The future of cell-free biotechnology

这里是斯坦福工程学院的《万物未来》，我是主持人奥尔特曼。

This is Stanford Engineering's The Future of Everything, and I'm your host, Altman.

自从八年前我们开播以来，这个节目已经成了记录我的斯坦福同事们杰出且富有影响力工作的宝库。

Since we started this show eight years ago, it's become an archive of amazing and impactful work by my Stanford colleagues.

研究并不仅仅发生在实验室里，正如你们在节目中将听到的，斯坦福的研究能影响健康、科技、法律、商业，以及许多与日常生活息息相关的领域。

Research is not something that just happens in the lab, and as you'll hear on this show, the research at Stanford can can impact areas like health, technology, law, and business, and many other topics that can affect everyday life.

我们希望你们能持续关注，了解科研如何有机会改善你们自己，以及你们家人和社区中所关心的人们的生活。

We hope you'll tune in to learn more about how research has the potential to help your life and to help the lives of people you care about in your family and community.

你可能会把DNA想象成一本食谱。

You kind of think of DNA like a cookbook.

它储存了所有的操作指南。

It stores the instructions.

我们会把这段信息转录成一份临时副本，就像你奶奶写的菜谱卡片，然后再翻译成蛋白质——正如你所说，蛋白质是细胞里的执行者。

We transcribe that information into a temporary copy like your grandma's recipe card, and then you translate that into proteins, which as you said, they're the doers of the cell.

这些无细胞系统的特别之处在于，它们包含了生物学的所有过程，比如支持蛋白质合成的能量代谢，但我们可以把这些蛋白质在活体之外制造出来。

What's so special about these cell free systems is they have all of the processes of biology going on, in fact, like energy metabolism to support how we make proteins, but we can produce those proteins outside of the living organism.

这样我们就能在需要的时候、需要的地方生产药品了。

So that can allow us to make things like medicines when and where they're needed.

这是斯坦福工程学院的《万物未来》，我是主持人阿尔特曼。

This is Stanford Engineering's The Future of Everything, and I'm your host, Altman.

如果你喜欢这个节目，别忘了分享给你的朋友和亲人。

If you're enjoying the show, please share it with people you like, people you love.

我们很希望他们也能加入进来。

We'd love to have them on board.

我们很想和他们一起探索万物的未来。

We'd love to share with them the future of everything.

最有效的推广方式，就是来自亲朋好友的推荐。

Personal recommendations are the best way to go.

今天，迈克·杰维特会告诉我们，通过去除细胞、只利用细胞内部的‘核心部件’来运作生物系统，我们可以开发出更有效的药物、疫苗和生物燃料。

Today, Mike Jewett will tell us that you can get better medicines, better vaccines, better biofuels by using biological systems where we strip away the cells and we just use the guts of the cells to do useful things.

这就是无细胞生物技术的未来。

It's the future of cell free biotechnology.

今天，我们继续带来‘一分钟展望未来’这个系列。

Today, we're continuing our feature, The Future in a Minute.

在和迈克的访谈结束时，我会问他一些快速问答，他会在‘一分钟展望未来’里给出他的快速回答。

At the end of my interview with Mike, I will ask him some rapid fire questions, and he'll give us his rapid fire answers in the future in a minute.

在正式开始之前，别忘了跟朋友和家人推荐一下这个节目，尤其是如果你喜欢的话。

And also, we get started, remember to tell your friends and family about the show, especially if you're enjoying it.

我们非常欢迎他们加入。

We'd love to have them on board.

过去五十年里，生物技术无疑是重大突破之一。

So biotechnology is one of the great things that has developed over the last fifty years.

我们可以利用组织、活细胞来制造药物、疫苗、生物燃料，驱动汽车和发动机，还有许多其他应用，甚至包括助力可持续发展的技术。

We can use tissue, living cells to create medicines, to create vaccines, to create biofuels, to run cars, engines, and many other applications, including things that will help for sustainability.

甚至有些细菌能分解有毒物质，把它们转化成无害的物质。

There are even bacteria that can eat toxic materials and turn them into nontoxic materials.

但这项技术的问题在于，它极度依赖在巨大的容器里培养大量细胞，容器大得像游泳池，才能获得足够多的材料来做这些有用的事。

Well, the problem with that technology is it relies very heavily on cultivating and growing large numbers of cells in huge vats, size of a swimming pool in order to get enough materials to then do all this useful stuff.

不过，我们或许可以打破细胞，取出里面负责这些工作的成分，把它们分离出来，制成更高效、更小巧的生物机器，直接生产同样的药物、疫苗和生物燃料，而不用再让细胞持续生长。

Well, it's possible that we can break open the cells and take the pieces inside the cells that do that work, isolate them and make much more effective and efficient little machines, biological machines to create these very same medicines, vaccines and biofuels without having to keep those cells growing.

迈克尔·朱特是斯坦福大学的生物工程和化学工程教授，他是这种所谓无细胞生物技术的专家。

Michael Jewett is a professor of bioengineering and chemical engineering at Stanford University, he's an expert on these so called cell free biotechnologies.

他会告诉我们这些技术的工作原理，以及它们如何开始改变未来生物技术和生物经济的面貌。

He'll tell us how they work and how they're starting to change how the biotechnology and bioeconomy might look like in the future.

迈克，你研究的是无细胞生物技术。

Mike, you study cell free biotechnology.

什么是无细胞生物技术？

What's cell free biotechnology?

嘿，拉uss，这问题

Hey, Russ, that's a

问得真好。

great question.

其实，生物技术已经渗透到我们生活的方方面面。

So biotechnology is all around us.

几十年来，我们一直用这种方法生产药物。

We've used this to make medicines for decades.

一般来说，人们会利用微生物或者活细胞来制造这类产品，比如抗癌药。

And generally speaking, people use, microorganisms, living cells, to make those types of products, like an anticancer drug.

我的实验室做的是不一样的事，叫做无细胞生物技术。

My lab does something different, which is called cell free biotechnology.

