Michael Levin: The electrical blueprints that orchestrate life | TED

翻译人员: Hancheng Li 校对人员: Helen Chang

Chris Anderson: Mike, welcome.

克里斯·安德森：迈克，欢迎你。

It's good to see you. I'm excited for this conversation.

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。

安德森：大多数人脑海里 对生物学有这样的概念模型，

CA: So, most of us have this mental model in biology

that DNA is a property of every living thing,

就是DNA是所有生物的一种属性，

that it is kind of the software that builds the hardware of our body.

它好像电脑软件一样， 指引我们搭建出身体这个硬件。

That's how a lot of us think about this.

很多人都是这样想的。

That model leaves too many deep mysteries.

这种模型引出了很多很深的谜团。

Can you share with us some of those mysteries

你可以向我们分享这些谜团吗？

and also what tadpoles have to do with it?

顺便提一提它们与小蝌蚪之间的关系。

ML: Sure. Yeah.

列文：当然，没问题。

I'd like to give you another perspective on this problem.

我想分享的是这个问题的另一个角度。

One of the things that DNA does is specify the hardware of each cell.

DNA的一个功能是 指定每个细胞所含的硬件。

So the DNA tells every cell what proteins it's supposed to have.

所以DNA告诉每个细胞， 它们应该含有哪些蛋白质。

And so when you have tadpoles, for example,

比如我们研究蝌蚪，

you see the kind of thing

你会发现这种现象，

that most people think is sort of a progressive unrolling of the genome.

大多数人会觉得是 基因组的“阶段性展开”。

Specific genes turn on and off,

特定的基因会激活或者休眠，

and a tadpole, as it becomes a frog,

当蝌蚪发育成青蛙时，

has to rearrange its face.

它会重新组合脸部器官。

So the eyes, the nostrils, the jaws -- everything has to move.

比如眼睛、鼻孔、下巴， 各种东西都移动了。

And one way to think about it used to be that, well,

过去解读这种现象的一种方式是

you have a sort of hardwired set of movements

你有一系列固定的移动路线，

where all of these things move around and then you get your frog.

这些器官按照给定路线移动， 于是就形成了青蛙。

But actually, a few years ago, we found a pretty amazing phenomenon,

但事实上，就几年前， 我们发现了一个很了不起的现象，

which is that if you make so-called "Picasso frogs" --

就是当我们研究所谓的 “毕加索青蛙”——

these are tadpoles where the jaws might be off to the side,

这指的是一些蝌蚪比如说下巴长歪了，

the eyes are up here, the nostrils are moved,

眼睛跑到顶上，鼻孔也长偏了，

so everything is shifted --

总之各种东西位置不对——

these tadpoles make largely normal frog faces.

这些蝌蚪依然能发育出 大致正常的蛙脸。

Now, this is amazing,

那么这就很厉害了，

因为所有器官的起始位置都不正常，

because all of the organs start off in abnormal positions,

and yet they still end up making a pretty good frog face.

然而最后还能长成比较正常的蛙脸。

And so what it turns out is that this system,

所以我们发觉这样一个系统，

like many living systems,

很像其他的生物系统，

is not a hardwired set of movements,

它不是一系列固定的路线，

but actually works to reduce the error between what's going on now

而是可以努力降低从当前状态

and what it knows is a correct frog face configuration.

发展到它所知的正确蛙脸状态的误差。

This kind of decision-making

这种决策能力

that involves flexible responses to new circumstances,

涉及到如何灵活应对各种新情况，

in other contexts, we would call this intelligence.

放在其他领域， 我们会称之为智能、智慧。

And so what we need to understand now is not only the mechanisms

那么我们需要理解的就不只是

这些细胞移动的机制，

by which these cells execute their movements

and gene expression and so on,

或者基因表达之类的，

but we really have to understand the information flow:

我们更要理解信息在其中的流向：

How do these cells cooperate with each other

这些细胞如何互相沟通

to build something large and to stop building

以构建大规模机体，

并且在构建完成时 知道应该停止构建。

when that specific structure is created?

