Long Now - Craig Venter: Joining 3.5 Billion Years of Microbial Invention 封面

Craig Venter: Joining 3.5 Billion Years of Microbial Invention

Craig Venter: Joining 3.5 Billion Years of Microbial Invention

本集简介

With his current series of breakthroughs in synthetic biology Craig Venter and his team are not so much creating life as joining life. Reverse-engineering evolution's long-refined tricks and subtleties at the molecular level is building humanity's most powerful toolkit yet. Through shotgun-sequencing whole microbial populations ("metagenomics"), the domain of the organisms that rule the world is at last opening up. Genome synthesis will lead to major advances in biomedicine and in adjusting civilization's global energy metabolism.

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我是斯图尔特·布兰德。

I'm Stuart Brand.

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这场关于长期思维的研讨会,由Long Now基金会为您呈现。

This seminar about long term thinking is brought to you by the Long Now Foundation.

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如果您想观看本系列演讲的高清视频,包括这场,登录longnow.org,成为Long Now会员就能免费观看。

If you would like to see high quality videos of the talks in the series, including this one, they are available online for Long Now members at longnow.org.

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晚上好。

Good evening.

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谢谢大家的到来。

Thank you for coming.

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我是来自Long Now基金会的斯图尔特·布兰德。

I'm Stuart Brand from the Long Now Foundation.

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我得提醒一下,你们大多数人手里都有提问卡,在剧场这么昏暗的环境下,写好问题后最好能走到前面,让凯文·凯利和我先看看,之后再转交给讲者。

I should say that you most of you have these question cards and in the semi darkness of the theater, it's helpful when you've written out a question to come up to the front for Kevin Kelly and me to look at to later address the speaker with.

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如果能挥一挥卡片,让穿黄帽子的工作人员看到,他们就会过来收走,帮您送上台,那就再好不过了。

It's helpful if you wave it so that the guys in the yellow hats can see it, come collect it, bring it up.

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随时都可以写问题,不管是演讲中间还是问答环节都没关系。

And you know, write questions anytime during the talk, during the Q and A.

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这才是互动的精髓。

That's the interactive part.

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我们叫‘长期当下’基金会,是因为我们心里想的是未来一万年,还有过去一万年。

Now the Long Now Foundation is called the Long Now because we have in mind the next ten thousand years and the last ten thousand years.

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这个一万年的数字是彼得·施瓦茨提出来的,因为一万年前,人类经历了一场生物技术革命,主要跟植物和我们吃的、用的动物有关。

And Peter Schwartz here is the one who came up with that number because ten thousand years ago, there was a biotech revolution having to do with mainly plants and then animals that we eat and use.

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那时候我们开始大规模搞基因改造、基因工程,人类就此拐了个大弯,到现在还在适应。

You know, we started genetic modification, genetic engineering in a big way, and humanity took a swerve that it's still getting used to.

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大概一百五十年前,又一场生物技术革命来了,就是生物医学,人类这才开始能掌控自己的健康、控制生育率。

And then about a hundred and fifty years, another biotech revolution happened with biomedicine, and humans started to be able to control their health, be able to control their birth rate.

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到了二十一世纪,很多人说这是生物学的世纪,说白了,就是生物技术的世纪。

And then we get to the twenty first century which is regarded by many as the century of biology, which to a large extent means the century of biotechnology.

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所以你看,这些革命好像都遵循着一种‘生物技术摩尔定律’——越来越频繁,现在一个人的一生里就能经历好几次,不再是隔一千年才来一次了。

And so these revolutions that we've seen seem to be on a kind of a biotech Moore's law of getting more and more frequent and happening now in one lifetime instead of it a millennia at a time.

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而当前基因科学和基因工程的快速发展,通常都是由一些特别敏锐的科学家推动的——他们能找到关键问题、搭对团队、争取到资金,然后一鼓作气冲在前面。

And the current acceleration of genetic science and genetic engineering is as often the case being carried by very sharp individuals, scientists who find the right problems, find the right people to work with, find the right funding, and swarm ahead.

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而眼下最典型的代表,就是克雷格·文特尔。

And really the exemplary case of that these days is Craig Venter.

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有请他上台。

Please welcome him.

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谢谢斯图尔特。

Well, thank you Stuart.

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能来到长今基金会,和大家一起从长远的角度思考人类的未来,真的非常荣幸。

It's certainly nice to be here with the the long now foundation taking a long view hopefully forward with humankind.

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这其实还是个开放性问题,但我们正努力试着调整一些变量,看看能不能推动这个进程。

I think it's very much an open question but we're trying to see if we can change some of the equations maybe to help that process along.

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今晚我想谈两个阶段的信息。

I'm to talk about two different phases of information tonight.

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第一个阶段,是收集信息。

The first phase is gathering the information.

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对我来说,这其实就是读取基因密码。

I actually refer to it in my case as reading the genetic code.

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接下来我会讲讲,我们现在怎么用这些信息来改变进化、改变生物学,甚至希望借此改变社会的某些部分——也就是编写基因密码。

And then I'll turn to how now we're using that information to change evolution, to change biology, to change hopefully some parts of society with writing the genetic code.

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我会聊聊这一过程的早期阶段。

And I'll talk about the early steps of that.

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这一切其实都发生在很短的时间内。

All this has happened in a pretty short period of time.

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我们早在1995年就测出了第一个生物体的基因组——流感嗜血杆菌。

We sequenced the first genome of a living species, Haemophilus influenzae in 1995.

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在此之前,我们已经开发出能大规模发现基因的技术,但完整测出活体生物基因组,也就这二三十年的事。

Before then we developed techniques for scaling up gene discovery but we've only had complete genomes of living organisms for a relatively short period of time.

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这彻底改变了我们看待生物学的方式。

It's changing our view of looking at biology.

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1995年我们测了两个基因组,接下来我会讲第二个,后来那些阶段的基因组规模和特性都截然不同。

We did two genomes in 1995 and I'll talk about the second one and the later phases of this had very different size genomes, very different characteristics.

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但在我们自掏腰包完成前两个基因组后,政府开始大量资助我们,推动整个流程规模化。

But after those first two that we had to fund ourselves, we started getting a lot of government funding to scale up the process.

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我们拿到了资金,几乎把所有主要的人类病原体都测了一遍。

We got funding to do almost every major human pathogen.

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接着我们转向植物,然后是简单的动物,再后来是更复杂的,比如果蝇和人类。

We moved into plants, then simple animals, then more complex ones such as fruit flies and people.

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1995年之后,技术上最大的突破其实是在四五年后,果蝇基因组问世时才出现的。

The big change in technology after 1995 came surprisingly only four to five years later with the fruit fly genome.

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流感嗜血杆菌的基因组有180万个碱基,而果蝇有1.8亿个,但它们都是在短短四个月内完成的。

Haemophilus was 1,800,000 letters of genetic code, Drosophila is 180,000,000 and they were both done in the same four months time period.

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九个月后,我们就拿到了人类基因组30亿碱基的初版草图。

And nine months later we had the 3,000,000,000 letter first draft of the human genome.

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计算方面特别关键,我们甚至得建了当时世界上第三大的超级计算机来处理这些运算。

Computational aspects were very important, we actually had to build the third largest computer in the world to do this calculation.

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现在用普通电脑就能轻松搞定,完全不一样了。

Now it's not so hard to do with much more standard computers.

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1999年的时候,一台每秒能运算一兆五千亿次的计算机,那可是个庞然大物。

One and a half tera ops in 1999 was a huge computer.

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现在呢,我们手里的设备已经是那时候的十倍、二十倍、三十倍,甚至一百倍。

Today, we have things ten, twenty, 30 and a 100 times that size.

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就在去年,我们首次发布了完整的人类基因组序列。

Just this last year we published the first complete human genome.

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这是二倍体基因组,包含了来自父母双方的全部染色体。

This was the diploid genome, so it had both sets of chromosomes from both parents.

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2000年和2001年完成的那些工作,其实只做了一半。

What was done in 2000 and 2001 ended up being only half the job.

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公共项目之所以只完成了一半,是因为他们原本就打算只做一半,觉得另一半能轻易推出来。

The public effort only got it half right because they set out to only do half thinking the other half would be easily discernible.

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我们索拉拉团队其实想一次性搞定完整基因组,但有点贪心了。

The project at Solara actually tried to do the complete genome but we made the mistake of overreaching.

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我们当时想一口气测五个个体的基因组。

We tried to do the genome of five individuals.

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是三个女人、三个男人,还有两个女人。

It was three women, three men and two women.

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不对,是三个女人和两个男人。

No, was three women and two men.

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听着像部旧金山拍的电影。

Sounds like a San Francisco movie.

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但因为样本多样性高,我们在拼接基因组时,把他们之间的主要差异都过滤掉了。

But because of the diversity when we assembled the genome we ended up subtracting out all the major variation between them.

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所以很多人还记得2000年、2001年时的说法:我们所有人基因都一样,差别只在千分之一的碱基上。

So the message and many of you will remember it 2,000, 2,001 is we all have the same set of genes and we all differ from each other only in one out of a thousand letters of genetic code.

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这引导了很多人往特定方向去研究。

And this started all kinds of people down certain tracks.

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现在光是测量这些千分之一差异的产业就已经相当庞大了。

We have a pretty large industry now just to measure those one out of thousand differences.

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但事实上,我们每个人之间其实有1%到3%的差异。

But it turns out we're all one to 3% different from each other.

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所以实际的差异比我们想象的要大得多。

So it's a much greater variation than we imagined.

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打个比方,我们以前以为和黑猩猩的基因差异只有1.27%。

To put that in context, we thought we differed from chimpanzees only by 1.27%.

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你可能也希望这个数字也变了才好。

So you're probably hoping that number changed as well.

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不然我们就得好好解释一下进化是怎么回事了。

Or we really have some explaining to do about evolution.

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结果发现,我们和黑猩猩其实差了4%到5%,而你们每个人身上那两套染色体之间的差异,我们之前完全没注意到。

It turns out we're four to 5% different from chimps and so this individual variation was totally missed, the two sets of chromosomes that each of you have.

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这两套染色体,不一定每一对基因都完全一样。

Each of those sets of chromosomes, they don't necessarily have the same gene that the other pair has.

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比如有个关键基因负责分解环境毒素,在白人里,三分之一的人根本没有这个基因,三分之一只有一个拷贝,另外三分之一有两个拷贝。

For example, there's a major gene associated with detoxifying environmental toxins that of the Caucasian population, a third have no copies of this gene, another third have one copy, and another third have two copies.

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但就算你有两个拷贝,它们之间也存在巨大差异。

But even when you have two copies, there's major variation of these.

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要找到两个基因完全一样的人,真的很难,我们的基因太复杂了。

It's hard to find two of us with the exact same genetic code and we have a lot of complexity.

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我觉得现在弄清楚这一点特别重要,因为这意味着我们能朝着找到正确答案的方向前进。

I think it's important that we know it now because it means we can move towards getting the right answers.

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在第一个基因组里,将近一半的基因都存在显著变异,这肯定会打乱那些指望从人类基因组里找出简单解释的人的计划。

In this first genome, almost half the genes had a major variant in them and this certainly is going to confound anybody who was hoping to get simple interpretations out of the human genetic code.

