Chris Anderson: Mike, welcome. It's good to see you. I'm excited for this conversation.
克里斯·安德森:迈克,欢迎你。 很高兴见到你。 我很期待接下来的讨论。
Michael Levin: Thank you so much. I'm so happy to be here.
迈克尔·列文:非常感谢。 我也很高兴来到这里。
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?
安德森:大多数人脑海里 对生物学有这样的概念模型, 就是DNA是所有生物的一种属性, 它好像电脑软件一样, 指引我们搭建出身体这个硬件。 很多人都是这样想的。 这种模型引出了很多很深的谜团。 你可以向我们分享这些谜团吗? 顺便提一提它们与小蝌蚪之间的关系。
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.
列文:当然,没问题。 我想分享的是这个问题的另一个角度。 DNA的一个功能是 指定每个细胞所含的硬件。 所以DNA告诉每个细胞, 它们应该含有哪些蛋白质。 比如我们研究蝌蚪, 你会发现这种现象, 大多数人会觉得是 基因组的“阶段性展开”。 特定的基因会激活或者休眠, 当蝌蚪发育成青蛙时, 它会重新组合脸部器官。 比如眼睛、鼻孔、下巴, 各种东西都移动了。 过去解读这种现象的一种方式是 你有一系列固定的移动路线, 这些器官按照给定路线移动, 于是就形成了青蛙。 但事实上,就几年前, 我们发现了一个很了不起的现象, 就是当我们研究所谓的 “毕加索青蛙”—— 这指的是一些蝌蚪比如说下巴长歪了, 眼睛跑到顶上,鼻孔也长偏了, 总之各种东西位置不对—— 这些蝌蚪依然能发育出 大致正常的蛙脸。 那么这就很厉害了, 因为所有器官的起始位置都不正常, 然而最后还能长成比较正常的蛙脸。 所以我们发觉这样一个系统, 很像其他的生物系统, 它不是一系列固定的路线, 而是可以努力降低从当前状态 发展到它所知的正确蛙脸状态的误差。
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.
这种决策能力 涉及到如何灵活应对各种新情况, 放在其他领域, 我们会称之为智能、智慧。 那么我们需要理解的就不只是 这些细胞移动的机制, 或者基因表达之类的, 我们更要理解信息在其中的流向: 这些细胞如何互相沟通 以构建大规模机体, 并且在构建完成时 知道应该停止构建。 这种运算过程,不仅是机制, 而是解剖学控制的精密计算, 是生物学未来的研究方向。
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?
安德森:那么我感觉传统的模型是说 细胞之间会互相传递生物化学信号 使得生物体发育能够 灵活、有智能地进行。 不过你认为还有其它的机制在起作用。 那是什么呢?
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.
列文:细胞肯定会通过生物化学信号 以及物理力的作用进行沟通, 但还有另外一个机制是非常有趣的, 它叫做生物电, 而且是非神经传导的生物电。 其实所有的细胞—— 不只是神经细胞,而是全身所有的细胞—— 都用电信号来进行相互交流。 这里看到的是一段延时摄影片段。 历史上第一次, 我们能够窃听细胞与细胞之间 用电信号进行的所有对话。 所以想想看。 我们现在看到的—— 这是青蛙的一个早期胚胎。 这大概是发育的前 8 到 10 小时。 这里的颜色代表着实际的电位, 这让我们看到所有的电流“软件”, 在由基因组所定义的细胞“硬件”上 执行的样子。 简单来说,这些细胞就在互相沟通: 哪些应该形成头部, 哪些应该形成尾部, 哪些去左边、去右边, 哪些应该形成眼睛、大脑等等。 其实是这种软件 使得生物体去实现特定的目标, 比如搭建一个胚胎, 或者是有再生能力的动物 修复损伤的肢体, 我们有能力观察到这些电信号对话, 这给了我们一些重大机会, 让我们引导甚至是重写生物体 想要达到的各种目标。
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?
安德森:好的,听起来太厉害了。 你看看我理解的对不对。 你说的是,当有机体开始发育的时候, 每当一个细胞分裂时, 电信号都在细胞之间传递。 但当你发展到一百个、 几百个细胞级别时, 这些信号就不知怎么 变成像电脑程序一样, 这个程序就包含了 有机体所需的所有信息, 告诉这个有机体 发展的结局是什么? 你觉得我理解的对吗?
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.