And these kinds of computations, not just the mechanisms,

这种运算过程，不仅是机制，

but the computations of anatomical control,

而是解剖学控制的精密计算，

are the future of biology.

是生物学未来的研究方向。

CA: And so I guess the traditional model

安德森：那么我感觉传统的模型是说

is that somehow cells are sending biochemical signals to each other

细胞之间会互相传递生物化学信号

that allow that development to happen the smart way.

使得生物体发育能够 灵活、有智能地进行。

But you think there is something else at work.

不过你认为还有其它的机制在起作用。

What is that?

那是什么呢？

ML: Well, cells certainly do communicate biochemically and via physical forces,

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，

but there's something else going on that's extremely interesting,

它叫做生物电，

and it's basically called bioelectricity,

non-neural bioelectricity.

而且是非神经传导的生物电。

So it turns out that all cells --

其实所有的细胞——

not just nerves, but all cells in your body --

不只是神经细胞，而是全身所有的细胞——

communicate with each other using electrical signals.

都用电信号来进行相互交流。

And what you're seeing here is a time-lapse video.

这里看到的是一段延时摄影片段。

For the first time,

历史上第一次，

we are now able to eavesdrop on all of the electrical conversations

我们能够窃听细胞与细胞之间

that the cells are having with each other.

用电信号进行的所有对话。

So think about this.

所以想想看。

We're now watching --

我们现在看到的——

This is an early frog embryo.

这是青蛙的一个早期胚胎。

This is about eight hours to 10 hours of development.

这大概是发育的前 8 到 10 小时。

And the colors are showing you actual electrical states

这里的颜色代表着实际的电位，

that allow you to see all of the electrical software

这让我们看到所有的电流“软件”，

that's running on the genome-defined cellular hardware.

在由基因组所定义的细胞“硬件”上 执行的样子。

And so these cells are basically communicating with each other

简单来说，这些细胞就在互相沟通：

who is going to be head, who is going to be tail,

哪些应该形成头部， 哪些应该形成尾部，

who is going to be left and right and make eyes and brain and so on.

哪些去左边、去右边， 哪些应该形成眼睛、大脑等等。

And so it is this software

其实是这种软件

that allows these living systems to achieve specific goals,

使得生物体去实现特定的目标，

goals such as building an embryo

比如搭建一个胚胎，

or regenerating a limb for animals that do this,

或者是有再生能力的动物 修复损伤的肢体，

and the ability to see these electrical conversations

我们有能力观察到这些电信号对话，

gives us some really remarkable opportunities

这给了我们一些重大机会，

to target or to rewrite the goals towards which

让我们引导甚至是重写生物体

these living systems are operating.

想要达到的各种目标。

CA: OK, so this is pretty radical.

安德森：好的，听起来太厉害了。

Let me see if I understand this.

你看看我理解的对不对。

What you're saying is that when an organism starts to develop,

你说的是，当有机体开始发育的时候，

as soon as a cell divides,

每当一个细胞分裂时，

electrical signals are shared between them.

电信号都在细胞之间传递。

But as you get to, what, a hundred, a few hundred cells,

但当你发展到一百个、 几百个细胞级别时，

that somehow these signals end up forming essentially like a computer program,

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，

a program that somehow includes all the information needed

to tell that organism

告诉这个有机体

what its destiny is?

发展的结局是什么？

Is that the right way to think about it?

你觉得我理解的对吗？

ML: Yes, quite.

列文：对的，差不多。

Basically, what happens is that these cells,

简单解释就是这些细胞

by forming electrical networks much like networks in the brain,

通过组成电信号网络， 很像大脑里的神经，

they form electrical networks,

它们组成这种网络，

and these networks process information including pattern memories.