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现在好多公司都在宣传,花一千美元就能测序,但那只是瞥了一眼冰山一角而已。

So we we have all kinds of companies promising that now for a thousand dollars, but it's only a partial peak at what might be there.

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我们两个人之间75%的基因差异,根本没在之前人们常测的单核苷酸多态性里出现过。

75% of the letters of genetic code that are variant between any two of us didn't show up in the single nucleotide polymorphisms that people were measuring.

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所以我们现在正加大规模,未来十年要测一万个全基因组。

So we're scaling up now to do 10,000 human genomes over the next decade.

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希望别真花一万年,Stuart,也许十年就够了。

Hopefully it won't take ten thousand years Stuart, but maybe only ten.

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到那时,我们才第一次有机会搞清楚:哪些是遗传的,哪些是天性,哪些是环境影响。

And we will finally have the first chance to understand what's genetic, what's nature and what's nurture.

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我们不仅要测基因组,还要收集这些被测个体详细的表型数据,这可比测基因难多了——毕竟要描述一个人长什么样、怎么想、身体结构、器官构造、新陈代谢,这些方面每个人都不一样。

Not only with the genetic code but we're trying to collect intense extensive phenotypic information on all these individuals that we're going to be sequencing and that's a much greater challenge when you think about all the information that might describe you or your lives, how you look, how you think, your body structure, your organ structure, your metabolism, all those things differ dramatically with each of us.

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想把这些全说清楚,相比之下,测基因组简直就跟玩儿一样。

And trying to describe that makes sequencing the genome look like the easy part.

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我们把数据公开发布了在《生物学杂志》上。

We published our data in the public access of Journal of Biology.

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如果你想下载,这个300兆的文件随时可以拿。

You can download this 300 megabyte file if you want to.

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这是一个可以无限缩放的人类基因组图谱,能清楚看到人类基因的多样性和差异程度。

It's a zoomable version of the human genome that shows the types and extent of human variation.

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用不了多久,你也能用这种方式查到自己的基因组图谱。

And hopefully in a short time you'll be able to get the map of your genome this way.

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我们跟XPRIZE基金会合作,现在设立了一个一千万美元的奖金,奖励第一个能实现以一千美元、极短时间内完成单人基因组测序的技术。

Working with the XPRIZE Foundation, we now have a $10,000,000 prize for whoever gets the technology going to the extent that we can sequence an individual genome for $1,000 in a very short period of time.

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所以我们很有信心,未来五年内这笔钱就能发出去。

So we're hopeful that we'll be giving out that $10,000,000 in the next five years.

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如果你想赚点零花钱,不如试着发明点真正有价值的东西。

If you're looking for a little spare change, you might try inventing something worthwhile.

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我们推出了一款全新的基因组浏览器,能让用户直接查看到序列文件级别的细节,比如那些从23andMe或其他平台获取数据的人。

We're releasing a new browser for the genome that allows it to be looked at down to the sequence file level as people for example get data from 23andMe or other places.

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他们可以完整查看自己的基因组,试着理解这些数据的意义,看看早期那些检测到底漏掉了多少信息。

They can look at actually a complete genome to try and put it in some kind of context and find out how much is missing from those early tests.

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当年我们完成人类基因组测序时,很多人都以为我会退休了,但我没停,反而在想:用我们开发出来的这套读取遗传密码的技术,还能干点啥最要紧的事?

Now when we finished sequencing the human genome, many people were hoping I would retire but instead looked around for what we thought were the most important projects in science to do particularly with what the technology that we developed for reading the genetic code could try and tackle.

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我们很清楚,光看人体内部的基因还不够,还得看看环境——不只是影响我们基因的周围环境,更要放眼整个地球,看看能不能用DNA序列这个新工具,搞清楚我们到底和哪些生物共享着这颗星球。

And it was clear to us that trying to look at the environment, not only the extensive environment around us that helps influence our genes but the broader environment to see if we could use DNA sequence as the new tool to see who we were sharing the planet with.

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长期以来一直有个说法:每毫升海水里有一百万个细菌、一千万个病毒,但没人真懂这代表什么,也不知道这里面到底有多少多样性。

There's been this statistic for a long time that each milliliter of seawater has a million bacteria and 10,000,000 viruses but nobody really knew what that meant and whether there was any diversity in that.

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于是我们决定在萨尔加索海做个实验,就取一桶海水,把所有生物过滤出来,把它们的DNA大规模提取出来,然后直接测序。

And so we decided to do an experiment in the Sargasso Sea, just taking a barrel of seawater, filtering out all the organisms in it, isolating the DNA from them on mass and sequencing it.

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就这一桶水,我们测到快一百四十万个新基因时,才不得不停下来。

And just from one barrel of water, we stopped sequencing after we had close to 1,400,000 new genes.

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说不定有四万种以前从没人见过的新物种。

Maybe it's 40,000 new species that had never been seen before.

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这方法显然管用,因为以前大家都以为萨尔加索海是片贫瘠的沙漠,没什么营养,应该没啥生命存在。

So the technique obviously worked because in fact people thought we'd find little or no life in the Sargasso Sea because it was supposed to be a desert with no nutrients in it.

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我待会儿会解释这些生物是怎么活下来的,但当时我们决定再往远处探索,于是启动了‘索罗特号’二期远征。

And I'll show you why and how these organisms survived in a minute but we decided to look further and we started the Sorcerer two expedition.

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我一直想找机会驾着自己的船环球航行,所以我们决定追随像‘挑战者号’那样的科学远征,每航行两百英里就采一次样,把能测的DNA全测一遍,看看能不能拼出一幅全新的生命图景。

I'd always been looking for an excuse to sail around the world on on my own vessel and So we decided we would follow great scientific expeditions such as the Challenger expedition and sail around the world taking samples every 200 miles and sequencing everything we could find to see if we could generate a different view of life.

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我们对发现的结果简直惊呆了,这些成果后来登上了去年《PLOS》的特刊。

And we're absolutely stunned with what we found and that was a special issue of PLOS that was published last year.

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这条路线就是我们跟‘挑战者号’当年走的一模一样的。

This is the route that we followed as with the Challenger Expedition.

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我们从哈利法克斯出发,沿着美国东海岸南下,进入加勒比海,再穿过墨西哥和古巴之间的水道,经过巴拿马运河,先到科科斯岛,然后到加拉帕戈斯群岛。

We started in Halifax, went down the Eastern Seaboard into the Caribbean Sea, then down between Mexico and Cuba to the Panama Canal, through the Panama Canal and down to first Cocos Island and then to the Galapagos.

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图上这些蓝色的点,就是我们在《PLOS生物学》特刊里覆盖过的采样区域。

And that's the dots you see here in blue, that's what was covered in the special issue of PLOS biology.

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这发现了超过六百万个新基因,比此前所有科学发现的基因总数还多了一倍多。

And that covered over 6,000,000 new genes, more than doubling the number of genes known from all science up to that point.

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现在我们正在分析全球其他地区的样本。

And we've now been analyzing the samples from the rest of the globe.

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离开加拉帕戈斯后,我们前往马克萨斯群岛,结果一到就被抓了——因为法国政府和法属波利尼西亚政府在争谁对那里的微生物拥有主权。

After Galapagos, we left and sailed to the Marquesias where we are promptly arrested because there was a debate between the French government and the French Polynesian government as who had rights over the microbes that are there.

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你可能不太明白,但这其实是一张地理地图。

You may not understand this but this is this is a physical map.

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你看政治地图就知道,比如加勒比海,根本不存在公海。

If you look at a political map, in the Caribbean Sea for example, there's no international waters.

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每滴水都属于某个或某些国家,你想取样做科研,必须先得到他们的许可。

Every drop of water is claimed by one or more countries and you need permission from them to take a scientific sample.

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在这些地方捕鱼倒是没人管。

They're they're It's okay to fish in most of those places.

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你可以捕杀海洋哺乳动物,想干嘛都行,但只要你是为了科研取样,那就被视作极度危险,分分钟可能被抓。

You can, you know shoot marine mammals, you can do whatever you want but if you're asking scientific questions it's considered extremely dangerous and you can get arrested for it.

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实际上,当海洋生物在太平洋中部时,它们处在公海区域,不属于任何国家,而是属于全人类。

In fact, when the organisms in the ocean are out in the middle of the Pacific Ocean, they're in international waters and they belong to nobody or to everybody.

Speaker 1

可一旦它们被太平洋洋流带到法属波利尼西亚,这些微生物瞬间就变成了法国的遗传遗产,他们会不惜一切代价来保护它。

As soon as the one not current that goes across the Pacific carries them into French Polynesia, all those microbes instantly become French genetic heritage and they're willing to defend it to the extreme.

Speaker 1

我们终于离开了那里,采集了样本,然后在澳大利亚待了一段时间,接着横跨印度洋。

We finally got out of there and took samples and spent some time in Australia then went across the Indian Ocean.

Speaker 1

刚走到一半,我们在查戈斯群岛停了下来,那里靠近我们国家的B-52轰炸机基地,结果又被英国人抓了,他们担心我们会采样搞科研。

We got halfway across and we stopped in Chagos Island which is near where our country has a b 52 airbase and we're arrested again by the British this time because they were worried we would take samples and understand science in that water.

Speaker 1

所以现在全球对生物资源的保护非常严格,为了能把这些数据公开发布到公共数据库,我们得给每条DNA序列都标注上精确的地理坐标。

So science is something and organisms that are greatly protected around the world and to be able to publish this data in the public databases we had to put geographic GPS coordinates on every DNA sequence.

Speaker 1

比如,如果有人用我们在澳大利亚发现的序列做出了新发现,想拿来商业化,就必须去找澳大利亚政府谈条件。

So for example, if somebody makes a discovery using the sequences that we found in Australia and you want to commercialize those, you have to contact the Australian government and negotiate something.

Speaker 1

具体该怎么谈,现在还没个准话。

It's not clear what.

Speaker 1

所以现在的科研比以前复杂多了,但实验本身其实很简单。

So science is is much more complicated today but the experiments were very simple.

Speaker 1

我们就是用不同孔径的滤网过滤海水。

We just simply filtered sea water through different size filters.

Speaker 1

然后把滤网直接放进冷冻箱里。

We could then just take those filters, put them in the freezer.

Speaker 1

等到了港口,我们就把它们装进联邦快递的包裹,加点干冰,寄回马里兰州罗克维尔的实验室,那里一次性提取了所有DNA,测序后再用电脑重建——重建出来的时候,我们都惊呆了。

When we got into a port, we put them in a FedEx package with some dry ice and send them back to the lab in Rockville, Maryland where all the DNA was isolated at once from them and sequenced and then reconstructed in the computer and when we reconstructed it, we are amazed with what we found.

Speaker 1

比如,每200英里,就有85%的序列和生物是独一无二的。

For example, every 200 miles 85% of the sequences and the organisms are unique.

Speaker 1

海洋根本不是一大锅均匀的汤。

The ocean's not a giant homogeneous mixture.

Speaker 1

我们在旧金山湾采的样本,跟洛杉矶、西雅图和俄勒冈的完全不一样。

Samples that we've taken off of San Francisco Bay will be very different than the ones off of Los Angeles and off of Seattle and Oregon.