我们不依赖活的生物体或细胞来生产，而是直接用细胞内部的组分来制造这些产品。

So rather than using living organisms or cells to make stuff, we actually use the components of cells to make those types of products.

我们的做法是取细胞，去掉细胞壁，把内部的成分收集起来。

So what we do is we take cells, we rip off their cell walls, and we collect the insides.

然后把这些成分当作分子工厂，用来生产从药物、化学品到诊断工具等各种东西。

And then we use the insides as a molecular factory to produce everything from medicines to chemicals to diagnostics.

你可以把它想象成把一辆车打开引擎盖，把发动机拆下来。

I guess you can kinda think of it like taking a car and lifting the hood up and pulling the engine out.

相当于只用发动机，却不受车身其他部分的限制。

It's like using the engine but without the constraints of the car chassis.

明白了。

Gotcha.

好的。

Okay.

我本来不想质疑这个方法的合理性，但我想问几个问题。

So far free be it for me to like question the wisdom of this, but let me just ask a couple of questions.

在我看来，细胞的厉害之处在于它们是活的，能自我修复损坏的部分。

It seems to me that cells, the good part of the cells is that they're living and they do things like repair stuff that's broken.

你说的汽车这个比喻没错，但汽车可不会自己修自己。

So like you said, cars, and that's a fair analogy, but cars don't fix themselves.

可细胞不一样，它们在受伤或出问题时，能靠一些感应机制自我修复。

Whereas to some degree, cells fix themselves, like if they have an injury or a problem going on, they have some sensors.

你们放弃完整的细胞，也放弃了这些我们还没完全搞懂的神奇生物功能，是不是有点因噎废食了？

So are you throwing out the so called baby with the bathwater when you give up the intact cell and all of its kind of amazing biological capabilities that we actually don't really fully understand yet?

是的。

Yeah.

这其实是最让人意外的地方。

So that's actually the totally surprising part.

我们并没有把孩子和洗澡水一起倒掉。

We're not actually throwing the baby out with the bathwater.

在这种情况下，我们只是甩掉了细胞身上那些进化带来的累赘。

In this case, we're actually just getting rid of the evolutionary baggage of the cell.

我是个工程师，拉uss。

So I'm an engineer, Russ.

所以我一直想的是，把生物学拿来用，比如更好地让药物触达患者，或者把大气中的二氧化碳转化成可持续的化学品。

And so what I try to do is is, you know, take biology and use that to, you know, let's say, create better access to medicines or convert carbon oxides into the atmosphere into sustainable chemicals.

作为工程师，其中一个难题是，那些能自我修复、能生长、拥有这么多优点的细胞，对细胞本身在环境中生存适应来说确实很棒。

And one of the challenges as an engineer is that those cells that repair themselves and grow and have all these kind of great features, that's terrific if you're a cell living in an environment and you're trying to adapt and live and survive.

但对工程师来说，这未必是我要的。

That's actually not necessarily what I want as an engineer.

所以很多时候，细胞想做的——比如活下去、生存下去——和我作为工程师希望它们做的——比如生产药物——之间总在拉扯。

And so oftentimes there's a tug of war that exists between what cells want to do, let's say live and survive, and what I might want them to do as an engineer, which is to produce a medicine.

所以我们这种方法的优势在于，能兼得两者之长。

And so the advantage of our approach is that we kinda get the best of all worlds.

我们既利用了生物过程的能力——比如把廉价原料转化成药物和化学品，又避开了那些活细胞自带的进化包袱，而这些包袱常常跟我的工程目标背道而驰。

We get the capacities of biological processes, like how do we convert inexpensive substrates into things like medicines and chemicals, but without the constraints of that living evolutionary baggage that oftentimes is totally fighting what I want to do as an engineer.

这确实是个很棒的回答。

So that actually is, that's a great answer.

我就知道你会有精彩的回答。

I knew you would have a great answer.

我只是不确定具体会是什么。

I didn't know what it was.

那我问你，能说说这个进化包袱吗？

So let me ask you, tell me about this evolutionary baggage.

这个想法真的很有趣。

Like that's very interesting idea.

能讲讲细胞通常会做哪些事，反而干扰你的工程目标吗？

Tell me about the things that like cells tend to do that can like mess up your engineering goals.

是的

Yeah.

细胞在维持自身基本生命活动方面非常精密，比如确保各种必要过程持续运转。

So cells are like finely tuned in terms of their ability to, let's say, keep the processes that they need going alive.

其中一个关键点是细胞如何利用能量来支持自身的生长。

So and one of the major ones is how a cell uses, let's say, energy to support its growth.

我们经常使用微生物细胞的组分，比如细菌或酵母。

So we oftentimes use the components of microbial cells like bacteria or yeast.

这些细胞在生长过程中，通常有50%到70%的能量都用于一种叫蛋白质合成的过程。

And those cells, as they're growing, oftentimes, like, 50 to 70% of the energy of the cell is going towards a process called protein synthesis.

这是为了支持蛋白质合成，让细胞能够复制、分裂，保持正常状态。

And it's to support that process of protein synthesis so that those cells can replicate and divide and be happy.

所以当我作为一名生物技术专家，给这些细胞设定一个工程目标，并在DNA层面进行编码时，我们会发现中间涉及太多环节了，不过也许之后可以再回头细聊。

And so one of the challenges is when I, as a biotechnologist, might give those cells an engineering objective and code it at the level of DNA, and I realize we just jump through a lot of topics, but maybe we can come back to those.

对。

That's yeah.

细胞可能并不愿意把能量和资源用在实现我的目标上。

The cell might not want to take its energy and resources to support my objective.

它更倾向于继续生长，制造自身所需的成分，比如用于蛋白质合成的那些东西。

It would rather actually keep itself growing and make more of the components it needs for, let's say, protein synthesis.

所以这正是我们这些把细胞当作工厂来使用的工程师常常面临的矛盾。

And so that's kind of this tension that we have oftentimes as engineers for those that use kind of cells as factories.