然后这些网络可以处理信息 并记忆一些模板。

They include representation of large-scale anatomical structures

这些模板包含了 大规模解剖学结构的蓝图，

where various organs will go,

比如各种器官该长在哪里，

what the different axes of the animal -- front and back, head and tail --

各种动物的方向性—— 哪里是前是后，哪里是头是尾——

are going to be,

应该怎么安排，

and these are literally held in the electrical circuits

这些信息就储存在电路中，

across large tissues

横跨大块的组织，

in the same way that brains hold other kinds of memories and learning.

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?

安德森：所以这种理解是对的吗？

Because this seems to be such a big shift.

因为我感觉这种转变很大。

I mean, when I first got a computer,

我指的是，当我有了 自己的第一台电脑时，

I was in awe of the people who could do so-called "machine code,"

我特别佩服一些程序员 可以写所谓“机器语言”，

like the direct programming of individual bits in the computer.

就是直接去操纵电脑的每一个字节。

That was impossible for most mortals.

大多数人是不可能做到的。

To have a chance of controlling that computer,

如果想要操控那台电脑，

你必须要会这种编程语言，

you'd have to program in a language,

which was a vastly simpler way of making big-picture things happen.

用最底层、最简洁的方式 去实现大规模的复杂功能。

And if I understand you right,

如果我理解得对，

what you're saying is that most of biology today has sort of taken place

你所描述的就是现阶段的生物学

trying to do the equivalent of machine code programming,

就在努力实现用类似 “机器代码”的方式编程，

of understanding the biochemical signals between individual cells,

尝试理解各个细胞之间的 生物化学信号，

when, wait a sec, holy crap, there's this language going on,

但突然，我的天啊， 出现了这么个新语言，

this electrical language, which, if you could understand that,

这个生物电的语言， 如果你们能研究明白的话，

that would give us a completely different set of insights

会让我们站在完全不一样的视角，

into how organisms are developing.

去理解生物体的发育发展。

Is that metaphor basically right?

这个类比你觉得对吗？

ML: Yeah, this is exactly right.

列文：对的，完全正确。

So if you think about the way programming was done in the '40s,

回想1940年代，大家是怎么编程的，

in order to get your computer to do something different,

如果你想让电脑实现不同功能，

那就得手动插拔各种电线。

you would physically have to shift the wires around.

你得钻进机箱里去 重接电脑硬件的连线。

So you'd have to go in there and rewire the hardware.

你要这样直接操纵硬件，

You'd have to interact with the hardware directly,

and all of your strategies for manipulating that machine

而且所有控制电脑的方式

would be at the level of the hardware.

都是在硬件级别的。

And the reason we have this now amazing technology revolution,

我们现在有如此惊人的技术革新，

information sciences and so on,

尤其信息科学相关领域，

is because computer science moved from a focus on the hardware

就是因为计算机科学不只是关注硬件，

on to understanding that if your hardware is good enough --

而是在硬件足够好的条件下， 转为关注——

and I'm going to tell you that biological hardware is absolutely good enough --

这里插一句话， 生物体的硬件绝对是足够好的——

then you can interact with your system not by tweaking or rewiring the hardware,

你与系统的互动方式， 不通过调整或重新布线硬件，

but actually, you can take a step back and give it stimuli or inputs

而是可以退一步， 给系统加入某种刺激或输入，

the way that you would give to a reprogrammable computer

就好像你给可编程的电脑 输入信息一样，

and cause the cellular network to do something completely different

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。

than it would otherwise have done.

So the ability to see these bioelectrical signals

因此我们能够观察到生物电信号

is giving us an entry point directly into the software

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，

that guides large-scale anatomy,

which is a very different approach to medicine

是很不一样趋近医学的方式，

than to rewiring specific pathways inside of every cell.

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

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，

is that you're starting to crack the code of these electrical signals,

是你们开始破译这种电信号的密码，

and you've got an amazing demonstration of this

你有一个很神奇的例子

in these flatworms.

是关于扁虫的。

Tell us what's going on here.

请给我们解释一下。

ML: So this is a creature known as a planarian.