Speaker 1

实际上,如果你看这张图,红色或者深色的部分——如果你是色盲的话——代表暖水。

In fact, if you look at the, so the red or the dark here if you're color blind is warm water.

Speaker 1

蓝色或浅色是冷水,哪怕只有3%的序列在多个地点都出现,它们也严格区分暖水和冷水,而且这些差异每年都会随天气变化。

The blue or light colors is cold water and even the 3% of sequences that assemble across more than one site, they make an absolute distinction between warm and cold water and some of these change on an annual basis with weather.

Speaker 1

还有其他因素,比如阳光和营养物质,但光靠一滴海水里的DNA,我们就能判断出这水来自世界上的哪个地方。

Other things that affected are sunlight but and nutrients, but we can tell simply from a sample of seawater looking at the DNA in that water where that water came from in the world.

Speaker 1

比如,每天进出旧金山湾的船只特别多,油轮进港卸完货后,会往船舱里灌满海水,开到下一个港口再把这水排掉,换上新货物。

And for example, with all the ships that come and go from San Francisco Bay, if a tanker comes in offloads its cargo, it fills up its hold with seawater and will go to its next port, dump all that seawater and take on new cargo.

Speaker 1

你想想,每天有这么多船来来往往,每毫升海水里都有一百万个细菌、一千万个病毒,这些环境简直时刻都在被搅动、被改变。

So look at all the ships that come and go from San Francisco Bay each day and imagine with a million bacteria and 10,000,000 viruses per milliliter, how these environments are constantly being challenged and shifted.

Speaker 1

我们最早的一个重大发现是,海洋里这些生物居然都有光感受器。

One of the biggest discoveries we made early on was that these organisms we discovered in the ocean had photoreceptors.

Speaker 1

它们的分子结构跟我们眼睛里的视觉色素非常像,几乎整个海洋表层的生物都有这种东西。

Molecules very similar to our own visual pigments and almost everyone in the top parts of the ocean have these photoreceptors.

Speaker 1

幻灯片底部那个蓝色部分,是我们这次考察之前对光感受器的全部认知。

The blue segment at the bottom of the slide is our prior knowledge of photoreceptors before this expedition.

Speaker 1

而这些新发现的种类分支特别深,多样性惊人。

And these are very deep branching, a lot of diversity.

Speaker 1

所以这根本不是什么罕见的基因家族,只影响我们的视力——它其实影响着地球上绝大多数生命。

So instead of being a rare gene family just affecting our visual acuity, it affects much of life on the planet.

Speaker 1

我们可以把这些蛋白质一一比对出来。

We can line up all these proteins.

Speaker 1

那是早期阶段,我们当时只有几千个而已。

This was early on when we only had a couple thousand of them.

Speaker 1

那为什么要这么做呢?

And why do this?

Speaker 1

结果发现,只有一个氨基酸残基决定了这些受体感知的光的波长。

It turns out there's a single amino acid residue that determines the wavelength of light that these receptors see.

Speaker 1

这样一来,我们就能提出一些很特别的问题了。

So then that allows us to ask some unique questions.

Speaker 1

我们有没有发现不同地理区域的光波长和这些受体之间有关联?结果真的出乎意料——有个现象特别合理,但之前根本没人预测到。

Do we see any association with different geographic regions with the wavelength of light and we're quite surprised in fact to see something that makes sense but nobody predict it ahead of time.

Speaker 1

比如萨加索海,那里的海水是深靛蓝色的。

For example, the Sargasso Sea, it's a deep indigo blue.

Speaker 1

那里的生物,它们的光受体就是对蓝光敏感的。

The organisms that are there, the photoreceptors see blue light.

Speaker 1

到了沿海水域,那里叶绿素多,它们主要感知绿光。

You get into coastal waters where there's a lot of chlorophyll, they see primarily green light.

Speaker 1

像巴拿马运河这样的淡水里,它们看到的完全是绿光。

You get into fresh water like the Panama Canal, they see entirely green light.

Speaker 1

只需要改变遗传密码中的一个字母,就能通过改变这个氨基酸残基来调整光的波长。尽管这些水域中生物数量庞大,但能存活并繁衍的,都是那些能直接从阳光中获取能量的。

So there's only one letter of the genetic code that is needed to change to change the wavelength of light by changing this amino acid residue And even though there's a large abundance of organisms traversing these waters, the ones that survive and grow are the ones that can get their energy directly from the sun.

Speaker 1

去年,一个瑞典团队的研究证实,这些生物真的能直接靠阳光生长。

And last year, there was a study from the Swedish group showing in fact these organisms grow directly on sunlight.

Speaker 1

这可不是光合作用。

This is not photosynthesis.

Speaker 1

这跟你现在在幻灯片上看到的生物机制是一样的。

This is the same biological mechanisms that you're seeing the slide with right now.

Speaker 1

光打在这些受体上,它们就把离子跨膜运输。

You're having light hit these receptors and they transport ions across the membrane.

Speaker 1

这些微生物就是靠这种方式,在营养匮乏的环境里产生能量的。

Well these microorganisms that's how they generate their energy in a low nutrient environment.

Speaker 1

所以实际上,低营养并不意味着生命稀少,相反,这是我们见过的生命密度最高的区域之一,因为它们能直接从阳光中获取能量。

So in fact, instead of low nutrients indicating a sparsity of life, this was some of the highest density of life anywhere that we'd seen because they have these mechanisms of getting energy straight from sunlight.

Speaker 1

我们还发现,以前人们以为只有一种生物,结果发现有成千上万种。

The other thing that we found is where people thought there was a single organism, we found evidence for thousands.

Speaker 1

它们基因组成相似、排列顺序也差不多,但每一个都截然不同。

All related in the sense they have similar sets of genes, similar gene order, but hardly a single one.

Speaker 1

你看到的每一条小竖条,都代表900个碱基对的遗传密码。

Each one of these little bars you see on here represents 900 base pairs of genetic code.

Speaker 1

我们可以从这些数据里任意截取一段,构建进化树,来看看这些高度相似的生物之间的关系。

One of the things we can do is take a slice out of this data anywhere and create trees to look at the relationships between these very closely related organisms.

Speaker 1

它们用颜色标出了采样地点,比如大西洋和太平洋的区别。

They're color coded by site so we can look at things like Atlantic Ocean versus the Pacific Ocean.

Speaker 1

但最让我兴奋的是,当你看最近的进化过程时。

But the bottom to me is the most exciting when you look at recent evolution.

Speaker 1

这些光感受器在蓝光和绿光之间,已经独立切换了四次。

There's been a switch between blue and green light for these photoreceptors of four different times.

Speaker 1

所以你看,在这种选择压力下,一旦发生突变,从蓝光切换到绿光,在近海区域你就能活得很好。

So you can see at such selective pressure you get a mutation and you switch from blue to green and you're in coastal waters obviously you're gonna thrive.

Speaker 1

但如果你在远洋中间从蓝光切换到绿光,那大概就活不下去了。

If you switch from blue to green out in the middle of the ocean you probably won't.

Speaker 1

你可以用类似的方式,对这套数据提出任何问题。

You can ask basically any question of this data in a similar fashion.

Speaker 1

实际上,能问的问题多着呢。

There's in fact a lot of questions.

Speaker 1

这些新发现让已知基因数量翻了一倍,到底有多少是真正的新东西?

How much novelty is there with all these new discoveries that have been doubling the number of all genes known to science?

Speaker 1

它们是像光感受器那样,只是已知基因家族的新成员,还是我们真的在发现全新的基因?如果是新发现,那速度有多快?

Are they like the photoreceptors just new members of known gene families or are we really making new discoveries and if we're making new discoveries what's the pace of these discoveries?

Speaker 1

我们刚开始看这组数据时,简直惊呆了——仅从哈利法克斯到加拉帕戈斯这一段,我们的数据库里的基因含量就比所有公开数据库加起来还多一倍。

When we looked at the data set initially we were quite shocked to find that our database just between Halifax and the Galapagos was twice the size of all the public databases in terms of gene content.

Speaker 1

于是我们做了个对比分析,把所有这些数据互相比对了一遍。

And so we did calculation by comparing all this data to each other.

Speaker 1

我们用了大约一百万CPU小时,发现到目前为止,这个数据集中大概有五万个主要基因家族。

It was about a million CPU hours and we found out thus far in the data set there was maybe 50,000 major gene families.

Speaker 1

但我们人类目前只确认了两万二到两万三千个基因,大概也就一万四到一万五千个基因家族。

But we only have 22 to 23,000 genes, maybe 14 or 15,000 gene families.

Speaker 1

就连整个人类的生物学,也只是这片数据中的一小部分。

So even all of human biology represents only a subset of this data.

Speaker 1

但如果把这看成一条曲线,而不是一条直线,我们会发现它的长尾几乎无限延伸——不断有新发现、新基因家族冒出来,唯独动物界除外。

But if we look at this as a as a curve instead of a long now, we have a long tail that basically goes out approaching infinity right now with new discoveries and new gene families with the exception of the animal world.

Speaker 1

提醒一下大家,我们目前只是触及了进化树的一小部分,虽然‘树状模型’其实并不完全适用,但用来做这种图还是挺直观的。

So just to remind people we're just in one part of evolution even though the tree model doesn't really hold, it's useful for these kinds of diagrams.

Speaker 1

当我们研究哺乳动物的基因组时,基本上已经挖得差不多了。

When we look at our reading the genetic code in mammals, it's basically been saturated.

Speaker 1

再测一个哺乳动物的基因组——不管是你的宠物,还是街角的动物——你都不太可能发现新的基因了。

So sequencing another mammalian genome, your favorite pet, the species down the street, whatever, you're not going to discover any new genes.

Speaker 1

你可能会发现一些基因组合方式或拼写上的差异,但哺乳动物这一支,我们基本已经摸透了。

You might discover some unique combinations or spelling of those genes, but we pretty much saturated the mammalian part of the tree.

Speaker 1

但如果我们看细菌和古菌,那才刚刚进入发现的快速增长期。

But if we look at bacteria and archaea, we're in a linear phase of discovery.

Speaker 1

我们其实还不知道具体走到哪了,只知道现在是线性增长。

We don't really know where we are, we just know it's linear.

Speaker 1

我们推测,目前可能才刚起步,连百分之几都不到,这意味着随便谁去海边、太平洋捞一勺海水,都能发现成千上万的新物种、数百万个新基因。

Our thinking is that we're in the earliest phases of this of just a few percent at most which means anybody can just go out to the bay or go across to the Pacific, take a sample of seawater and make tens of thousands of species discoveries, millions of gene discoveries, etcetera.

Speaker 1

我们最早其实是拿这些技术来研究人体内的细菌的。

We we first actually apply these techniques to the human looking at the bacteria that are associated with us.

Speaker 1

微生物组就是你身上所有微生物的总和。

So the microbiome is your collection of microbes.

Speaker 1

不是每个人都有这么多牙洞,但这时候可别嫉妒别人牙洞多啊——不过我们可以从这些不同部位分离出微生物,比如看看你旁边那人,他嘴里可能有成千上万种微生物,或者你干脆尝尝自己嘴里的菌群。

Not all of you have all these cavities but you know this is no time for cavity jealousy or anything but we can isolate organisms from these different cavities and for example, look at the person next to you and you know maybe maybe you see them as having thousands of species in their mouth right now or maybe you can taste your own species.