明白了。

Gotcha.

好的。

Okay.

好，明白了。

Okay, good.

所以我们已经知道，细胞虽然具备惊人的特性，但也有一些特点让它不太适合你的工程需求。

So we've established that the cells have amazing properties, but they also have some features that make them not so perfect for your engineering.

就像你刚才说的，你把它们拆开——抱歉，我这话说得有点粗俗。

And as you said, you bust them open, forgive my, like course language.

然后你把像你提到的发动机这样的部件取出来，就能用它来做各种事情。

And then you take the pieces like the engine you pointed out, and you can use that then to do things.

那采用这种方法，最大的好处有哪些呢？

So what are the big wins that accrue when you take this approach?

我猜你肯定也见过那些巨大的工业反应罐，里面培养着大量细菌，试图让它们完成各种任务。

I'm guessing that, for example, we've all seen these pictures of these huge industrial vats where they're growing huge amounts of bacteria, trying to coax the bacteria to do all these things.

我想到，也许其中一个优势就是规模——你或许能在更大的范围内实现这种操作。

Maybe it occurs to me that maybe one of the advantages is scale, that maybe you can do this on a larger scale.

那你说说，具体有哪些好处？

So tell me what the advantages are.

确实如此。

Yeah.

好问题。

So good question.

其中一个优势是，我们不必非得在那么庞大的规模下操作，反而可能开辟出分布式制造或去中心化制造的新可能。

So some of the advantages are actually that instead of maybe having to do things at these massive scales, we might open up opportunities in, let's say, distributed manufacturing or decentralized manufacturing.

我来给你举个例子。

So I can give you an example.

如果你是一家大型制药公司，想生产某种药物，我们确实会这么做。

If you're a large pharmaceutical company and you wanna produce a medicine, we do.

我们会把这些生物体放在五万升甚至十万升的大型反应罐里培养。

We we grow these organisms in, let's say, 50,000 liters or a 100,000 liter tanks.

那可是个奥运标准泳池的大小。

That's like an Olympic swimming pool.

对吧？

Right?

所以当我们建造这类产品的生产工厂时，成本非常高。

And so that when we build the manufacturing plants for those products, it's expensive.

建造费用可能高达几亿甚至上十亿美元，这带来了很大的风险。

It can cost hundreds of millions of dollars to a billion dollars or more, and that creates risk.

结果就是，很多来自生物技术和生物领域的药品根本无法推向市场，因为风险太高了——万一情况变了，或者客户不再需要这种生产方式，就全砸手里了。

And so the consequence is that there are oftentimes many types of products from biology and biotechnology that can never reach the customer because the risk is too great that maybe something changes and maybe the customer doesn't need that process.

我们所使用的无细胞蛋白质合成系统，或者说生物技术系统，彻底颠覆了这一点。

The cell free protein synthesis systems or biotechnology systems that we use kind of flipped that on its head.

这就让我们有机会在更小的规模上应用生物技术。

And we opened this chance to use biology maybe at lower scale.

我拿疫苗举个例子吧，因为你刚才问过，什么是重大的突破？

So I'll give you an example with vaccines because you asked like, what's a big win?

对吧？

Right?

是的。

Yeah.

没错。

Yeah.

让我特别担心的一件事，就是所谓的抗生素耐药菌。

One of the things that terrifies me is something known as antibiotic resistant bacteria.

实际上，预计到2050年，这个问题会更加严重。

So in fact, it's now projected by like 2,050.

现在，死于耐抗生素细菌的人数可能已经超过死于癌症的人数了。

The possibility is that there will be more lives threatened by antibiotic resistant bacteria than by cancer today.

这很可怕，因为可能导致很多人生病，甚至更糟的情况。

And that's scary because it can lead to many people potentially getting sick or even worse.

所以我和很多其他人正在想办法，开发新的方法，更快地生产药物，不仅产量大，还能送到全球各地。

And so myself and many others are trying to think about ways to develop new approaches to create medicines maybe more quickly at scales that could be distributed and certainly also reach kind of global locations.

事实上，全球有大约百分之三十的人口无法获得基本药物。

So in fact, like 30% of the world's population lacks access to essential medicines.

而借助这些无细胞系统，我们可以在系统里自己培育出所需的成分。

And so what we can do with these cell free systems is we can grow up ourselves in our cell free systems.

我们可以裂解这些细胞，得到一个像引擎一样的装置。

We can lyse these cells and we've got like this engine.

只要给它一段DNA，它就能生产出药物。

We feed this a piece of DNA and now it can produce a medicine.

我们这套系统的厉害之处在于，它可以被冻干。

What's neat about our system is that it can be freeze dried.

你可以把它想象成宇航员吃的冰激凌或者冻干水果。

So you kinda think of it like astronaut ice cream or or freeze dried fruit.

于是你就得到了这种干燥的粉末。

And so you have this dried powder.

厉害的是，我们只要加点水，就能做出这种药物。

And what's neat is we can just add water to kind of make this medicine.

所以最大的突破就是，我们开发出了一种‘加水即用’的生物技术。

So a big win is we created a just add water biotechnology.

针对抗生素耐药菌或致病菌的药物，我们一升原料就能生产大约十五万剂疫苗，用来预防细菌感染。

In the case of these medicines for antibiotic resistance of bacteria or pathogenic bacteria, we can produce about a 150,000 doses of, vaccine to prevent infection by bacteria in about a liter.

你可以想象成一盒牛奶那么大的量。

So you can think about like a carton of milk.

这太棒了。

Okay, so this is great.

其实我刚才问了个好问题，只是我原本想的答案是错的。

And so actually I asked a good question, but I had the wrong answer in mind.

我本来以为你会说你们能扩大规模，用巨大的反应罐来生产，结果你们反其道而行之，把技术做得更小巧、更易用——加点水，就能得到抗生素。

I was thinking you would tell me you can scale up and do huge vats of things, but actually you're scaling in the opposite direction to create almost a more manageable deliverable technology, add water, get your antibiotic.