列文:对的,差不多。 简单解释就是这些细胞 通过组成电信号网络, 很像大脑里的神经, 它们组成这种网络, 然后这些网络可以处理信息 并记忆一些模板。 这些模板包含了 大规模解剖学结构的蓝图, 比如各种器官该长在哪里, 各种动物的方向性—— 哪里是前是后,哪里是头是尾—— 应该怎么安排, 这些信息就储存在电路中, 横跨大块的组织, 与大脑储存各种信息、 学习知识的方式一样。
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?
安德森:所以这种理解是对的吗? 因为我感觉这种转变很大。 我指的是,当我有了 自己的第一台电脑时, 我特别佩服一些程序员 可以写所谓“机器语言”, 就是直接去操纵电脑的每一个字节。 大多数人是不可能做到的。 如果想要操控那台电脑, 你必须要会这种编程语言, 用最底层、最简洁的方式 去实现大规模的复杂功能。 如果我理解得对, 你所描述的就是现阶段的生物学 就在努力实现用类似 “机器代码”的方式编程, 尝试理解各个细胞之间的 生物化学信号, 但突然,我的天啊, 出现了这么个新语言, 这个生物电的语言, 如果你们能研究明白的话, 会让我们站在完全不一样的视角, 去理解生物体的发育发展。 这个类比你觉得对吗?
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.
列文:对的,完全正确。 回想1940年代,大家是怎么编程的, 如果你想让电脑实现不同功能, 那就得手动插拔各种电线。 你得钻进机箱里去 重接电脑硬件的连线。 你要这样直接操纵硬件, 而且所有控制电脑的方式 都是在硬件级别的。 我们现在有如此惊人的技术革新, 尤其信息科学相关领域, 就是因为计算机科学不只是关注硬件, 而是在硬件足够好的条件下, 转为关注—— 这里插一句话, 生物体的硬件绝对是足够好的—— 你与系统的互动方式, 不通过调整或重新布线硬件, 而是可以退一步, 给系统加入某种刺激或输入, 就好像你给可编程的电脑 输入信息一样, 这样使得整个细胞网络去实现 没有外界刺激情况下不会去做的任务。 因此我们能够观察到生物电信号 给我们一个入口, 给我们一个直接进入 指导大规模解剖的软件的入口, 是很不一样趋近医学的方式, 与重新连接每个细胞的方式大不相同。
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.
安德森:所以说从各个角度看, 这就是你们科研成果很了不起之处, 是你们开始破译这种电信号的密码, 你有一个很神奇的例子 是关于扁虫的。 请给我们解释一下。
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.
列文:这种生物名叫涡虫。 它属于扁形动物门。 它们其实结构很复杂。 它们有完整的大脑, 有各种不同的器官。 这些涡虫厉害的地方在于 它们的再生能力极强。 所以如果你把它切成小段—— 事实上,超过200个小段—— 每一段都可以再生出 其所需的一切部件, 恢复成完整的小虫。 大家揣摩揣摩。 这个系统里的每一小块, 都清楚地知道 一只正常的涡虫长什么样, 把所有需要的器官 长在正确的位置,然后停止生长。 这是生物再生最了不起的事情之一。 我们发现一个现象, 就是如果你把它切成三段, 就是把头部和尾部切除, 只留下中间那段, 就是画面中看到的, 神奇的现象是,虫的头部到尾部 展现出生物电位的梯度, 告诉这一小段身体头部和尾部 应该长在哪里, 其实还表示了应该长出 几个头和几条尾巴。 所以我们就想到去改变这个电位梯度, 然而重要的是我们并不直接输入电流。 我们做的实际是把细胞上的 小电容器打开或关闭—— 其实是用作离子通道的蛋白质—— 细胞原本就利用这些蛋白质 来调控电位状态。 于是我们就有办法开关这些电容器, 如此调整的话,可以做的事情是 你把细胞电路调到一个状态, 让他发育出两个头来, 或者是一个头也不发育。 画面看到的就是真实的涡虫, 有两个头的,也有无头的, 就是这么调整得来的, 因为细胞就是用那个电位图来 决定怎么生长的。
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.