Speaker 1

你嘴里、肠道里,要是还有其他部位的话,加起来大概有四百万个来自其他物种的基因。

On the order of 4,000,000 genes of foreign species in your mouth, in your intestinal tract, if you have those other parts that you have those as well.

Speaker 1

我们身体里的细菌细胞,其实比人类自身的细胞还多。

So we have more bacterial cells associated with us than we have human cells.

Speaker 1

结果发现,它们对我们的生理有着一些相当有趣的影响。

And it turns out they affect our physiology in some pretty interesting ways.

Speaker 1

北卡罗来纳州有一家公司叫代谢组学,他们用高通量质谱技术来分析血液里的所有化学物质。

There's a company in North Carolina called Metabolomics that's using high throughput mass spectrometry to look at all the chemicals in the bloodstream.

Speaker 1

他们发现,作为人类,我们自己大概能合成两千四百种左右的化学物质。

And they've worked out that we as a species can make maybe make around 2,400 chemicals.

Speaker 1

比如你刚吃完饭,检查一下血液,会发现其中大约60%的物质是我们自己身体产生的。

If you look in the bloodstream of anybody for example after they've had a meal, easily find about 60% of what's there is made by our own bodies.

Speaker 1

大概30%是直接从食物里来的化学成分。

About 30% are just chemicals that came out of what we eat.

Speaker 1

所以说‘你吃什么就是什么’,这话有道理,但不全对。

You know, so this notion you are what you eat is partly right.

Speaker 1

还有10%是细菌代谢产生的物质。

But 10% are bacterial metabolites.

Speaker 1

所以严格来说,我们某种程度上也是由我们喂给细菌的东西,以及细菌回馈给我们的东西决定的。

So in fact, partly we are what we feed our bacteria and what they give us.

Speaker 1

但我们任何时候体内循环的外来化学物质都有成百上千种,更别提我们还直接吃药或者其他东西了。

But we're dealing at any one time with hundreds to thousands of foreign chemicals circulating in our bloodstream, Not to mention what we add directly by taking pharmaceutics or other things.

Speaker 1

这些物质对生理的影响,我们根本一无所知,因为以前连它们存在都不知道。

And we have no idea the impact of these on physiology because in fact we didn't even know they were there before.

Speaker 1

所以我们现在研究人类基因组及其各种变异,再结合血液里的成分——要是给在座每位都做一次检测,每个人的结果都不一样,取决于你吃了什么,还有你肠道和口腔里独一无二的细菌。

So we're looking at the complexity of the human genome and all the variations there and what's in our bloodstream and if we did this test on everybody in this room we'd get a different answer for everybody based on what what you ate and also the uniqueness of the bacteria in your own guts, in your mouth.

Speaker 1

这直接影响了我们体内的化学环境。

This affects our chemical milieu.

Speaker 1

这其实是影响我们的环境的一部分。

This is part of the environment that affects us.

Speaker 1

我们还在对空气的‘基因组’进行测序。

We're also sequencing the air genome.

Speaker 1

比如在这个大小的房间里坐上一小时,你可能会吸入上万种不同的细菌,病毒更是可能多达十万种。

So for example, in a room this size, sitting here for an hour, you would absorb maybe 10,000 different bacteria and maybe 10 times that in viruses in an hour.

Speaker 1

要是你走到户外,这个数字还得翻倍,所以你现在待在这儿反而更安全——当然,这还得看你旁边坐的是谁,他们呼出来、吸进去的到底是什么。

If you go outside, it's twice that much so you're actually safer in here right now depending on who you're sitting next to again and what they're exhaling and inhaling.

Speaker 1

所以我们生活在细菌的环境里。

So we live in a bacterial milieu.

Speaker 1

你一进水里,四周全是细菌。

You go into the water, you're surrounded by bacteria.

Speaker 1

你要是去游泳,吞一口海水,等于一口气吞下几百万甚至上千万的细菌和病毒。

So if you're out swimming and you swallow a mouthful of sea water, you've just swallowed millions and millions of bacteria and viruses.

Speaker 1

我们呼吸的空气、脚下的土壤、自己的皮肤、体内的腔道——我们对细菌代谢的依赖,不亚于对人类自身代谢的依赖。

The air we breathe, the soil, our own skin, our own cavities, so we are as much dependent on bacterial metabolism as human metabolism.

Speaker 1

我们收集了这么多基因信息,就是想搞清楚这背后的复杂性,后来就想,不如干脆试着复制它。

We've been collecting all these genes, all this information trying to understand the complexity and we decided one way to try and understand the complexity was to try and mimic it.

Speaker 1

这在化学界是常规操作:你想证明自己搞懂了一个分子结构,就得把它重新合成出来。

This is standard in chemistry to prove that you have the structure that you think you have, you remake that compound.

Speaker 1

我们就想着,用同样的办法来处理遗传密码,先从一些简单的生物开始。

We decided to try and do this with the genetic code starting with some pretty simple organisms.

Speaker 1

1995年被测序的第二个生物体,是生殖支原体。

The second organism that was sequenced in '99 '95 was Mycoplasma genitalium.

Speaker 1

这是它的基因组,至少是它的示意图。

This is its genome, at least it's depiction of it.

Speaker 1

跟我们的基因组差别可大了,它只有五百多个基因,而我们有两万两千多个。

Very much unlike our genome, so it has a little over 500 genes in contrast to our 22,000.

Speaker 1

我们的基因组里头有大片大片的空白区域,比这个整个基因组还大。

We have gaps in our genetic code with no genes that are much larger than this entire genetic code.

Speaker 1

细菌的基因组你看这些条块代表基因,它们之间几乎没什么空隙。

So bacterial genomes you can see these bars represent genes have very little energetic space.

Speaker 1

这至今还是已知能自我复制的生物里最小的基因组。

This is still the smallest genome of a self replicating organism.

Speaker 1

它在实验室里能自己长起来。

So it'll grow on its own in the lab.

Speaker 1

虽然有更小的基因组,但那些都得靠别的生物共生才能活。

There's smaller genomes but they're dependent on having a symbiote organism for its growth.

Speaker 1

所以现在还不清楚,它们到底是病毒的延伸,还是真的特别简单的生物,完全依赖别人生存。

So it's not clear whether they're extension of the viral world or just truly simple organisms that are dependent on others.

Speaker 1

我们就问一些简单的问题。

And we just ask simple questions.

Speaker 1

如果一个细胞要活下来需要1800个基因,而这个只需要500个,那这真的是最少的组合了吗?

If one cell needs 1,800 genes to live and this one needs 500, Is this actually the minimal set?

Speaker 1

我们能不能用基因密码来从分子层面定义生命?

Can we define life in molecular terms based on the genetic code?

Speaker 1

于是我们开始尝试敲除这个基因组里的基因,看看能不能把数量再压得更低。

And so we set out to try and knock out genes in this genome to see if we could get down to a smaller number.

Speaker 1

你看这些小三角形,每个地方都代表一个转座子——其实就是一段像小病毒一样的DNA,能随机插进基因组的任何位置。

So every place you see one of these small triangles is where a transposon which is just a piece of DNA very much like a small virus that can randomly insert anywhere in the genetic code.

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然后我们筛选出还能活下来的细胞。

Then we select for living cells.

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所以只有那些非必需的基因,才能容得下转座子插进来。

So only genes that are not essential can tolerate transposons going into them.

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所以这其实是个‘排除法’图谱。

So this is very much a negative map.

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你可以看到,有些基因可以容纳大量转座子。

You can see some genes can take large numbers of transposons.

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但别忘了,这些实验一次只敲除一个基因。

But keep in mind these experiments only done one gene at a time.

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我们最终发现,大约有100个基因是可以敲除的。

And we got to a number of around a 100 genes that we could knock out.

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但我们怀疑,如果把这100个基因全敲掉,细胞还能活吗?

But we doubted whether if we knocked all 100 out that we could get to a living cell.

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事实上,如果我们看这种最简单生物的代谢图谱,表面看挺复杂,但跟人体任何一种细胞比起来,简直简单得惊人。

In fact, if we look at a metabolic map of this simplest organisms, it may look complex but this is remarkably simple from looking at any one of cells in the human body.

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如果把所有能敲除的基因全删掉,那代谢通路就全崩了,细胞肯定活不了。

And here's all if all the different genes that could be knocked out would knock out a lot of metabolic pathways probably not resulting in a living cell.

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所以我们决定,唯一的办法就是干脆在实验室里化学合成这条染色体,直接重新设计它的基因组成。

So we decided the only way forward was to actually make chemically in the lab this chromosome so we could alter its gene composition.

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正是这个简单的想法,催生了合成基因组学这个概念。

And that's how the whole notion of synthetic genomics was born with that relatively simple notion.

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所以我们一开始提出了两个核心问题。

So we started off with two primary questions.

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化学方法真能准确地在实验室里合成这么庞大的生物分子吗?

Can the chemistry actually permit making these incredibly large biological molecules accurately in the lab?

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如果真做出来了,我们能拿它干什么?

And if we make it what can you do with it?

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DNA本质上是惰性的化学物质,我们真能让它‘活’起来,变成一个活细胞吗?

DNA is an inert chemical, can we actually boot it up into a living cell?

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这里对比了两个领域:红线代表读取遗传密码的能力,蓝线则是我们合成DNA的能力。

This is comparing the two areas so the red line here is reading the genetic code and the blue line is our ability to synthesize DNA.

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目前,写入遗传密码的速度比读取还要慢上五个数量级。

It's actually five orders of magnitude slower right now for writing genetic code than it is reading it.

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但最近几个月,这方面的进展简直是指数级的,我觉得写入速度很快就会追上读取的速度——虽然现在还在赶。

But this is changing exponentially basically just over the last few months and I think writing the genetic code will soon catch up with our pace of reading it even though it's still changing.

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我们原本以为这事儿应该挺简单的,因为早就有种叫DNA合成仪的设备,能做出很短的DNA片段,叫寡核苷酸。

Now we thought this would be relatively simple, so there's machines called DNA synthesizers that can make very short stretches of DNA called oligo nucleotides.

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我们做的片段大概有50个碱基长,本来以为只要做出一堆这样的片段,让它们互相重叠,自然就能拼成一段更大的DNA。

We make pieces that are about 50 letters long and we thought if we just make a number of pieces and they overlap each other that they would just all go together and we could make a larger piece of DNA.

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结果发现,虽然理论上可以,但这些机器合成DNA的准确率实在太低了。

It turns out you can but the process with these machines for synthesizing DNA is very inaccurate.

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这其实是个累积出错的过程,DNA片段越长,错误就越多。

It's a degenerative process so the longer you make the piece of DNA, the more errors there are with it.

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所以我们决定做个实验,试着合成φX174基因组。

So we set out to do an experiment trying to make the PHYX174 genome.

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φX174,如果你不知道的话,是一种噬菌体。

PHYX174 for those of you who don't know was is a bacteriophage.

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它专门感染细菌,尤其是大肠杆菌,也是最早被深入研究的病毒之一。

It's a virus that kills bacteria particularly E coli and it was one of the first viruses that was extensively studied.

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事实上,它是弗雷德·桑格测序的第一个完整基因组。

In fact, it was the first actual genome of any type that was done by Fred Sanger.