这样一来，就不需要从生产地到使用地一路上都配备冷藏链了，这真是个巨大的突破。

And bypasses amazing things like we don't need to have a cold chain of refrigerators everywhere from wherever it's manufactured to wherever it's being taken.

冷藏对活细胞和各种组织来说，一直都是个大问题，这点你再清楚不过了。

That refrigeration can be a huge issue for what, as you know very well, for living cells and all kinds of tissues.

这真是个绝佳的例子。

So that's a great example.

我最近读到你们做的工作，想问问这方面的情况。

What about So I've read about recently the work that you've done.

你们其中一个重点是制造蛋白质。

And one of the things that you guys focus on is creating proteins.

很多人上高中生物时都学过，蛋白质是生命系统里真正干活的分子。

And proteins, as many people will remember from their high school biology, proteins are the things that do stuff in living systems.

我们总听说DNA，其实它编码的就是蛋白质，这些蛋白质有着精妙的三维结构。

The DNA that we always hear about encodes for proteins, which are these beautiful three-dimensional structures.

它们在你的肌肉里收缩，产生力量。

They contract in your muscles to make force.

它们存在于你的眼睛里，帮助聚焦光线，形成清晰的视觉。

They are in your eyes and they bend light to make a focused vision.

它们参与消化你的食物。

They digest your food.

你可以在细胞外制造这些蛋白质。

You're able to make these proteins outside of the cell.

没错。

That's right.

要理解这个过程，你说得对。

And to kind of understand that process, you're totally right.

你得稍微了解一点生物学是怎么运作的，对吧？

You kind of need to understand a little bit about how the biology works, right?

生物学的核心，其实就是用DNA来编写指令。

At the heart of biology, you know, we're programming instructions at the level of DNA.

你可以把DNA想象成一本菜谱，它储存了所有的指令，对吧？

You can kind of think of DNA like a cookbook, it stores the instructions, right?

我们会把这段信息转录成一份临时副本，就像你奶奶的手写食谱，然后再翻译成蛋白质——正如你所说，蛋白质才是细胞里的实干家。

We transcribe that information into a temporary copy, like your grandma's recipe card, and then you translate that into proteins, which as you said, they're the doers of the cell.

细胞外系统的特别之处在于，它能模拟出生物学里所有的过程。

What's so special about kind of these cell free systems is they have all of the processes of biology going on.

比如支持蛋白质合成的能量代谢，我们都能在活体生物之外完成这些蛋白质的生产。

In fact, like energy metabolism to support how we make proteins, but we can produce those proteins outside of the living organism.

这样一来，我们就能在需要的时候、需要的地点生产药物，就像我们刚才说的那样。

So that can allow us to make things like medicines when and where they're needed, like we just talked about.

它还能帮助我们更广泛地探索蛋白质序列和功能之间的关系。

It also can allow us to explore the landscape of, protein sequence and protein function generally.

过去几年，生物技术和医学领域掀起了一场彻底的革新，那就是AlphaFold——它能根据DNA编码的蛋白质序列，提前预测出它的三维结构。

So, actually, there's been a complete wave of innovation in biotechnology and medicine over the last even just handful of years was something known as AlphaFold, which allows us to take kind of this protein sequence encoded by DNA and and define what the structure is gonna be ahead of time.

对吧？

Right?

这还让它们获得了2024年的诺贝尔奖。

It led to the Nobel Prize in 2024.

而未来真正令人兴奋的机遇、当前科学的前沿问题是：我们该怎么去理解蛋白质的功能呢？

And like the the big interesting opportunity for the future, and a real frontier of science now is right, how do we get to protein function?

这些无细胞系统能让我们快速表达蛋白质，从而比以往更深入地探索蛋白质的功能空间。

And these cell free systems allow us to express proteins, very rapidly and kind of explore that functional protein space even more than before.

没错，我觉得你正在做的工作之一，就是生物传感器领域。

Yes, and one of the things that I think you're doing is in the area of biosensors.

而且我知道，其中一些传感器至少是基于蛋白质的。

And I believe that some of these are at least are proteins.

你能跟我讲讲什么是生物传感器吗？在无细胞技术的背景下，它现在发展得怎么样？

And can you tell me about what a biosensor is and how that's looking in the context of cell free technologies?

是的，我们确实在使用生物传感器。

Yeah, we're using biosensors.

你可以把它想象成一种诊断工具，或者像一个开关那样。

You can think of it like diagnostic or even like a light switch, You know?

所以这个生物传感器的作用就是告诉我，某种我关心的分子是否存在。

And so what the biosensor is going to do is it's gonna tell me the presence of a molecule that I might care about.

在诊断领域，无细胞系统的一个关键优势是，我可以做出类似新冠检测的东西，但针对的是其他我们关心的物质。

And one of these key advantages of cell free systems in the context of diagnostics is I can create something like a COVID test, but for something else that we might care about.

你说得对。

And you're right.

我们实验室一直在研究这类传感器，主要用于水质和环境采样。

Our lab has been looking at these particular sensors involved in kind of water and environmental sampling.

你可能也知道，全球有超过二十亿人缺乏安全的饮用水。

So, you know, you're probably aware, more than 2,000,000,000 people on the planet lack access to clean water.

因此，弄清楚什么时候、哪里的水可以安全饮用，正变得越来越重要，也越来越困难。

And so being able to understand kind of when and where water is safe to drink is an increasingly challenging and important problem.

生物体本身时时刻刻都在感知各种物质。

Biology, of course, senses things all the time.

对吧？

Right?

如果你把手放在热炉子上，马上就知道烫，微生物也是这么感知环境的——这里有食物。

If you put your hand a hot plate, you realize it's a hot temperature, microorganisms are sensing their environment to say, there's food.

我要往那边游，因为我饿了。

I'm gonna swim that direction because I'm hungry.

对。

Right.