列文：这种生物名叫涡虫。

They're flatworms.

它属于扁形动物门。

They're actually quite a complex creature.

它们其实结构很复杂。

They have a true brain, lots of different organs and so on.

它们有完整的大脑， 有各种不同的器官。

And the amazing thing about these planaria

这些涡虫厉害的地方在于

is that they are highly, highly regenerative.

它们的再生能力极强。

So if you cut it into pieces -- in fact, over 200 pieces --

所以如果你把它切成小段—— 事实上，超过200个小段——

every piece will rebuild exactly what's needed

每一段都可以再生出 其所需的一切部件，

to make a perfect little worm.

恢复成完整的小虫。

So think about that.

大家揣摩揣摩。

This is a system where every single piece

这个系统里的每一小块，

knows exactly what a correct planarian looks like

都清楚地知道 一只正常的涡虫长什么样，

and builds the right organs in the right places and then stops.

把所有需要的器官 长在正确的位置，然后停止生长。

And that's one of the most amazing things about regeneration.

这是生物再生最了不起的事情之一。

So what we discovered is that if you cut it into three pieces

我们发现一个现象， 就是如果你把它切成三段，

and amputate the head and the tail and you just take this middle fragment,

就是把头部和尾部切除， 只留下中间那段，

which is what you see here,

就是画面中看到的，

amazingly, there is an electrical gradient, head to tail, that's generated

神奇的现象是，虫的头部到尾部 展现出生物电位的梯度，

that tells the piece where the heads and the tails go

告诉这一小段身体头部和尾部 应该长在哪里，

and in fact, how many heads or tails you're supposed to have.

其实还表示了应该长出 几个头和几条尾巴。

So what we learned to do is to manipulate this electrical gradient,

所以我们就想到去改变这个电位梯度，

and the important thing is that we don't apply electricity.

然而重要的是我们并不直接输入电流。

What we do instead was we turned on and off the little transistors --

我们做的实际是把细胞上的 小电容器打开或关闭——

they're actual ion channel proteins --

其实是用作离子通道的蛋白质——

that every cell natively uses to set up this electrical state.

细胞原本就利用这些蛋白质 来调控电位状态。

So now we have ways to turn them on and off,

于是我们就有办法开关这些电容器，

and when you do this, one of the things you can do

如此调整的话，可以做的事情是

is you can shift that circuit to a state that says no, build two heads,

你把细胞电路调到一个状态， 让他发育出两个头来，

or in fact, build no heads.

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，

And what you're seeing here are real worms that have either two or no heads

that result from this,

就是这么调整得来的，

because that electrical map is what the cells are using

因为细胞就是用那个电位图来

to decide what to do.

决定怎么生长的。

And so what you're seeing here are live two-headed worms.

这里所看到的就是活的双头涡虫。

And, having generated these, we did a completely crazy experiment.

发育了这些涡虫之后， 我们又做了另一个疯狂的实验。

You take one of these two-headed worms, and you chop off both heads,

就是你切除一只双头涡虫的两个头，

and you leave just the normal middle fragment.

只留下中间的那一段。

Now keep in mind, these animals have not been genomically edited.

提醒一下，我们从未编辑过 这些动物的基因。

There's absolutely nothing different about their genomes.

它们的基因组与自然的涡虫没有差别。

Their genome sequence is completely wild type.

它们的基因组序列就是野生型的。

So you amputate the heads, you've got a nice normal fragment,

所以如果你切除两个头， 获得了一段正常的中间段，

and then you ask: In plain water, what is it going to do?

然后你就想问： 在清水里它会怎样再生？

And, of course, the standard paradigm would say,

如果按照传统惯例，你肯定会说

well, if you've gotten rid of this ectopic extra tissue,

既然我们移除了这段异位的组织，

the genome is not edited so it should make a perfectly normal worm.

然后基因组也没改变， 它应该会长成完全正常的涡虫。

And the amazing thing is that it is not what happens.