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我们选它是因为它的基因组对任何改动都极其敏感,容错率极低。

We chose this because in fact its genome is very intolerant of changes.

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只要改了遗传密码,病毒就没法复制了。

If you change the genetic code the virus cannot reproduce.

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所以我们开发了一种新方法,能精准地编写遗传密码,边合成边实时修复错误。

So we developed some new techniques for actually accurately writing the genetic code where we can repair the errors in real time as we're making it.

Speaker 1

虽然之前有别的团队尝试合成过脊髓灰质炎病毒——它比这个稍大一点,但因为合成时错误太多,活性只有我们预期的万分之一。

And for us even though there had been an attempt by another group to make the polio virus which was slightly larger than this, it only had one ten thousands of the activity because of all these errors in making the genetic code.

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我们从电脑里的遗传密码开始,设计好每一段,让它们能完美拼接,再用这套新方法纠错,最后做出的DNA长度完全正确,测序结果也和我们设计的分毫不差。

We went from the genetic code in the computer, designing the pieces so that they would go together appropriately, use this new process for error correction and we ended up with a piece of DNA exactly the right length and when we sequenced it, it was exactly what we had designed and were trying to make.

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最让人激动的是,我们把这段DNA放进大肠杆菌里。

The exciting part was we took this piece of DNA and inserted it into the bacteria E.

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大肠杆菌一收到这段DNA,就把它当成了程序指令,开始制造病毒颗粒。

Coli and what had happened was E.

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大肠杆菌识别出这段DNA是病毒程序,就开始生产病毒了。

Coli recognized this as a piece of software and started making viral particles.

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就像自然界里一贯发生的那样,病毒颗粒一释放出来,立马回头把制造它们的细菌给杀死了。

True to form in nature when the viral particles were released from the cell they turned around and killed the bacteria that had made it.

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这其实是我们自然界里天天都在发生的事。

So this is a process we see all the time in nature.

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我刚跟一些石油公司的高管聊过,他们一听就明白了这个原理。

I was just speaking to oil executives and I said they clearly understood that process.

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但最让人激动的是,我们只是把一段DNA放进去,它居然自己启动,造出了病毒颗粒。

But this was pretty exciting of just taking a piece of DNA and having it activated, making viral particles.

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所以我们觉得,这就像软件在自己构建硬件。

So we view this as the software actually building its own hardware.

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这个概念特别重要,因为未来我们要往前走,连很多做这行的人还没真正意识到:我们根本不用从零开始设计生命。

And this is an important concept as we're trying to go forward in this field that even most people that are working in this area have not truly grasped the implications of this that we don't have to design life from scratch.

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我们只需要把‘软件’设计好就行了。

We just have to design the software appropriately.

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事实上,我们已经把这套方法放大了。

In fact, we've gone to scale this up.

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我们的目标是先做出病毒大小的片段,再把它们拼成一条完整的染色体。

Our plan was to make pieces that were viral sized pieces that we would then put together to make an intact chromosome.

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我们试了好几种方法来实现这个目标。

We look for a number of ways to do this.

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我们研究这个已经四年多了,自然界里有个过程叫同源重组。

We've been working on it for over four years and there's a process in nature called homologous recombination.

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这篇论文就是我们刚发表的,里面详细记录了我们是怎么做出这条完整染色体的。

This is the paper that you might have read about that we just published where we in fact made this entire chromosome.

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这是人类制造过的、结构最复杂的最大分子。

It's the largest man made molecule of a defined structure.

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如果用10号字体、不加空格、一个字母一个字母地打印出来,光是这段基因序列就得占142页纸。

To print it out one letter at a time at 10 font with no spaces, it takes a 142 pages just to print out the the letter code for this structure.

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它由58万2970个碱基对组成,分子量超过三亿。

It's 582,970 base pairs or letters of genetic code and it's over 300,000,000 molecular weight.

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我们用的方法没那么简单,不是直接拼接小片段就行的,但差不多是这个思路。

So the process that we used was not as simple as just making pieces that go together, but it's close to that.

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但这一切都始于正确的设计——现在,设计已经成为生物学的核心部分。

But it started with the right design and design now is a key part of biology.

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其实,在我们开始设计之前,就得重新测序整个基因组,因为1995年的标准是每1万个碱基大概有一个错误。

In fact before we started even the design phase, we had to go back and resequence the entire genome because the standard in 1995 was roughly one error per 10,000 letters of genetic code.

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当时没人想到,就算用这种看似准确的测序结果,未来有人会拿这些序列去再造生物体,甚至亲手编写基因代码。

Nobody thought about when reading the genetic code even with that seemingly accurate error code that anybody would be using those sequences to reproduce the organisms to actually write the genetic code.

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如果你从电脑里的基因序列开始做,那最终能做多准,完全取决于你一开始拿到的数据有多准。

And if you're starting with the genetic code in the computer, you can only make things as accurate as the information you're starting with.

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所以我们重新测了一遍整个基因组,结果发现了30个错误——这在当时其实已经算正常水平了。

So we went back and sequenced the genome all over again and found 30 errors which was the standard for where it should have been.

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但我们知道,要是用最初那个有错误的序列来合成这条染色体,它根本没法启动运行。

But we know with those 30 errors if we made this chromosome based on the initial sequence, it would never been able to be booted up.

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于是我们从这些数字信息出发,开始设计各个片段,想着要把这58万碱基的大工程拆成50个碱基的小段。

So we start with this digital information and we design the pieces thinking that we're now breaking this 580,000 piece into 50 base pair segments.

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这50碱基的小段必须和相邻片段有重叠,我们一开始先做出5到7千碱基大小的片段,每个片段都要精心设计,确保和邻居对接时能完美重叠。

The 50 base pair segments have to be designed so they overlap with their neighbor And we started off by making pieces on the order of five to seven KB, five to 7,000 base pairs that each had to be designed so when they lined up with their neighbor, they would overlap.

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我们还在里面加入了一些其他独特的元件。

We designed some other unique elements into it.

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你可能在最上面那行就能看到。

You might be able to see this on the top line.

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这里标出了我们插入水印的位置。

It shows the places in the genome where we inserted watermarks.

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我们得确保万无一失,绝对不能让哪怕一个来自原始生物的DNA分子混进来,骗了自己也骗了别人。

We wanted to absolutely be sure that we would not fool ourselves or others by having a contaminant of even one molecule of DNA from the native organism.

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这一步其实还挺有意思的。

And this can be a fun part of this process.

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我们用的是四字母的遗传密码。

So we have a four letter genetic code.

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我相信在座的大多数都知道,遗传密码是三个字母一组,对应一个氨基酸。

I'm sure most of you know that we have this triplet code or three letters of the genetic code for our amino acids.

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大概有二十种氨基酸,每种都有一个单字母的代号。

And we have roughly 20 amino acids and there's a single letter code representing each amino acid.

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所以我们可以用这套方法在DNA里写东西,实际上我们就用它来标记这段DNA,团队还特意把遗传密码的几位作者和机构名字都藏了进去。

So we can write things in the genetic code using this procedure and we use this in fact to label the DNA and the team came up with some of the authors of the genetic code and the institution.

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我们听说很多人挺失望的,觉得我们没在DNA里写点诗啊,或者像‘个人一小步,人类一大步’这类更有深意的话。

We've read that people were very disappointed we didn't put any poetry or other more profound statements like one small step or anything like that.

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不过下次我们会更认真地考虑这个问题。

But we'll think about that more carefully for the next time.

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于是这些全都进了设计环节,我们开始把这些片段做出来。

So all this went into design, started making these pieces.

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我们把四个5000到7000个碱基对的片段拼在一起,组成24千碱基的区块。

We put four of these 5,000 to 7,000 base pair pieces together to make 24 kilobytes pieces.

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每一步我们都把这些片段放进大肠杆菌里扩增。

And at each step we would grow these pieces up in bacteria E.

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我们用大肠杆菌大量复制DNA,然后测序,确保万无一失——因为我们不光想做出最终产物(那其实可以快得多),更想打造一套特别靠谱的方法,好弄清楚万一出错,错到底在哪。

Coli to make large amounts of the DNA that we then sequenced to make sure it was absolutely accurate because not only were we trying to make the end product which we could have done much faster, we were trying to make absolutely robust methods so we would understand if errors crept in where they came from.

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接着我们把24千碱基的区块再拼成72千碱基的大块。

We combined the 24 kilobytes pieces to make 72 kilobytes pieces.

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之前世界上最大的人工合成DNA片段,大概也就3万1千个碱基左右。

In the prior world's record for the largest piece of DNA made was around 31,000.

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所以这些72000碱基对的片段,远远超过了以往任何成果。

So all these pieces at 72,000 greatly exceeded what had been done before.

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然后我们把这些片段再拼在一起。

Then we put those together.

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这个过程看起来就像篮球季后赛一样,把我们所谓的‘四分之一分子’和‘二分之一分子’逐步组合起来。

This looks like a basketball playoff perhaps to make what we called quarter molecules and half molecules.

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但后来我们发现,细菌克隆的极限到了,就换了个系统。

But what we found is we exceeded the limits of cloning in bacteria and we switched to another system.

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我们改用酵母来拼接和扩增这些片段。

We switched to yeast to put these together and to grow them up.

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其实,我们从一开始就想用同源重组这个方法来组装这些片段。

In fact, we had always envisioned that we'd put these pieces together by this process called homologous recombination.

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自然界里的细胞平时就老在干这事儿——修复自己的DNA。

Basically, cells in nature do this all the time with repairing their DNA.

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比如这种叫极端嗜辐射菌的生物,地球上到处都是,可能别的星球也有,能扛住三百万拉德的辐射。

In fact, this organism, Deinococcus radiodurans, which is pretty ubiquitous on the planet and perhaps elsewhere, can take 3,000,000 rads of radiation.

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它的染色体被炸成了几百个小片段。

Its chromosomes get blown apart with a couple 100 little pieces.

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但只要它在水里待上十二到二十四小时,就能原封不动地把染色体重新拼回来。

Then as long as it's in water over twelve to twenty four hours, it remakes its chromosome exactly as it was before.

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这是它在承受了175万拉德辐射后的实际照片。

Here's an actual picture of it after 1,750,000 rads of radiation.

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我劝你别在家试,咱们人类要是碰上这么高的辐射,早就挂了,连它的一小部分都扛不住。

I recommend you not try this at home because we as a species can only take a tiny tiny fraction of this amount of radiation without being killed.

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咱们人类的染色体可没这本事。

We can't do this with our human chromosomes.

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这过程简直太惊人了。

And so this is a pretty stunning process.

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结果发现,这种细胞并不是个例。

It turns out this cell is not unique.

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地球上成千上万种生物都能做到这一点。

We have thousands of species on this planet that can do this.

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这些细胞可以完全脱水。

These cells can be totally desiccated.

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它们能被彻底晒干。

They can be dried out.

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它们甚至能在真空中存活。

They can be in a vacuum.

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它们能长时间积累电离辐射。

They can accumulate this ionizing radiation for a very long period of time.

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我们还不确定具体能撑多久,但根据估算,它们的耐受时间完全能符合‘永恒基金会’的尺度——几万年甚至上百万年,只要它们稍微有点遮挡,比如躲在彗星里或者被包裹在物质中。

We don't actually know how long but the speculation and calculations we've done is it would certainly fit into the Long Now Foundation because it's tens of thousands to millions of years if the organisms even had slight shielding in a comet or their material.