在这种情况下，很多生物传感器甚至能检测出饮用水里的铅等污染物。

And in this case, there are lots of biosensors that even detect like contaminants like lead in drinking water.

所以我们实验室一直很感兴趣，想开发一种类似验孕棒或者新冠检测试纸的东西，只不过用在水上，告诉你什么时候、哪里的水能喝。

And so our lab has been super interested in trying to develop you can kind of think of it like a pregnancy test for water or COVID test for water to tell us when and where our water is safe to drink.

这挺难的，因为水里的污染物往往看不见、尝不出、闻不到。

That's tricky because actually contaminants in water, oftentimes you can't see them, you can't taste them, you can't smell them.

但我们用的这些生物传感器是蛋白质，就像电灯开关一样，能明确告诉你污染物是否存在。

But these biosensors that we use are proteins that, like a light switch, tell us whether or not the contaminant is in the water.

这个过程的原理，是利用了生物体内的信息传递机制，我们用的是一种叫转录因子的物质。

How that process works is leveraging the information flow of biology where we use something known as a transcription factor.

所以我们用的就是这种生物传感器。

So that's the biosensor that we're using.

针对铅污染，我们用的是一个叫PBRR的传感器。

For lead, it's something called PBRR.

当这个传感器遇到铅时，会启动DNA里的信息编码，转录并翻译成一种可见的蛋白质，比如水母里的绿色荧光蛋白；或者你也可以设计一种小酶，让它和特定物质反应，产生颜色变化，肉眼就能看出来。

This biosensor, when it's in the presence of lead, will allow for that information encoding a DNA to be transcribed and translated into a visual protein that we can see like a green fluorescent protein from a jellyfish, or you could imagine making a a small enzyme that can take a substrate and turn it into something that's color metric that you can visually see with your eyes.

这真的很酷。

So that's really cool.

所以如果水里有铅，水就会变绿，对吧？

So if I'm so if there's lead in the water, the water's gonna turn green, basically.

是的。

Yeah.

完全正确。

Totally.

而且这

And that's

太棒了。

very cool.

当然，最难的是让它在你能接受的时间内真正运作起来。

The hard part of course is like getting it to like work so that I can see it in a timescale that I care about.

我想在十五分钟内就能看到结果。

And you know, like I wanna see it in fifteen minutes.

我们都

We all

因为口渴了才急着想知道。

got used to because you're thirsty.

你口渴了。

You're thirsty.

没错。

That's right.

完全对。

Totally.

另外一点是，生物学其实不需要感知到美国食药监局规定的法定限值——也就是每十亿份中的五份铅浓度。

And the other thing, of course, is it turns out that biology doesn't need to sense lead at the legal limit approved by the FDA, which is five parts per billion.

对吧？

Right?

生物体当然需要感知周围是否有铅或其他金属，因为它们需要这些金属来合成酶或其他蛋白质，但并不需要达到人类设定的检测灵敏度标准。

So biology, of course, it needs to know that it has lead around or other metals because it needs metals for its enzymes or other proteins, but it doesn't need that at the human specified performance characteristic.

对吧？

Right?

所以我们的情况是，必须教会这个转录因子——也就是这个生物传感器蛋白——去识别法定限值的铅浓度，这真是个特别有趣的问题。

And so in our instance, what we had to do is we had to teach the transcription factor, this biosensor protein, to read lead at the legal limit, which was a really fun problem.

我正想说到这儿，结果你已经带我们到了这里：你是在利用这些天然蛋白质，它们本来已经很擅长某件事，但你却需要它们在这同一件事上表现得更好或更不一样。

That's, so I was just gonna go there and you've already brought us there, which is you're taking these natural proteins, which might be very good at something, but you might need them to be better or different at that same thing.

在这件事上，我想你是想让它变得更加灵敏。

In this case, I guess you're trying to make it even more sensitive.

我理解的方向对吗？

Is that the right was that the direction you were going?

它对高浓度铅太敏感了，所以我们得告诉它：我需要你检测更低浓度的铅。

Like, it was too happy with high lead levels and you needed to tell it, hey, I need you to detect lower lead lead levels?

没错。

That's right.

我们希望这个传感器在铅浓度最低的时候就能被激活。

So we want this sensor to turn on at, like, the lowest level of lead possible.

我们希望这个开关能亮起来。

We want the light switch to turn on.

对吧？

Right?

没错。

It's Right.

我们用的是一个基因回路。

We use a genetic circuit.

明白吗？

See?

你可以把这想象成家里的电灯开关，我们需要它在铅含量极低的时候就能启动。

But you can kinda think about, like, the circuit of your light switch, and we need it to turn on at super low levels.

所以，这是我们设计这个铅检测传感器时必须解决的一个问题。

And so that was one thing we had to solve for with this particular lead sensor.

另一个我们要解决的是，让传感器只在有铅的时候才启动，而不是对水里其他可能存在的元素，比如锌，也有反应。

But the other thing we had to solve for is we wanted the sensor to only turn on in the presence of lead, but let's say not other atoms that might or other elements that might be in your water like zinc.

这还涉及到一个叫选择性的概念。

And so it's something called selectivity as well.

我们得同时解决灵敏度和选择性这两个问题。

We needed to address both the sensitivity problem, but also the selectivity problem.

对吧？

Right?

我希望我房间的灯只在我自己开的时候才亮，而不是我孩子跑过去随手一碰就亮了，我根本没看见。

I want the light in my room to turn on only when I'm doing it, not when my child runs around the corner and flips it on and I don't see them.

对吧？

Right?

所以，这算是其中一个挑战吧。

And so anyways, that's kind of one of the challenges.

除了利用这些天然分子，你们研究的关键部分其实是对它们进行工程改造，或者说让它们进化，从而具备更符合你们需求的特性。

So in addition to taking these natural molecules, a key part of your research is basically engineering them, evolving them if you will, to have slightly different properties that are better fit to your use case.

这样一来，你们很多时候实际上是在创造全新的蛋白质。

So that gets you into the you're creating entirely novel proteins in many cases.