然而了不起的是，结果并不是这样的。

These worms, when cut again and again, in the future, in plain water,

这些虫子不论切多少次， 之后在清水里

they continue to regenerate as two-headed.

它们依然会再生成双头的涡虫。

Think about this.

大家想想看。

The pattern memory to which these animals will regenerate after damage

这些动物受到损伤后再生的模板

has been permanently rewritten.

已经被永久改写了。

And in fact, we can now write it back and send them back to being one-headed

事实上，我们也可以把它改写回原状， 让它们变回一个头，

without any genomic editing.

这都无需经过基因剪辑。

So this right here is telling you that the information structure

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

that tells these worms how many heads they're supposed to have

is not directly in the genome.

并不直接储存在基因组里。

It is in this additional bioelectric layer.

它其实储存在这个额外的生物电层。

Probably many other things are as well.

可能很多其他信息也是这样。

And we now have the ability to rewrite it.

而且我们现在有能力改写它了。

And that, of course, is the key definition of memory.

而这其实就是“记忆”的关键标准。

It has to be stable, long-term stable, and it has to be rewritable.

它必须是稳定的，长久稳定的， 而且可被覆写的。

And we are now beginning to crack this morphogenetic code

我们逐渐学会破解 这种生物发育的密码，

to ask how is it that these tissues store a map of what to do

慢慢理解这些组织 如何储存发育指令的信息，

and how we can go in and rewrite that map to new outcomes.

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

安德森：我觉得 这是非常有信服力的证据，

that DNA is just not controlling the actual final shape

说明DNA并不是真正控制这些生物体

of these organisms,

最终形态的，

that there's this whole other thing going on,

实际上还有这个完全独立的作用，

and, boy, if you could crack that code,

天啊，如果你们可以破解的话

what else could that lead to.

想想可以实现什么。

By the way, just looking at these ones.

哦对了，我看这些虫子。

What is life like for a two-headed flatworm?

这种双头的涡虫是怎样生活的呢？

I mean, it seems like it's kind of a trade-off.

我感觉看起来像是有利有弊。

The good news is you have this amazing three-dimensional view of the world,

好的一面是能用三维的方式观察世界，

but the bad news is you have to poop through both of your mouths?

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,

列文：这些虫子长有这些小管子 叫做咽管，

and the tubes are sort of in the middle of the body,

这些管子长在身体中间，

and they excrete through that.

它们会从咽管排遗。

These animals are perfectly viable.

这些动物完全可以生存。

They're completely happy, I think.

我觉得它们也挺开心吧。

The problem, however,

但有个问题是

is that the two heads don't cooperate all that well,

它们的两个头配合得不是很好，

and so they don't really eat very well.

所以它们吃东西有一定困难。

But if you manage to feed them by hand,

如果你自己动手去喂它们的话，

they will go on forever,

它们就可以一直活下去，

and in fact, you should know these worms are basically immortal.

其实你可能想象到， 这些虫子基本上是永生的。

So these worms, because they are so highly regenerative,

这些虫子因为具有极强的再生能力，

they have no age limit,

它们就没有年龄限制，

and they're telling us that if we crack this secret of regeneration,

然后它们告诉我们， 如果能破解再生的秘密，

which is not only growing new cells but knowing when to stop --

这指的不仅是长出新细胞， 而且也指知道如何停止——

you see, this is absolutely crucial --

这一点其实非常重要——

if you can continue to exert this really profound control

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，

over the three-dimensional structures that the cells are working towards,

you could defeat aging as well as traumatic injury

你就可以击败衰老或是严重的创伤，

and things like this.

以及类似的损伤。

So one thing to keep in mind is that this ability to rewrite

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

the large-scale anatomical structure of the body

is not just a weird planarian trick.

并不只是涡虫身上的小把戏。

It's not just something that works in flatworms.