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我们知道这种生物能在太空中生存。

We know this organism can survive in outer space.

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一旦遇到水环境,它就能重新拼好自己的遗传代码,再次开始复制。

It reaches an aqueous environment and it reassembles its genetic code and it can start replicating again.

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所以我们觉得,从这种生物身上找到的这些机制,或许能帮我们把断裂的基因片段重新拼回原样。

So we thought these mechanisms that we're trying to isolate from this organism would be great for assembling the little pieces of the genome to put it back together again.

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但事实上,我们发现情况比这还要简单。

But in fact, we found it was even simpler than that.

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结果发现,酵母——就是用来做面包、啤酒、葡萄酒那些我们喜欢的东西的酵母——自己就能搞定,连外源DNA都能自动拼起来。

It turns out yeast which is used for making bread and beer and wine and all these good things we like, can do this on its own with foreign pieces of DNA.

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我们本来想在酵母里慢慢拼出这些片段,结果发现,只要设计得当,把它们放进去,它们就会自动组装成更大的片段,最后形成完整的染色体。

So while we were trying to grow up the pieces in yeast, we found that if we designed the pieces correctly and put them in, it would assemble those automatically into the larger pieces into the intact chromosome.

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所以我们最终得到了这段58万碱基对的完整序列,而且零错误。

So that's how we ended up with the entire 580,000 base pair piece that we sequenced and it's down to zero errors.

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这其实是它的照片。

This is actually a picture of it.

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根本不用电子显微镜,因为这个分子实在太大了。

You don't need an electron microscope because this molecule is so large.

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我们只是用普通显微镜观察了六秒钟。

This is just looking at it over a six second period.

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你能清楚看到它是个环状DNA,能亲眼看到它,对我们来说简直太激动了。

So you can actually see it's a circular piece of DNA and so it's pretty exciting for us to be able to actually visualize it.

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Speaker 1

那染色体怎么启动呢?

Well, how do you boot up a chromosome?

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你看到病毒了,我们只要把它放进细菌里,细菌就能自动读取这段‘代码’并开始生产东西。

You saw with the virus, all we had to do was insert it in a bacteria and the bacteria could start reading that software and producing things.

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但整个细菌染色体就没那么简单了。

We think it's a little bit more complicated with whole bacterial chromosomes.

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一开始,我们以为得先把细菌原有的染色体取出来,再换上我们设计的这个新染色体。

Initially, we thought we would have to try and remove the chromosome from a bacterial cell and add in this new one to replace it.

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结果发现这事儿特别难搞。

It turns out that's very hard to do.

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你可能听说过哺乳动物克隆,那在真核细胞里特别好操作,因为有明确的细胞核,用显微镜一割、一提,就能把核换掉,换别的生物的或者同个生物的其他细胞的核都行。

So what you've heard about with mammalian cloning works very easily in eukaryotes where there's a defined nucleus that's easy just to cut out of a cell under a microscope, lift it out and put in a nucleus from a different organism or different cell from the same organism.

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但细菌和古菌不一样,它们根本没有细胞核。

With bacteria and archaea, there is no nucleus.

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它们的DNA就跟细胞质混在一起的。

The DNA is part of the cytoplasm of the cell.

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所以我们得动点脑筋才能搞定这件事。

So we have to use a little bit more ingenuity to do this.

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去年,我们发表了一项关键的移植技术,我觉得这特别了不起。

And and last year, we published what we think is the the key technique of transplantation.

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这本身就很惊人,因为我们把一条新染色体放进原本带有不同染色体的细胞里,竟然把一个物种彻底变成了另一个物种。

That's pretty stunning in its own right because we actually by putting in a new chromosome into a cell that had a different chromosome in it to start with, We completely converted one species into another.

Speaker 1

这是一次百分之百的彻底转化。

So it was an absolute 100% transformation.

Speaker 1

我们用了两种关系很近的支原体,它们之间的差异,大概就像人和老鼠之间的差距。

We used two closely related Mycoplasma species roughly the same distance apart as we are to mice.

Speaker 1

我们从这种支原体细胞里提取出染色体,目标是拿到纯粹的DNA。

We isolated the chromosome from this microid cell and we wanted to make sure we could get down to just naked DNA.

Speaker 1

染色体上绑着很多蛋白质,所以我们用强效的消化酶把所有蛋白质都清得干干净净。

Chromosomes have a lot of proteins associated with them so we treated these pretty harshly with digestive enzymes to digest away all the proteins.

Speaker 1

之后,我们又往这条染色体里加了几段新的基因。

And then we added back a few additional genes to this chromosome.

Speaker 1

比如有一组叫LACZ的基因,能让细胞变蓝,这样就很容易识别出来。

One set of genes, the LACZ set for example will turn the cells blue so it makes it easy to identify them.

Speaker 1

我们还加了一组可筛选标记,方便挑出那些只含有移植染色体的细胞。

And we also added in a set of selectable markers so we could select for cells just with this transplanted chromosome.

Speaker 1

然后我们把这条染色体放进了一种叫丝状支原体的细胞里。

And we put this chromosome into a species called a Capricolum.

Speaker 1

这儿有个特别棒的示意图。

Now here's a wonderful graphic.

Speaker 1

我相信你们一定能看出它的精妙之处。

I'm sure you'll appreciate the sophistication of this.

Speaker 1

我们把染色体移植进了细胞。

We transplanted the chromosome into the cell.

Speaker 1

其实我们原本以为会得到这种结果:

In fact, we thought we would end up with this situation.

Speaker 1

一个细胞里头有两条染色体。

A cell with two chromosomes in it.

Speaker 1

这种事在自然界里太常见了。

We see this all the time in nature.

Speaker 1

那些反对进化论的人总说,DNA不可能只靠一个点突变就变得越来越复杂——除非是像光感受器对光波长的感知这种特例。

So all these people that make arguments against evolution because we know that you can't just get a point mutation in one piece of DNA unless it's for the wavelength of light your photoreceptor sees that that's going to change into more complexity.

Speaker 1

但现实世界里,我们看到的是染色体在不断移动,一秒钟就能给细胞增添上千个新性状。

What we see in the real world is we see chromosomes moving around where you can add a thousand new traits to a cell in a second.

Speaker 1

比如霍乱,以前大家都觉得没必要测霍乱基因组,因为它跟大肠杆菌太像了。

Cholera for example, most people thought there was no point in decoding the cholera genome because it was very closely related to E.

Speaker 1

大肠杆菌。

Coli.

Speaker 1

但当我们真的测了霍乱基因组,才发现它根本不是只有一条染色体。

But when we read the cholera genome, turns out it didn't have just a single chromosome.

Speaker 1

它有两条,而且长这样。

It had two chromosomes and it looked like this.

Speaker 1

这两条染色体差别可大了。

They were very different from each other.

Speaker 1

很明显,它从别的物种那里拿了一条染色体,加进了自己的基因库。

Obviously, it had taken up a chromosome from another species and added it to its repertoire.

Speaker 1

但我们可不希望出现这种情况。

Well, we didn't want this situation.

Speaker 1

结果发现,Capricolum的基因组特别奇怪,它根本没有任何限制性内切酶的基因。

It turns out the Capricolum genome is very unusual and that it doesn't contain any genes for restriction enzymes.

Speaker 1

限制性内切酶就像分子剪刀,专门切碎外来的DNA,是细胞用来防御入侵基因的手段。

Restriction endonucleases are the molecular scissors that cut up DNA and it's how cells protect themselves from this foreign DNA coming in.

Speaker 1

事实上,我们移植进去的那条染色体上,恰恰带了一个限制性酶。

In fact, the chromosome that we put in did have a restriction enzyme.

Speaker 1

一进细胞,这个酶就启动了,把原来的染色体当成外敌,咔咔剪成小片,全给消化了。

As soon as it was in the cell, it got expressed and it recognized the original chromosome as foreign and cut it up into small pieces and it got digested.

Speaker 1

最后,我们只剩下那些带着移植染色体的细胞。

So we were left with cells just with the transplanted chromosome.

Speaker 1

没过多久,我们就得到了一群蓝色的细胞,它们所有的特征,全由那条移植来的染色体说了算。

And over a very short period of time, we ended up with these blue cells that all the characteristics of these cells were that what was dictated by the transplanted chromosome.

Speaker 1

细胞里的每一种蛋白质,全都从原来物种的变成了由丝状支原体染色体编码的版本。

Every protein in the cell changed from that with the original species into that coded by the mycoides chromosome.

Speaker 1

细胞膜变了,所有东西都变了。

The membrane changed, everything changed.

Speaker 1

我们把DNA分离出来一看,果然只剩下我们移植进去的那部分。

We can isolate the DNA and it was only what we had transplanted in.

Speaker 1

这简直就是最彻底的身份盗窃了——好在咱们大多数人都有保护机制,大多数细胞也靠限制酶来防这一手。不过,这些机制也给我们未来做类似实验提供了强大的工具。

So this is true identity theft at the ultimate level and fortunately, you know most of us have mechanisms to protect us against this and most cells do with these restriction enzymes, But they give us very powerful tools to try and do this in the future.

Speaker 1

所以我们已经知道,能拿一个染色体移植过去,彻底把一个物种变成另一个物种。

So we know we can take a chromosome, can transplant it, we can completely convert one species into another.

Speaker 1

现在我们正在用人工合成的染色体做同样的事。

So we're in the process of doing this right now with the synthetically made chromosome.

Speaker 1

希望很快就能成功。

We hope this will happen very soon.

Speaker 1

这些实验进展特别慢,因为细胞长得太慢了。

These experiments go very slowly because the cells grow slowly.

Speaker 1

所以,做完移植后,大概要等六个星期才能看出细胞有没有活下来。

So it takes about six weeks once you do a transplant to see whether you have viable cells.

Speaker 1

不过我们很快就应该能看到结果了。

But we should be seeing that hopefully in the very near future.

Speaker 1

这将为我们这一系列研究画上一个完整的句号。

That will complete the trilogy that we've been putting together on this.

Speaker 1

其实从移植实验已经能很清楚地看出这肯定能成功,对我来说,用合成DNA还是天然DNA差别不大,因为序列完全一样,但为了确证,这一步还是很有必要的。

Although it's clear now just from the transplant experiment that we know this will work and to me it's more of a technicality if it works with synthetically made DNA versus DNA out of a cell because it is the same, it sequences the same but I think it's still important for the proof.

Speaker 1

但这真正把我们带入了一个新时代——只要重写遗传代码,就能直接改造细胞。

But it transforms us into a new era of now being able to alter cells by simply rewriting the genetic code.

Speaker 1

接下来该做什么?为什么要做?

So the next steps and why.

Speaker 1

我来快速跟你讲讲我们做这些事的初衷和目标。

We we I'm gonna walk you through quickly the some of the reasons we're doing this and where we're trying to go.

Speaker 1

很多人一听到这个,写文章就以为我们在重演《创世纪》,但其实完全不是这么回事。

But a lot of people when they think about this and write about it, they think we're redoing Genesis and we're not.