是的。

Yeah.

我们既在创造自然界中原本不存在的新蛋白质，也在调整现有的天然蛋白，让它们变成我们想要的样子。

So we're creating both novel proteins, new to nature proteins, or just tuning a natural protein to make it into something that we want.

以这个铅检测传感器为例，如果我们继续沿着这个思路说下去，蛋白质是由许多氨基酸组成的。

In the context of, like, this lead sensor, if we just stick with this story for a second, the way we did that is a a protein is made up of many amino acids.

生物体系中一共有20种氨基酸。

There are 20 amino acids in biological systems.

这些氨基酸以不同的顺序排列，正是这种排列顺序决定了蛋白质的结构和功能。

Those those amino acids are arranged in different orders, and it's that sequence of amino acids that leads to the protein structure and the protein function.

我们无法事先准确知道该如何修改氨基酸序列，来预测出人类想要的功能。

We don't know how to necessarily change the sequence of amino acids a priori to predict the human specified function.

所以我们不断反复试验。

And so that's what we iterate on.

我们实验室的做法是，在氨基酸序列中引入突变或调整，通常集中在蛋白质可能结合铅的区域，或者在这个案例中，可能结合DNA的位置，因为这会影响基因转录的过程。

So what my lab would do is we make mutations or changes in that sequence of amino acids probably around where, like, that protein would bind lead or where the protein in this case might bind to DNA because it's modifying essentially how the process is transcribed.

然后我们快速尝试大量不同的序列变化，直到找到有效的那个。

And then we would just iterate quickly through many different sequence changes till we find something that worked.

在某些情况下，这个过程会非常耗时。

And and that can be an arduous process in in some context.

但现在有意思的是，我们正尝试用机器学习算法来加快这个过程。

What's neat is in today's world, we're trying to use machine learning algorithms to accelerate that process.

你正在收听《万物的未来》。

You're listening to the future of everything.

我是拉塞尔·阿尔特曼，接下来我们会继续与迈克·杰威特对话。

I'm Russ Altman, and we'll have more with Mike Jewett next.

欢迎回到《万物的未来》。

Welcome back to The Future of Everything.

我是拉uss Altman，今天和来自斯坦福大学的迈克尔·杰威特对话。

I'm Russ Altman, I'm speaking with Michael Jewett from Stanford University.

在上一部分，迈克解释了什么是无细胞生物技术，为什么它如此有用，以及它如何能实现‘生物技术粉末化’——加水即用。

In the first segment, Mike described what he means by cell free biotechnologies and why they're so useful and why they can lead to biotechnology in powder form, just add water.

在这一部分，我想问问他对可持续发展的看法。

In this segment, I'm going to ask him about sustainability.

我还会问他一些关于人工智能应用和教育的问题。

I'm gonna ask him about how he uses AI and a little bit about education.

别忘了，我们对话快结束时，我会请迈克回答几个快速问题，这是我们‘一分钟展望未来’环节的内容。

Don't forget, at the end of our conversation, I'm gonna ask Mike a few quick questions as part of our segment called The Future in a Minute.

迈克会给出一些简短的回答。

Mike will then give me some quick answers.

在上一部分快结束时，你提到用机器学习加速了新蛋白的设计，让它们具备你传感器所需的特殊铅结合能力。

At the very end of the last segment, Mike, you mentioned that you had used some machine learning to kind of supercharge your design of new proteins that had these special lead binding capacity that you needed for your sensors.

AI在你的工作中扮演了重要角色吗？

Is AI playing a big role in your work?

没错，AI在我们的工作中起了关键作用。

Definitely, AI is playing a big role in our work.

我觉得其实大家都明白，解决铅生物传感器这个问题的唯一办法就是——

And I think everyone's actually, you know, one of the key things and the only way we solve this problem with the lead biosensors, so we

我们还没来得及说完，但事实上，我们成功改造了转录因子PBRR，让它能在法定限值下检测铅，而且不受锌干扰。

didn't get really to the end of it, but actually we were able to engineer this transcription factor, PBRR, to read out lead at the legal limit and in the absence of zinc.

更具体一点，检测铅和锌的一大难题在于，它们都是+2价阳离子。

So actually to get a little more specific, one of the challenges with trying to identify lead and zinc is they're both like plus two cations.

它们的电子轨道和空间结构不同，从化学角度看，却挺相似的。

So they have different orbitals and different geometries, so if we think about the chemistry, but they're kinda similar.

它们都是带正电的金属离子。

They're positively charged metals.

所以我们得训练这个转录因子，让它活性位点的形状能分辨出铅，而忽略锌。

And so as we look at how to discriminate between those two, we had to teach this transcription factor and the shape of the active site of this transcription factor to recognize one but not the other.

为了做到这一点，我们收集了大量数据，然后决定用机器学习模型来指导设计的迭代优化。

And so in order to do that, we generated a lot of data and we said, Hey, let's use machine learning based models to try to guide iterations of this design.

你可能还记得刚才提到的，我们一直在调整氨基酸序列，以获得更好的设计。

You might've just kind of back to the previous segment, we were changing the amino acid sequence to get better designs.

于是我们用机器学习模型预测该做哪些序列改动，好让传感器只对铅有响应，而对锌完全不反应。

And so we actually used the machine learning model to predict for us what sequence changes we should make so that we could read out at the level of lead, but not at zinc.

因为最初我们设计铅传感器的时候，效果差得离谱。

Because actually the first time we tried to engineer the lead sensor, it was terrible.

我们确实做了一个更灵敏的铅传感器，

Because basically, we made a better sensitive lead sensor.

它能在法律限值下检测出铅，但一有锌就激活，根本没法用。

We we could actually report out on lead at the legal limit, but it turned on to the presence of the zinc, so it's actually a totally useless sensor.

而机器学习模型帮我们预测并找到了那些既能响应铅、又对锌无反应的序列变化，但这离不开大量正负样本数据的支持。

And actually, the machine learning model allowed us to predict and identify sequence changes that could do both, but only in the presence of large quantities of positive and negative data.