不是说只能在扁虫上才起作用。

What you're seeing here is a tadpole with an eye and a gut,

这里所看到的蝌蚪肠子上长了一个眼睛，

and what we've done is turned on a very specific ion channel.

我们所做的就是 打开了一个特定的离子通道。

So we basically just manipulated these little electrical transistors

简单来说，我们就是调整了细胞里的

that are inside of cells,

那些小电容器，

and we've imposed a state on some of these gut cells

我们把肠子上的某些细胞 调整为特定的电位，

that's normally associated with building an eye.

而这种电位一般和眼睛的生长有关。

And as a result, what the cells do is they build an eye.

于是细胞所做的就是搭建了一个眼睛。

These eyes are complete.

这些眼睛都结构完整。

They have optic nerve, lens, retina,

它们有视神经、晶状体、角膜，

all the same stuff that an eye is supposed to have.

正常眼球所有的一切它都有。

They can see, by the way, out of these eyes.

而且这些眼睛都是有视觉的。

And what you're seeing here

你在这里看到的

is that by triggering eye-building subroutines

就是我们通过调整蝌蚪的生理软件，

in the physiological software of the body,

触发了搭建眼睛的“子程序”，

you can very easily tell it to build a complex organ.

你可以很容易的让生物 搭建出复杂的器官。

And this is important for our biomedicine,

这对生物医学是非常关键的，

because we don't know how to micromanage the construction of an eye.

因为我们还不知道 如何一步搭建出一个眼睛。

I think it's going to be a really long time

我觉得我们需要很长时间

before we can really bottom-up build things like eyes or hands and so on.

才能搞清楚如何从无到有 组建出眼睛、手之类的器官。

But we don't need to, because the body already knows how to do it,

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，

and there are these subroutines that can be triggered

而且也有这些可以手动激活的子程序，

by specific electrical patterns that we can find.

通过我们观察到的电位图来激活。

And this is what we call "cracking the bioelectric code."

这就是我们所说的“破解生物电的密码”。

We can make eyes. We can make extra limbs.

我们可以造出眼睛，造出肢体。

Here's one of our five-legged tadpoles.

这是我们培养出的五条腿的蝌蚪。

We can make extra hearts.

我们可以造出好几个心脏。

We're starting to crack the code to understand where are the subroutines

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，

in this software

that we can trigger and build these complex organs

可以让我们触发并组建出复杂器官，

long before we actually know how to micromanage the process

远早于我们真正学会一步步

从细胞级别开始组建。

at the cellular level.

CA: So as you've started to get to learn this electrical layer

安德森：那么你们开始 了解这个生物电层，

and what it can do,

以及它的功能，

you've been able to create --

你们就可以创造——

is it fair to say it's almost like a new, a novel life-form,

一种全新的生物形态，可以这么说吗？

called a xenobot?

叫做“活体机器人”？

Talk to me about xenobots.

请给我介绍一下活体机器人。

ML: Right.

列文：好的。

So if you think about this, this leads to a really strange prediction.

你想想看，这引出了一种 非常奇怪的预测。

If the cells are really willing to build towards a specific map,

如果细胞倾向于往某种蓝图去搭建，

we could take genetically unaltered cells,

我们就可以分离出 未经过基因编辑的细胞，

and what you're seeing here is cells taken out of a frog body.

这里看到的就是从青蛙体内取出的细胞。

They've coalesced in a way that asks them to re-envision their multicellularity.

它们聚集在一起的样子 似乎像是在预想出多细胞的状态。

And what you see here

画面中所看到的

is that when liberated from the rest of the body of the animal,

就是当细胞从动物体分离出来之后，

they make these tiny little novel bodies that are, in terms of behavior,

它们聚集成这些微小的新结构体， 从它们的行为来说，

you can see they can move, they can run a maze.

这里看到它们会移动、会走迷宫。

They are completely different from frogs or tadpoles.

这些结构体与青蛙或蝌蚪完全不一样。

Frog cells, when asked to re-envision what kind of body they want to make,

当我们让青蛙细胞 这样预想出身体构建的蓝图，

do something incredibly interesting.