Speaker 1

这更像是一场新的寒武纪大爆发。

This is much more like a new version of the Cambrian explosion.

Speaker 1

正如这场讲座的标题所说,我们依赖于这三十五亿年的进化历程。

We're dependent as the title of this lecture said on the three and a half billion years of evolution.

Speaker 1

毕竟,作为人类,我们之所以存在,正是因为这段漫长的进化,我们所用的生物都是经过长时间演化而来的。

Also in because we're here as humans because of that and we're using organisms that have evolved over a substantial period of time.

Speaker 1

不同的是,我们不用从头再来一遍——只要写入新的分子‘软件’,就能直接从这个基础上出发,朝无数个方向发展。

What's different is we don't have to redo all that because if we just write new molecular software, we can now start at that point and go in an infinite number of directions.

Speaker 1

那为什么要这么做呢?

Why do this?

Speaker 1

其中一个原因,是为了应对我们这个物种在未来地球上的命运。

One of the reasons is trying to deal with the future of our species on this planet.

Speaker 1

未来四十年,全球人口将从六十五亿飙升到九十亿。

Over the next forty years we're going to go from six and a half to 9,000,000,000 people.

Speaker 1

这个变化太巨大了,我努力把这组数据放在一个我能理解的语境里,也希望它能帮别人更好地看懂这件事。

That's a huge change in a short period of time to I I try to put this data in context for myself and hope that it leads others to be able to understand it.

Speaker 1

我出生于1946年。

So I was born in 1946.

Speaker 1

现在地球上的人口,是1946年时的三倍。

There's now three people on this planet for everybody that existed in 1946.

Speaker 1

如果你想象一下,四十年后,这个房间里的人数要变成现在的四倍,那意味着每个人对应的1946年的人口,现在要变成四个。

So if you think of having one third of the number of people in this room in forty years, there'll be four people for everybody that was on the planet in 1946.

Speaker 1

我们现在连给六十五亿人提供食物、干净的水、能源和住房都挺吃力的。

We're having trouble providing food, clean water, energy, housing for the six and a half billion.

Speaker 1

等人口达到九十亿,这事儿只会更难办。

We're gonna have even more trouble trying to provide it for 9,000,000,000 people.

Speaker 1

我们烧掉数十亿年积累下来的生物能源——石油和煤炭,正在剧烈改变地球环境。

We're changing our environment quite dramatically by burning billions of years of biology in the form of oil and coal.

Speaker 1

这是2003年的数据,那时候我们每年就挖出五十亿吨煤、几十亿桶石油,全烧了,二氧化碳全排进大气里。

This is now from 2003, so you know, 5,000,000,000 tons of coal, billions of barrels of oil that we just take out and burn and the c o two goes into the atmosphere.

Speaker 1

这张幻灯片已经过时了。

This slide is out of date.

Speaker 1

这已经是今年第三次需要改了。

It's it needs to be changed again the third time in a year.

Speaker 1

现在我们每年向大气中排放的二氧化碳已达42亿吨,而且这些气体都会滞留在空气中。

This number is now 4,200,000,000 tons of CO2 that we're adding and stays in the atmosphere each year.

Speaker 1

这个数字还在不断加速上升。

That number is accelerating.

Speaker 1

海洋是最大的碳汇,理论上能吸收数千亿吨的二氧化碳。

The ocean sink which is the largest sink as you can see that can take hundreds of billions of tons of CO2.

Speaker 1

很多人觉得海洋已经饱和了,再加上我们为了种更多粮食、产更多燃料而砍伐森林,情况更糟了。

Many people think it's saturated and deforestation is also contributing as we try and strip more land to make more food and fuel.

Speaker 1

大家都见过这张图,二氧化碳的浓度一直在稳步上升。

Everybody have seen this graph and the steady increase in c o '2.

Speaker 1

那我们能做点什么?

So what can be done?

Speaker 1

工业界正经历一场剧变,其规模可能不亚于第一次工业革命。

There's a dramatic revolution that's taking place in the industrial world equivalent maybe to the first industrial revolution.

Speaker 1

像杜邦这样的公司,过去完全靠石油做原料,现在不得不改用其他东西。

Companies like DuPont which were basically built on using oil as its raw material have now had to switch away from using oil.

Speaker 1

他们转而用糖,但糖是不是真更环保,咱们待会儿再说。

They're switching to sugar which maybe won't be any more sustainable and we'll talk about that in a second.

Speaker 1

他们花了十年,投了一亿多美元,改造大肠杆菌,让它能把六碳糖转化成三碳的丙二醇。

But they spent ten years and over a $100,000,000 altering E coli to do a simple reaction to take six carbon sugar and make a three carbon propane diol molecule.

Speaker 1

我不知道你们能不能看清,那些看着像大啤酒桶的东西。

I don't know if you can see those, it looks like the large beer kegs.

Speaker 1

其实那是四个六千升的发酵罐,每次能一次性培养上百吨这种细菌,用糖生产丙二醇。

Those are actually four six thousand liter fermenters that they grow up literally a 100 tons of this bacteria at a time in a batch and make propionediol from sugar with this engineered bacteria.

Speaker 1

用这种生物法,他们比靠化学方法更便宜、更快。

They can do this cheaper and faster than they can with chemical conversion with their chemist.

Speaker 1

但每次发酵完,都有些问题。

This has certain downfalls after each batch.

Speaker 1

他们得把那上百吨的大肠杆菌埋掉。

They have to go bury that those tons of E.

Speaker 1

大肠杆菌得埋进垃圾填埋场,还不让烧。

Coli in a landfill they're not allowed to burn it.

Speaker 1

尽管有这些限制,加上糖的成本,他们还是声称,这种用该化学物质制成的新聚合物,将是首个非医药类的十亿美元级生物技术产品。

But even with all these limitations and the cost of sugar, they claim their new polymer that uses this chemical will be the first multi billion dollar biotech product that's not a pharmaceutical.

Speaker 1

所以,代谢工程现在已经被用上了。

So metabolic engineering is being used.

Speaker 1

我新创办的公司‘合成基因组学’跟英国石油签了协议,想用地下生物技术,通过生物转化把煤变成甲烷,从而替代采煤。

My new company synthetic genomics has a deal with BP to try and use biology deep in the earth to stop mining coal by biologically converting that coal into methane.

Speaker 1

我们从地下一英里深取了第一个样本,结果大吃一惊——那里的生物多样性居然比海洋还丰富。

We were quite surprised a mile down in the earth when we took the first sample, There was more biological diversity there than we found in the ocean.

Speaker 1

就一个简单的显微视野里,到处都是微生物,密密麻麻。

Just a simple microscopic field was teeming with microorganisms.

Speaker 1

这是我们在实验室里保存的一块煤。

This is a piece of coal that we have in the laboratory.

Speaker 1

那些密密麻麻的小东西,就是靠煤当营养生存的细菌;我们还有别的细菌,能把煤直接转化成甲烷。

All those little tiny things or the bacteria that live off of coal as a substrate and we have other bacteria that convert that substrate right into methane.

Speaker 1

有点暗,但你可能能看到煤底下冒出来的甲烷气泡。

It's a little bit dark but maybe you can see the methane bubbles coming off the coal in the bottom.

Speaker 1

这并没有停止从地下取碳,但比起挖煤烧煤,效率提升了十倍左右。而且煤储量这么丰富,至少能帮我们撑一阵子,直到新经济出现。

This doesn't stop taking carbon out of the ground but it's about a tenfold improvement over mining coal and burning it and the coal reserves are extensive enough that this could maybe get us as a stop gap until there's a new economy.

Speaker 1

但我们其实早就走偏了,部分原因就是政府里那些游说团体在作祟。

But we've been going in the wrong direction already in part because of lobbies in the government.

Speaker 1

用玉米生产乙醇根本解决不了问题。

Corn to ethanol just is not going to get us there.

Speaker 1

它的碳平衡是负的。

It's negative carbon balance.

Speaker 1

我们所有人都在补贴它,数据简直惊人。

It's been heavily subsidized by all of us and the numbers are are pretty stunning.

Speaker 1

看起来乙醇产量特别大,但实际算下来,大概每年有60亿加仑。

It looks like a huge amount of ethanol is being produced and we actually look at the numbers on the order of 6,000,000,000 gallons.

Speaker 1

现在全美大概有160家工厂在生产。

There's now I think a 160 plants around the country.

Speaker 1

六十亿加仑听着不少,但一对照我们实际的用量,就不算什么了。

6,000,000,000 gallons sounds like a lot until you look at what we use.

Speaker 1

我们交通用的燃料,是每年一千四百亿加仑汽油,外加四千五百亿加仑柴油。

So this is our transportation fuel, a 140,000,000,000 gallons of gasoline, 45,000,000,000 gallons of diesel.

Speaker 1

区区五六十一亿加仑的乙醇,对这个局面根本无济于事,更何况它产生的二氧化碳还比它吸收的多。

So five to 6,000,000,000 gallons of ethanol basically does nothing for this equation especially when it produces more CO2 than it captures.

Speaker 1

它跟农田抢地盘。

It's competing with farmland.

Speaker 1

就是因为这个,粮食价格才涨上去了。

Food prices are going up because of this.

Speaker 1

去年一年,玉米价格直接翻了一倍。

Corn prices have doubled in the last year.

Speaker 1

这根本就是个错得离谱的实验,把我们往更糟的方向越带越远。

So this is just the wrong experiment taking us very much in the wrong direction.

Speaker 1

其实咱们地球根本不缺能源。

Now we're not short of energy on this planet.

Speaker 1

每天有12万太瓦的太阳能抵达地球。

A 120,000 terawatts of energy arrives here each day from the sun.

Speaker 1

如果我们能以1%的效率捕获这些能量,只需要大约50亿公顷土地就够了。

If we could capture that at 1% efficiency, we'd only need about 500,000,000 hectares.

Speaker 1

我一直觉得,内华达州特别适合干这个。

I've argued this is a great use of Nevada.

Speaker 1

从来没人反驳过这个观点。

Nobody's ever argued with it.

Speaker 1

他们也没提出过更好的替代方案。

They haven't come up with a better alternative for use.

Speaker 1

我们完全可以靠阳光来发电。

We could just from sunlight produce energy.

Speaker 1

实际上,沙漠和海水根本不跟粮食争地。

In fact, deserts and seawater don't compete with food.

Speaker 1

我们目前正在研发一种第四代燃料,一会儿我就给你们看,它的原料是二氧化碳。

We're in fact working on, I'll show you in a minute what we're calling a fourth generation fuel starting with CO2 as the feedstock.

Speaker 1

所以如果我们能从二氧化碳出发,不管是通过太阳能还是甲烷生成途径,就能绕开用农田生产燃料这一套。

So if we can start with CO2 either from sunlight or in the methanogenesis pathways, we skip all this of use of farmland for producing fuels.

Speaker 1

我们有两种燃料,马上就要进入试生产阶段了。

We have two fuels that are pretty close to going into test production.

Speaker 1

我们管它们叫第二代和第三代。

We call them second and third generation.

Speaker 1

它们的共同问题是得用糖做原料,但比乙醇强太多了。

They both have the downfall of using sugar as a starting material but they're far superior to ethanol.

Speaker 1

它们不溶于水。

They don't mix with water.

Speaker 1

凝固点特别低。

They have very low freezing points.