因此，我们和许多其他研究团队都在利用大规模数据集来指导设计。

And so we and many others are, of course, using large data sets to guide design.

我觉得这在生物工程研究中还会继续发挥巨大而重要的作用。

And I think it's gonna continue to be really an impactful and important area in bioengineering research.

这太令人兴奋了，而且很合理，你们能用人工智能学会锌和铅之间的细微差别，专注于铅，同时避免被锌干扰——毕竟锌不仅无毒，还是生命必需的元素。

That's super exciting and it makes sense that you could use the AI to learn the subtle differences between zinc and lead and say, hey, let's focus on the lead and let's try to not to be misled by the zinc, which is actually not only not toxic, it's required for life.

锌和铅之间的区别确实很大。

So it's a big difference between zinc and lead.

没错。

That's right.

说来有趣，我们当初光盯着数据看，根本找不到正确的模式。

You know, it's funny we found that like, when we were just trying to stare at the data we had, we couldn't find the right patterns.

我知道这对搞AI和机器学习的人来说不算新鲜，但确实很有帮助，我们借助了自然界中大量酶和蛋白质的进化树来指导模型。

And I know that's not new, right, for those of us that have been looking at AI and machine learning, but it was really, of course, helpful to use this model guided by kind of large evolutionary trees of enzymes and proteins that exist in nature to guide us.

我知道其中一个重要的应用方向，你第一部分提到过，我想再深入聊聊，就是可持续性。

So I know one of the big application areas, and you mentioned it briefly in the first segment, but I wanna go back to it, is sustainability.

你觉得这些无细胞生物技术在可持续发展方面有独特优势，能具体说说吗？

That you see that these cell free biotechnologies have a special opportunity to contribute to sustainability and play that out for me.

是的，能够可持续地生产我们每天所需的各种东西，真的非常重要。

Yeah, so, look, being able to sustainably produce all the stuff that we need every day is really, really important.

而这一切的核心，是蛋白质，甚至是蛋白质复合物。

And at the heart of that are proteins or even ensembles of proteins.

现在，我们周围大多数东西——从油漆到牙刷再到鞋子——都是用从石油中提取的碳基化学品制造的。

Right now, most of the things around us from paint to toothbrushes to shoes are all created, from carbon based chemicals that we get from petroleum.

因此，我们和许多其他研究团队都非常关注一个问题：有没有其他方式，能获取生产我们日常用品所需的碳元素，而且是在全球规模上？

And so we and many others are super interested in this idea of are there different ways to get the carbon that we need to produce the products that we use on a planetary scale?

如果你仔细想想，抬头看看大气层，会发现空气中其实充满了碳，主要以碳氧化物的形式存在。

And so, you know, if you think about that a little bit and you look to the atmosphere, there's a lot of carbon in our atmosphere and carbon oxides form a form.

比如二氧化碳，还有二氧化碳。

So it's carbon dioxide, for example, carbon monoxide.

所以我们团队特别感兴趣的是：如何把空气中的碳捕获下来，把污染物转化成我们日常用到的各种产品。

And so what our group's really been interested in is how can we take above ground carbon and pull it out of the air to transform pollution into the stuff that we use every day.

这有点像树木在做的事情。

This is kinda what trees do.

对吧？

Right?

没错，完全对。

That's totally right.

只不过树木是用它来生长、变大。

Except for trees are using it to grow and get bigger.

我们则是想利用生物和细胞里的蛋白质，把这种碳分子转化成可持续航空燃料、聚丙烯酸玻璃，或者你家里用的消毒剂之类的东西。

We're trying to use the proteins of, you know, biology and cells to take that carbon and then molecularly transform it into, let's say, a sustainable aviation fuel or polyacrylic glass or a disinfectant that you might use in your house.

从很多方面来说，我们一直在尝试用DNA编写指令，构建蛋白质复合体，这些复合体不像是树木或植物那样把碳用来生长，而是把碳转化成我们希望可持续生产的化学品。

And so many respects, we've been trying to kind of write instructions in DNA to kind of build protein ensembles that not don't necessarily take the carbon to grow like a tree or a plant, but take that carbon to produce these chemicals that we might be interested in sustainably.

关键在于，我们要实现一种我们称之为‘负碳制造’的过程。

And the the key thing is to be able to do this in something that we call carbon negative manufacturing.

我的意思是，不同于传统石油基工艺通常会向大气中排放二氧化碳或碳氧化物，我们能不能反过来，以负碳的方式，从空气中捕获碳，并把它封存在我们需要的产品里？

And what I mean by that is instead of kind of like canonical petroleum based processes that produce chemicals that oftentimes emit carbon dioxide or carbon oxides into the atmosphere, can we invert that and basically in a carbon negative way take carbon from the atmosphere and put it into the products that we need?

现在，我们必须把这个理念转化为自然界中原本不存在的新代谢路径。

Now, we've got to translate this concept into new to nature pathways.

我们最近发表的一项研究，尝试把电生物催化或者电化学和生物学结合起来。

And one of the more recent studies that we had that we just published on, we actually tried to create something that combines electro biocatalysis or electrochemistry and biology.

就是把两者的优点都拿过来用。

So it's kinda like taking the best of both worlds.

化学和生物学的优点，能同时利用吗？

Can you take the best of chemistry and biology?

我们用化学方法把大气中的二氧化碳转化成一种单碳分子，叫甲酸盐。

So we're using chemistry to take carbon dioxide from the atmosphere and turn it into a one carbon molecule called formate.

然后我们设计了一条全新的生物合成通路，用一组蛋白质，把甲酸盐转化成乙酰辅酶A——这是很多生物技术产品的基础分子。

And then we created a completely de novo biosynthetic pathway, our ensemble of proteins, to go from formate to the entry molecule, to many biotechnology products called acetyl CoA.

这太棒了。

So this is great.