它们就会做神奇的事情。

They use the hardware that their genetics gives them,

它们用基因所赋予的硬件，

for example, these little hairs, these little cilia

比如这些细小的毛发，

that are normally used to redistribute mucus on the outside of a frog,

原本是拿来分配青蛙表皮的粘液的，

those are genetically specified.

这些是基因所定义好的。

But what these creatures did,

这些小生物所做的，

because the cells are able to form novel kinds of bodies,

因为这些细胞可以聚集形成新的机体，

they have figured out how to use these little cilia

它们就发觉如何利用这些小毛发

to instead row against the water, and now have locomotion.

在水里划动，于是就有了运动能力。

So not only can they move around, but they can, and here what you're seeing,

所以它们不仅能到处移动， 还可以像图中看到的，

is that these cells are coalescing together.

它们会自动聚集在一起。

Now they're starting to have conversations about what they are going to do.

它们现在在互相交流， 讨论接下来要做什么。

You can see here the flashes are these exchanges of information.

你们可以看到这些小闪光 就是信息的交换。

Keep in mind, this is just skin.

提醒一下，这只是皮肤细胞而已。

There is no nervous system. There is no brain. This is just skin.

没有神经系统，没有大脑。 只是皮肤细胞。

This is skin that has learned to make a new body

光皮肤细胞就知道 如何聚集形成新机体，

and to explore its environment and move around.

并且如何移动、探索周围的环境。

And they have spontaneous behaviors.

它们也展现出一些自发行为。

You can see here where it's swimming down this maze.

比如这里可以看到它们在迷宫里游动。

At this point, it decides to turn around and go back where it came from.

走到这里，它又决定调头往反方向走。

So it has its own behavior, and this is a remarkable model system

它们有自己的行为， 而这就是一个非常厉害的模型系统，

for several reasons.

原因有以下几个。

First of all, it shows us the amazing plasticity of cells

首先，它告诉我们野生型的细胞

that are genetically wild type.

也有很了不起的可塑性。

There is no genetic editing here.

我们没有编辑过基因。

These are cells that are really prone to making some sort of functional body.

这些细胞能很容易组建出 具有特定功能的结构体。

The second thing,

第二点是，

and this was done in collaboration with Josh Bongard's lab at UVM,

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，

they modeled the structure of these things and evolved it in a virtual world.

他们把这些生物的结构建模， 放在虚拟环境里使其演化。

So this is literally -- on a computer, they modeled it on a computer.

这个就确实是——在电脑里了， 是他们做的计算机模拟。

So this is literally the only organism that I know of on the face of this planet

这确实是我所知的， 地球上唯一的有机体，

whose evolution took place not in the biosphere of the earth

它的进化不是在地球生物圈中进行的，

but inside a computer.

而是在电脑程序里进行的。

So the individual cells have an evolutionary history,

这里每一个细胞都有自己的进化史，

but this organism has never existed before.

但是这个有机体从未真实存在过。

It was evolved in this virtual world,

它是在虚拟世界里演化的，

and then we went ahead and made it in the lab,

然后我们再在实验室里把它们造出来，

and you can see this amazing plasticity.

你也可以观察到很强的可塑性。

This is not only for making useful machines.

这不只是说生产出有用的活体机械。

You can imagine now programming these to go out into the environment

你可以想象，如果我们把这些细胞 编程并放到环境里，

and collect toxins and cleanup,

它们可以收集毒素、做清扫，

or you could imagine ones made out of human cells

或者也可以想象人体细胞造出的机械

that would go through your body and collect cancer cells

会在身体里游走并清理癌细胞，

or reshape arthritic joints,

或是重组关节炎患者的关节，

deliver pro-regenerative compounds,

传递促进再生的化合物，

all kinds of things.

各种各样的事情。

But not only these useful applications -- this is an amazing sandbox

但它不止有这些应用—— 它还是一个很了不起的试验场，

for learning to communicate morphogenetic signals to cell collectives.