这里所看到的就是活的双头涡虫。 发育了这些涡虫之后, 我们又做了另一个疯狂的实验。 就是你切除一只双头涡虫的两个头, 只留下中间的那一段。 提醒一下,我们从未编辑过 这些动物的基因。 它们的基因组与自然的涡虫没有差别。 它们的基因组序列就是野生型的。 所以如果你切除两个头, 获得了一段正常的中间段, 然后你就想问: 在清水里它会怎样再生? 如果按照传统惯例,你肯定会说 既然我们移除了这段异位的组织, 然后基因组也没改变, 它应该会长成完全正常的涡虫。 然而了不起的是,结果并不是这样的。 这些虫子不论切多少次, 之后在清水里 它们依然会再生成双头的涡虫。 大家想想看。 这些动物受到损伤后再生的模板 已经被永久改写了。 事实上,我们也可以把它改写回原状, 让它们变回一个头, 这都无需经过基因剪辑。 通过这个现象,大家就知道 涡虫应该长出多少个头的信息架构 并不直接储存在基因组里。 它其实储存在这个额外的生物电层。 可能很多其他信息也是这样。 而且我们现在有能力改写它了。 而这其实就是“记忆”的关键标准。 它必须是稳定的,长久稳定的, 而且可被覆写的。 我们逐渐学会破解 这种生物发育的密码, 慢慢理解这些组织 如何储存发育指令的信息, 以及我们如何能够改写这些信息, 引导出全新的结果。
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?
安德森:我觉得 这是非常有信服力的证据, 说明DNA并不是真正控制这些生物体 最终形态的, 实际上还有这个完全独立的作用, 天啊,如果你们可以破解的话 想想可以实现什么。 哦对了,我看这些虫子。 这种双头的涡虫是怎样生活的呢? 我感觉看起来像是有利有弊。 好的一面是能用三维的方式观察世界, 坏的一面大概是 要从两个头的嘴里排泄?
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.
列文:这些虫子长有这些小管子 叫做咽管, 这些管子长在身体中间, 它们会从咽管排遗。 这些动物完全可以生存。 我觉得它们也挺开心吧。 但有个问题是 它们的两个头配合得不是很好, 所以它们吃东西有一定困难。 如果你自己动手去喂它们的话, 它们就可以一直活下去, 其实你可能想象到, 这些虫子基本上是永生的。 这些虫子因为具有极强的再生能力, 它们就没有年龄限制, 然后它们告诉我们, 如果能破解再生的秘密, 这指的不仅是长出新细胞, 而且也指知道如何停止—— 这一点其实非常重要—— 如果可以不断通过细胞 对生物的三维结构加以精密的控制, 你就可以击败衰老或是严重的创伤, 以及类似的损伤。
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.
我们要记住的一点是, 这种改写身体大规模解剖结构的能力 并不只是涡虫身上的小把戏。 不是说只能在扁虫上才起作用。 这里所看到的蝌蚪肠子上长了一个眼睛, 我们所做的就是 打开了一个特定的离子通道。 简单来说,我们就是调整了细胞里的 那些小电容器, 我们把肠子上的某些细胞 调整为特定的电位, 而这种电位一般和眼睛的生长有关。 于是细胞所做的就是搭建了一个眼睛。 这些眼睛都结构完整。 它们有视神经、晶状体、角膜, 正常眼球所有的一切它都有。 而且这些眼睛都是有视觉的。 你在这里看到的 就是我们通过调整蝌蚪的生理软件, 触发了搭建眼睛的“子程序”, 你可以很容易的让生物 搭建出复杂的器官。 这对生物医学是非常关键的, 因为我们还不知道 如何一步搭建出一个眼睛。 我觉得我们需要很长时间 才能搞清楚如何从无到有 组建出眼睛、手之类的器官。 但我们并不需要知道, 因为我们的身体自然就知道如何搭建, 而且也有这些可以手动激活的子程序, 通过我们观察到的电位图来激活。 这就是我们所说的“破解生物电的密码”。 我们可以造出眼睛,造出肢体。 这是我们培养出的五条腿的蝌蚪。 我们可以造出好几个心脏。 我们开始破解密码,逐渐理解 这个软件里的子程序都在哪里, 可以让我们触发并组建出复杂器官, 远早于我们真正学会一步步 从细胞级别开始组建。
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.
安德森:那么你们开始 了解这个生物电层, 以及它的功能, 你们就可以创造—— 一种全新的生物形态,可以这么说吗? 叫做“活体机器人”? 请给我介绍一下活体机器人。
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.