我想再回到我之前说的树的例子。

And I just wanna go back to my tree idea.

在第一部分，你提到可以打开这些细胞，取出其中有用的‘引擎’。

So in the first segment, you told us you can break open these cells and you can take the engines that are useful.

植物里有没有什么有用的‘引擎’，可以打破细胞把它们取出来，帮助推进这项工作？

Are there any useful engines in plants that you could break open those cells and grab to help advance this agenda?

还是说，树木的运作方式根本没法用来生产乙酰辅酶A，或者你们想制造的其他碳基分子？

Or is the way the tree doing it just not useful for getting to this acetyl CoA or the other kind of building blocks of carbon based matter that you're trying to generate?

百分之百，树木是有用的。

So 100%, the tree is useful.

我们就接着这个话题说。

So just to stick with that.

树木是我们已知最大的碳汇之一。

Of course, trees are one of the largest carbon sinks that we have.

而且我们确实会从树木中获取木材和各种产品。

And of course, we we take wood and all kinds of products from trees.

树木本身就有各种各样的生物合成过程，能制造出许多分子。

Trees, of course, have biosynthetic processes that make all kinds of molecules.

其中一类特别有意思，叫萜类化合物，可以用来制药。

One really interesting class is called isoproids, and those can be used for medicine.

你想啊，植物和树木不仅能用来生产治疗疾病的药物，还能制造环状分子这类化学物质，甚至能作为可持续的航空燃料。

Like, if you think of plants and trees, they can be used for making medicines that help fend off disease, but also chemicals like cyclic molecules or molecules that we can even use as like sustainable aviation fuels.

所以我们通常会把植物里的这些蛋白质组合提取出来，然后在植物体外重新利用它们。

And so what we oftentimes will do is try to take those ensembles of proteins from the plants and then repurpose them outside of the plant.

原因在于，植物的生长速度实在太慢了。

And the reason why is the plants, it turns out, grow slowly.

拿一棵树来说，它长得很慢。

So if we take a tree, we've got something that kind of grows slowly.

可惜的是，这些自然过程的速度和单位时间的产出，往往达不到我们工程师想要的效率，没法快速生产出所需产品。

And unfortunately, those processes oftentimes don't meet the rate or kind of the time space yield we might need as engineers to get products to No.

这确实是个

That's a very

在地球规模上，速度根本赶不上需求。

planet on a planetary scale fast enough to matter.

你明白吧？

You know?

这个回答很中肯，因为我确实长时间观察过树木，它们看起来几乎没什么变化。

Very fair answer because I have watched trees at length and they don't seem to change very much.

我能理解，你肯定希望它们所进行的这些过程能再快一点。

And I can imagine that you would want those processes that that they're doing to just move faster.

当然，也许你们的AI技术能像优化流程那样提升效率，但我明白这会是个巨大的挑战。

Now, of course, maybe your AI magic could speed them up in the way that you you improve the lead, but I get that it it it would be a big it would be a big challenge.

你刚才提到一种分子，我觉得是乙酰辅酶A，它是很多不同物质的早期前体。

So just the step, you said that this one molecule, I think you said acetyl CoA, that is a very early precursor for lots of different materials.

对于那些不太熟悉化学的人来说，由大量生物合成的辅酶A能衍生出哪些物质呢？

Just for those of us who don't follow the chemistry carefully, what kind of materials could stem from a large collection of biologically produced CoA?

对，乙酰辅酶A。

Acetyl Yeah.

乙酰辅酶A就像是一个核心枢纽。

So acetyl CoA is like the central hub.

就像身处伦敦地铁的换乘大站一样。

It'd be like being in the middle of like a London tube stop, right?

你可以从伦敦的中心车站出发，去任何地方。

And you can go anywhere in London from, you know, from like the central station.

而乙酰辅酶A这个分子，可以转向生产各种材料，比如能织成衣服的聚合物，甚至燃料或者可生物降解的塑料之类的东西。

But in this case, that acetyl CoA molecule can go towards a material, towards a polymer that might be something that you can weave into clothing to even kind of fuels or things like plastics, like biodegradable plastics.

所以这个

And so This

这意义重大。

is huge.

这意义重大。

Is huge.

它能延伸到很多不同的方向。

It can really go into a lot of different directions.

实际上，我们特别兴奋的无细胞方法的一个优势是，这和你刚才提到的速度问题也有关联——就是说，好吧，我明白了。

And actually one of the advantages of like our cell free approach that we're really excited about is that And tying this to the rate question that you mentioned a second ago, which was like, well, okay, I get it.

我们希望速度能更快。

We wanna go faster.

过去，生物技术在活体生物中面临的一个挑战是，我们生产产品的速度太慢，要达到目标产量，得用上像奥运泳池那么大的反应器。

One of the challenges historically with biotechnology in living organisms is that the rate at which we produce products coming back to our Olympic size swimming pools means that we need these large Olympic size swimming pools to produce these products.

因为我们通常每小时每升只能产出一克左右的分子。

Because we typically make molecules, let's say, on the order of like a gram per liter per hour.

所以，我得用一个十万升的发酵罐来培养细胞。

And so I need a 100,000 liter fermenter of a cell growing.

如果我们能利用生物合成通路和酶的潜力，把产量提升到每小时每升一百克，也就是提高一百倍。

If we could use either biosynthetic pathways and the capacity of enzymes to go faster, let's say a 100 grams per liter per hour, so a 100 X it.

我们能不能通过无细胞系统，把细胞的物理性能提升一百倍？

Can we a 100 X the physical performance of cells by using a cell free system?

这在理论上是可行的，而且很可能通过人工智能和蛋白质设计进一步加速实现。

Which is theoretically possible and actually might be supercharged by AI and protein design.

这样一来，我只需要一个一立方米的空间就能完成生产。

Now all of sudden, I could do something in a meter cube.

原本需要十万升的规模，现在只要一千升就够了。

Well, instead of a 100,000 liters, you know, that's a thousand liters.