让我们学习用生物发育的信号 与细胞组织对话。

So once we crack this, once we understand how these cells decide what to do,

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，

and then we're going to, of course, learn to rewrite that information,

之后我们肯定就会学着 去改写这些信息，

the next steps are great improvements in regenerative medicine,

那么下一步就是再生医学的突破，

because we will then be able to tell cells to build healthy organs.

因为我们可以让细胞 直接造出健康的器官。

And so this is now a really critical opportunity

这是目前一个非常重要的机遇，

to learn to communicate with cell groups,

去学习与细胞组织交流，

not to micromanage them, not to force the hardware,

不是对他们微管理， 也不是强行改变硬件，

to communicate and rewrite the goals that these cells are trying to accomplish.

而是交流、改写细胞所想实现的目标。

CA: Well, it's mind-boggling stuff.

安德森：好的，听起来太惊人了。

Finally, Mike, give us just one other story

最后，迈克，请你分享最后一个故事，

about medicine that might be to come

是关于未来可能出现的医药，

as you develop this understanding

随着你们逐渐增进

of how this bioelectric layer works.

对这个生物电层的理解。

ML: Yeah, this is incredibly exciting because, if you think about it,

列文：好的，这其实非常激动人心， 如果你想想看，

most of the problems of biomedicine --

生物医学现在的诸多问题——

birth defects, degenerative disease, aging, traumatic injury, even cancer --

比如先天缺陷、退化性疾病、衰老、 重大创伤，乃至癌症——

all boil down to one thing:

它们说白了都是一件事：

cells are not building what you would like them to build.

细胞没按照你想要的的方式 去组建东西。

And so if we understood how to communicate with these collectives

那么如果我们理解 如何与细胞聚集体沟通，

and really rewrite their target morphologies,

然后重写它们的发育目标，

we would be able to normalize tumors,

我们就可以化解肿瘤，

we would be able to repair birth defects,

我们可以修复先天缺陷，

induce regeneration of limbs and other organs,

可以促成肢体或其它器官的再生，

and these are things we have already done in frog models.

而这些事情都在青蛙模型上实现了。

And so now the next really exciting step

那么接下来激动人心的一步

is to take this into mammalian cells

就是把这些引入到哺乳动物细胞中，

and to really turn this into the next generation of regenerative medicine

真正把它转化为 新一代的再生医学成果，

where we learn to address all of these biomedical needs

我们从此学会应对 生物医学的各种需求，

by communicating with the cell collectives

通过与细胞团体进行沟通，

and rewriting their bioelectric pattern memories.

并重写它们的生物电所记忆的模板。

And the final thing I'd like to say is that the importance of this field

最后我想提的一点是这个领域的重要性

is not only for biomedicine.

不只停留在生物医学。

You see, this, as I started out by saying,

回想我一开始就说到，

this ability of cells in novel environments

细胞在各种新环境里

to build all kinds of things besides what their genome tells them

除了基因组的指令之外， 还能搭建新东西的能力，

is an example of intelligence,

是智能、智慧的体现，

and biology has been intelligently solving problems

而且生物学早就开始 很有智慧地解决问题，

long before brains came on the scene.

远早于动物大脑的发育、形成。

And so this is also the beginnings of a new inspiration for machine learning

这些也可以给机器学习领域 带来全新的启发，

that mimics the artificial intelligence of body cells, not just brains,

让算法去模仿这些身体细胞， 而不仅是大脑，

for applications in computer intelligence.

开拓计算机智能的全新应用。

CA: Mike Levin, thank you for your extraordinary work

安德森：迈克·列文， 感谢你们做出的卓越贡献，

and for sharing it so compellingly with us.

也感谢你如此热情洋溢地与我们分享。

Thank you.

谢谢你。

ML: Thank you so much. Thank you, Chris.

列文：非常感谢。谢谢你，克里斯。