列文:好的。 你想想看,这引出了一种 非常奇怪的预测。 如果细胞倾向于往某种蓝图去搭建, 我们就可以分离出 未经过基因编辑的细胞, 这里看到的就是从青蛙体内取出的细胞。 它们聚集在一起的样子 似乎像是在预想出多细胞的状态。 画面中所看到的 就是当细胞从动物体分离出来之后, 它们聚集成这些微小的新结构体, 从它们的行为来说, 这里看到它们会移动、会走迷宫。 这些结构体与青蛙或蝌蚪完全不一样。 当我们让青蛙细胞 这样预想出身体构建的蓝图, 它们就会做神奇的事情。 它们用基因所赋予的硬件, 比如这些细小的毛发, 原本是拿来分配青蛙表皮的粘液的, 这些是基因所定义好的。 这些小生物所做的, 因为这些细胞可以聚集形成新的机体, 它们就发觉如何利用这些小毛发 在水里划动,于是就有了运动能力。 所以它们不仅能到处移动, 还可以像图中看到的, 它们会自动聚集在一起。 它们现在在互相交流, 讨论接下来要做什么。 你们可以看到这些小闪光 就是信息的交换。 提醒一下,这只是皮肤细胞而已。 没有神经系统,没有大脑。 只是皮肤细胞。 光皮肤细胞就知道 如何聚集形成新机体, 并且如何移动、探索周围的环境。 它们也展现出一些自发行为。 比如这里可以看到它们在迷宫里游动。 走到这里,它又决定调头往反方向走。 它们有自己的行为, 而这就是一个非常厉害的模型系统, 原因有以下几个。 首先,它告诉我们野生型的细胞 也有很了不起的可塑性。 我们没有编辑过基因。 这些细胞能很容易组建出 具有特定功能的结构体。
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.
第二点是, 这是我们和佛蒙特大学 约什·邦嘉德教授实验室合作的成果, 他们把这些生物的结构建模, 放在虚拟环境里使其演化。 这个就确实是——在电脑里了, 是他们做的计算机模拟。 这确实是我所知的, 地球上唯一的有机体, 它的进化不是在地球生物圈中进行的, 而是在电脑程序里进行的。 这里每一个细胞都有自己的进化史, 但是这个有机体从未真实存在过。 它是在虚拟世界里演化的, 然后我们再在实验室里把它们造出来, 你也可以观察到很强的可塑性。 这不只是说生产出有用的活体机械。 你可以想象,如果我们把这些细胞 编程并放到环境里, 它们可以收集毒素、做清扫, 或者也可以想象人体细胞造出的机械 会在身体里游走并清理癌细胞, 或是重组关节炎患者的关节, 传递促进再生的化合物, 各种各样的事情。 但它不止有这些应用—— 它还是一个很了不起的试验场, 让我们学习用生物发育的信号 与细胞组织对话。 一旦我们破解了,一旦我们理解 这些细胞如何决定做什么事, 之后我们肯定就会学着 去改写这些信息, 那么下一步就是再生医学的突破, 因为我们可以让细胞 直接造出健康的器官。 这是目前一个非常重要的机遇, 去学习与细胞组织交流, 不是对他们微管理, 也不是强行改变硬件, 而是交流、改写细胞所想实现的目标。
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.
安德森:好的,听起来太惊人了。 最后,迈克,请你分享最后一个故事, 是关于未来可能出现的医药, 随着你们逐渐增进 对这个生物电层的理解。
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.
列文:好的,这其实非常激动人心, 如果你想想看, 生物医学现在的诸多问题—— 比如先天缺陷、退化性疾病、衰老、 重大创伤,乃至癌症—— 它们说白了都是一件事: 细胞没按照你想要的的方式 去组建东西。 那么如果我们理解 如何与细胞聚集体沟通, 然后重写它们的发育目标, 我们就可以化解肿瘤, 我们可以修复先天缺陷, 可以促成肢体或其它器官的再生, 而这些事情都在青蛙模型上实现了。 那么接下来激动人心的一步 就是把这些引入到哺乳动物细胞中, 真正把它转化为 新一代的再生医学成果, 我们从此学会应对 生物医学的各种需求, 通过与细胞团体进行沟通, 并重写它们的生物电所记忆的模板。 最后我想提的一点是这个领域的重要性 不只停留在生物医学。 回想我一开始就说到, 细胞在各种新环境里 除了基因组的指令之外, 还能搭建新东西的能力, 是智能、智慧的体现, 而且生物学早就开始 很有智慧地解决问题, 远早于动物大脑的发育、形成。 这些也可以给机器学习领域 带来全新的启发, 让算法去模仿这些身体细胞, 而不仅是大脑, 开拓计算机智能的全新应用。
CA: Mike Levin, thank you for your extraordinary work and for sharing it so compellingly with us. Thank you.
安德森:迈克·列文, 感谢你们做出的卓越贡献, 也感谢你如此热情洋溢地与我们分享。 谢谢你。
ML: Thank you so much. Thank you, Chris.
列文:非常感谢。谢谢你,克里斯。