modelu sistema iz više razloga. Pre svega, pokazuje nam neverovatnu plastičnost ćelija koje su genetski neizmenjene. Ovde nema genetske redakcije. Ovo su ćelije koje su zaista sklone gradnji nekakvog funkcionalnog tela.
The second thing, and this was done in collaboration with Josh Bongard's lab at UVM, they modeled the structure of these things and evolved it in a virtual world. So this is literally -- on a computer, they modeled it on a computer. So this is literally the only organism that I know of on the face of this planet whose evolution took place not in the biosphere of the earth but inside a computer. So the individual cells have an evolutionary history, but this organism has never existed before. It was evolved in this virtual world, and then we went ahead and made it in the lab, and you can see this amazing plasticity. This is not only for making useful machines. You can imagine now programming these to go out into the environment and collect toxins and cleanup, or you could imagine ones made out of human cells that would go through your body and collect cancer cells or reshape arthritic joints, deliver pro-regenerative compounds, all kinds of things. But not only these useful applications -- this is an amazing sandbox for learning to communicate morphogenetic signals to cell collectives. So once we crack this, once we understand how these cells decide what to do, and then we're going to, of course, learn to rewrite that information, the next steps are great improvements in regenerative medicine, because we will then be able to tell cells to build healthy organs. And so this is now a really critical opportunity to learn to communicate with cell groups, not to micromanage them, not to force the hardware, to communicate and rewrite the goals that these cells are trying to accomplish.
Druga stvar, a ovo smo radili u saradnji sa Džoš Bongardovom laboratorijom na UVM, radili su modele struktura ovih stvari i evoluirali ih u virtuelnom svetu. Ovo je bukvlano - na kompjuteru, modelirali su ga na kompjuteru. Ovo je bukvalno jedini organizam koji mi je poznat na našoj planeti čija evolucija se nije desila u biosferi zemlje, već unutar kompjutera. Pojedinačne ćelije imaju evolutivnu istoriju, ali ovaj organizam nikad pre nije postojao. Evoluirao je u ovom virtuelnom svetu, a mi smo se onda zaputili i napravili ga u laboratoriji, i vidite ovu izvanrednu plastičnost. Ovo nije samo za izgradnju korisnih mašina. Možete da zamislite kako ih programiramo da izađu u spoljni svet i čiste toksine i prečišćavaju, ili možete da ih zamislite napravljene od ljudskih ćelija koje bi se kretale kroz vaše telo i sakupljale ćelije raka ili bi lečile artritične zglobove, dostavljale proregenerativna jedinjenja, razne stvari. Ne radi se samo o korisnim primenama - ovo je izvanredno igralište za učenje komunikacije morfogenetičkih signala sa ćelijskim kolektivom. Čim ovo dešifrujemo, čim razumemo kako ove ćelije odlučuju šta da rade, onda ćemo, naravno, naučiti da menjamo tu informaciju, sledeći korak su velika unapređenja u regenerativnoj medicini jer ćemo tada biti u stanju da saopštimo ćelijama da grade zdrave organe. Pa je ovo trenutno uistinu ključna šansa da naučimo da komuniciramo sa grupama ćelija, ne da do detalja upravljamo njima, ne da forsiramo hardver, već da komuniciramo i menjamo ciljeve koje ove ćelije pokušavaju da ostvare.
CA: Well, it's mind-boggling stuff. Finally, Mike, give us just one other story about medicine that might be to come as you develop this understanding of how this bioelectric layer works.
KA: Radi se o stvarima koje raspamećuju. Za kraj, Majk, reci nam samo još jednu priču o medicini koja bi mogla da nastane dok ti razvijaš razumevanje o tome kako ovaj bioelektrični sloj deluje.
ML: Yeah, this is incredibly exciting because, if you think about it, most of the problems of biomedicine -- birth defects, degenerative disease, aging, traumatic injury, even cancer -- all boil down to one thing: cells are not building what you would like them to build. And so if we understood how to communicate with these collectives and really rewrite their target morphologies, we would be able to normalize tumors, we would be able to repair birth defects, induce regeneration of limbs and other organs, and these are things we have already done in frog models. And so now the next really exciting step is to take this into mammalian cells and to really turn this into the next generation of regenerative medicine where we learn to address all of these biomedical needs by communicating with the cell collectives and rewriting their bioelectric pattern memories. And the final thing I'd like to say is that the importance of this field is not only for biomedicine. You see, this, as I started out by saying, this ability of cells in novel environments to build all kinds of things besides what their genome tells them is an example of intelligence, and biology has been intelligently solving problems long before brains came on the scene. And so this is also the beginnings of a new inspiration for machine learning that mimics the artificial intelligence of body cells, not just brains, for applications in computer intelligence.
ML: Da, ovo je izuzetno uzbudljivo jer, ako razmisliš o tome, većina problema u biomedicini - urođeni defekti, degenerativne bolesti, starenje, traumatske povrede, čak i rak - sve se svode na jedno: ćelije ne grade što biste želeli da grade. Stoga, ako bismo razumeli kako da komuniciramo sa ovim kolektivima i da zaista menjamo njihove ciljne morfologije, bili bismo u stanju da normalizujemo tumore, da popravljamo urođene defekte, da pokrećemo regeneraciju udova i drugih organa, a ovo smo sve već uradili na žabljim modelima. Pa je sad sledeći zaista uzbudljiv korak da ovo prenesemo na ćelije sisara i da ovo uistinu pretvorimo u sledeću generaciju regenerativne medicine gde učimo da se bavimo svim ovim biomedicinskim potrebama komunicirajući sa ćelijskim kolektivima i menjajući njihovu bioelektričnu šablonsku memoriju. I posljednje što bih želeo da kažem je da se važnost ove oblasti ne ogleda samo u biomedicini. Vidite, kao što sam rekao na početku, ova sposobnost ćelija u novim sredinama da grade svakakve stvari pored onog što im genom saopštava je primer inteligencije, a biologija je inteligentno rešavala probleme još mnogo pre pojave mozgova. Pa su ovo i počeci nove inspiracije za mašinsko učenje koje oponaša veštačku inteligenciju telesnih ćelija, ne samo mozgova, za primene u kompjuterskoj inteligenciji.
CA: Mike Levin, thank you for your extraordinary work and for sharing it so compellingly with us. Thank you.
KA: Majk Levin, hvala ti za tvoj izuzetan rad i što si ga tako ubedljivo podelio sa nama. Hvala ti.
ML: Thank you so much. Thank you, Chris.
ML: Mnogo vam hvala. Hvala, Kris.