Speaker 1

可以直接快速混合。

They can just be flash blended.

Speaker 1

能直接用管道运输。

They can go through pipelines.

Speaker 1

它们的能量密度高得多,能让人转向不同的方向。

They have a much higher energy density to get people going in a different direction.

Speaker 1

但我们预计十八个月后就能推出的第四代燃料,原料直接用二氧化碳。

But the one that we think we'll have in about eighteen months, the fourth generation fuel starts with CO2 as a feedstock.

Speaker 1

如果我们真能用二氧化碳当原料,那好处可多了。

Now if we can really use CO2 as a feedstock, it does several things.

Speaker 1

想想碳捕集的努力,我们完全可以把管道输送来的二氧化碳直接送进生物反应器,用太阳能或者氢气,直接从二氧化碳里合成辛烷这类燃料。

When you consider the efforts for CO2 sequestration, We can just take piped CO2 into reactors, biological reactors and make fuels such as octane directly from carbon dioxide either using sunlight as the energy source or molecular hydrogen.

Speaker 1

你根本看不到任何能源计划会采纳这种想法。

You won't see any energy plans incorporating these types of ideas.

Speaker 1

我们总是靠过去的经验线性推演,用线性思维往前走。

We go forward by extrapolating from the past, from linear ideas and linear thinking.

Speaker 1

根本没人规划颠覆性技术,但如果我们真想在有生之年改变点什么,就必须靠颠覆性技术。

There is no planning for disruptive technologies but in fact if we're gonna change anything in anybody's lifetime here, we need disruptive technologies.

Speaker 1

今年达沃斯会议的结论是:四十年后,生物能源和其他替代能源可能也只占石油和煤炭使用量的几个百分点,因为既得利益太大了。

At the Davos meeting this year, the conclusion was forty years from now biology and all alternate energy sources will maybe only make a few percent impact on using oil and coal because there's so much vested interest.

Speaker 1

每天都有新的燃煤电厂投入运行。

There's a new coal powered fuel power plant coming online every day.

Speaker 1

建这么一座电厂要花上几十亿美元。

These cost billions of dollars to build.

Speaker 1

所以,除非出现一种经济可行的替代方案——还不跟粮食抢资源,否则短期内根本改变不了什么。而且,我真不希望我们继续无限制地向大气排放二氧化碳。

So it's only if there's an economically viable alternative that doesn't compete with food that has a chance to change anything in the near future and I don't think we want to keep adding indefinitely CO2 to the atmosphere.

Speaker 1

目前数据库里已经有了一千万个基因。

So we have 10,000,000 genes in the databases right now.

Speaker 1

今年我们还会再翻一倍,从‘远征计划’里新增到两千万个。

We're going to double that number again this year from the source Expedition to 20,000,000.

Speaker 1

这些就是我们的设计模块。

These are our design components.

Speaker 1

整个电子行业当初也就那么几个基础元件,你看看后来催生了多少多样性。

The entire electronics industry only had a few handfuls of design components and look at the diversity that we have there.

Speaker 1

我们现在有几千万种基础元件可以拿来组装。

We have tens of millions of starting components that we can build.

Speaker 1

现在我们造出了一台机器人,以前四年才合成一条染色体,现在它一天能合成几千甚至上百万条,而且还是随机组合的。

And now we've built a robot that instead of making one chromosome for four years, we think we can get up to making thousands to millions of them a day and in random combinations.

Speaker 1

所以我们把这门新领域叫做组合基因组学。

So we're calling this new field combinatorial genomics.

Speaker 1

你想想看这意味什么。

So just think of that.

Speaker 1

如果我们能从设计入手,用这上千万个组件,直接合成DNA,再自动转入酵母或者其他载体,然后筛选出能产化学品、辛烷、抗体——你想找什么,系统就自动选出什么。

If we can basically start with design, take these tens of millions of design components, just make the DNA, transform that automatically into yeast or some other vector and screen for chemical production, for octane production, for antibody production, whatever you screen for will be the selection that happens.

Speaker 1

这会彻底改变生物学的发展速度,就像上世纪五十年代没人能想象,今天这台不到一太字节存储的笔记本电脑,能干翻当年一屋子的巨型计算机。

It will change the pace of biology in unimaginable ways just like I don't think anybody could imagine in the 1950s, this computer, this laptop computer with close to a terabyte of storage on it doing more than giant rooms could.

Speaker 1

这会是一个完全靠想象力推动的新领域。

This is a new area that's going be driven by people's imagination.

Speaker 1

我们正在开发一套软件,把这当成真正的设计阶段,目标是创造出新型燃料、新型化学品——现在我们用极小的团队,正努力把它规模化,这真是令人兴奋的时刻。

This is sort of a software that we're working on to make the new software, thinking of this as a true design phase, trying to come up with new fuels, new chemicals and so it's an exciting time as we try to scale this up with remarkably small teams.

Speaker 1

这和传统工业革命不一样,它不需要成千上万的工人。

This is a different aspect of industrial revolution and that it doesn't take armies of thousands.

Speaker 1

事实上,从一开始我们读取遗传密码时就是这样做的。

In fact, that's what we've done from the beginning with reading the genetic code.

Speaker 1

酵母基因组项目花了十年时间,动用了上千名科学家。

The yeast genome took ten years and a thousand scientists.

Speaker 1

我们先把这项目缩短到四个月,现在更是压缩到我们几个人就能搞定,现在我们反过来也在做同样的事。

We reduced that project first to four months and now to ours and we're doing the same thing now going in the other direction.

Speaker 1

很明显,我们能大幅推动对生命本质的理解,因为我们得靠实证方法,处理这些海量数据。

It's clear we'll be able to have a huge dent in the first bullet here of increasing the understanding of life because we need to use empirical methods with the huge data sets that we have.

Speaker 1

光靠现有科学家,根本问不完、也搞不定已发现的那些生物机制。

There's not enough scientists to ask reasonable questions to work out the biology of what's been discovered to date.

Speaker 1

但我更乐观。

But I'm more optimistic.

Speaker 1

我希望能再过十五到二十年,我们真能把石油化工行业给替代掉。

I'm hoping within fifteen to twenty years, we can really have gone a long way for replacing the petrochemical industry.

Speaker 1

如果生物能成为能源和生物修复的主要力量——比如把二氧化碳捕获回来,再转化成燃料,我们甚至可能开始逆转过去一百年对地球造成的伤害。

Hopefully, biology will be a major source of energy and bioremediation, if we can capture back CO2 and recycle that into fuel, we possibly even start to undo some of the damage that we've been doing for the last hundred years.

Speaker 1

我们还在从各种化学物质的角度出发,比如研发组合抗体,这样就能针对流感的每个变异株快速推出疫苗,而不是像今年这样总是慢上一年。

And we're also looking at this in terms of every type of chemical and looking at making for example combinatorial antibodies so we can have instant vaccines for every variant of the flu virus for example, instead of being a year late like we are again this year.

Speaker 1

这个领域挺特别的,顺便说,这可是我最后一张幻灯片了。

This field is unusual and this is my last slide by the way.

Speaker 1

我们从一开始就没等做完实验才去想伦理问题,而是先问:这么做对不对,而不是做完之后才惊呼‘哇,这潜力太大了’。

It started with us asking the ethical questions before we did the first experiments not after we thought gee whiz we have a lot of potential here.

Speaker 1

宾夕法尼亚大学那个团队在1999年发表了他们的综述。

The results of this team at the University of Pennsylvania published their review in 1999.

Speaker 1

他们觉得我们问的问题和用的技术方向都是对的。

They thought we were proceeding with the right questions and the right technology.

Speaker 1

不过他们也提了个警告,担心会被用作生物武器。

There was a caveat about being concerned about biological warfare.

Speaker 1

过去几年,斯隆基金会一直资助我和MIT,对我们这项技术的风险和收益做了一次全面评估。

The Sloan Foundation has just funded my institute and MIT for the last couple of years to do a complete review of the risk and the benefits.

Speaker 1

这份报告去年年底刚发表,现在相关讨论还在继续。

They got published at the end of last year and there's ongoing discussions.

Speaker 1

我们发表PHYX174基因组之后,联邦政府新成立了一个机构。

A new body in the federal government got formed when we published the PHYX174 genome.

Speaker 1

这件事还被拿到白宫去讨论了。

It got reviewed at the White House.

Speaker 1

他们得决定,是把我们的数据和方法保密,还是公开发表。

They had to decide whether to try and make our data and processes secret or published in the open literature.

Speaker 1

我觉得这算是布什政府在科学领域少有的几件好事之一——他们最终选择了公开出版。

I think it's one of the few good things that the Bush administration has done in science as they went and opted for open publication.

Speaker 1

他们还成立了一个新的跨部门执行委员会,让政府各个部门的人都来审查这类研究。

But they formed a new branch executive committee that has people from every branch of the government reviewing this type of work.

Speaker 1

从1996年起,我们就在持续开展公众讨论了。

We've had public discussion ongoing basically since 1996 on this.

Speaker 1

我们一直想稳扎稳打,但这项技术马上就要进入爆发式增长阶段了,我觉得接下来的一万年会特别精彩。

We're trying to take it one step at a time but it's about to expand in an exponential fashion And I think it's gonna be an exciting next ten thousand years.

Speaker 1

非常感谢。

Thank you very much.

Speaker 0

或者一万小时。

Or ten thousand hours.

Speaker 0

你从来没做过第一个。

You've never done the first.

Speaker 0

我麦克风开着吗?

Am I alive on the mic?

Speaker 0

太好了。

Great.

Speaker 0

在回答大家的感谢之前,我有个问题。

I had a question before I get into ones from thank you, everybody.

Speaker 0

你怎么决定下一步做什么?

How do you decide what to work on next?

Speaker 0

仪器设备一直在进步。

The instrumentation keeps coming along.

Speaker 0

新工具层出不穷。

New tools keep coming along.

Speaker 0

是这些机会推着你走,还是你从人类生活中最关键的需求出发,倒推回来决定该做什么?或者其他方式?

Do they push you into new opportunity areas, or do you work back from kind of the most important threshold type needs that you see in human affairs and work back from them as to what you do or something else?

Speaker 1

其实是后者更多。

Well, it's much more the latter.

Speaker 1

我们更倾向于提出那些大问题,然后推动技术发展,好让我们有工具去探索这些问题。

We we try to ask the big questions and we try to drive the development of the technology so we'll have the tools to try and ask some of those.

Speaker 1

要是现在能花一千美元、几分钟内测出一个人的基因组,那该多好。

I mean, it'd be wonderful now if we could sequence a human genome for a thousand dollars in a few minutes.

Speaker 1

我觉得我们正是在创造这种需求,并推动它向前发展。

I think we're creating the need for that and driving that forward.

Speaker 1

工具也是同样的道理。

So the same with these tools.

Speaker 1

合成DNA的技术花了很长时间才发展起来。

It's taken a long time to develop the synthetic capabilities for DNA.

Speaker 1

现在有了这些机器人,下一步能让我们再往前迈一个数量级。

The next stage is now that we have these robots are gonna take us order of magnitude further.

Speaker 1

所以,是想法和方向在推动技术的发展。

So it's the the the ideas and the directions are driving the technology formation.

Speaker 0

这是帕姆·斯特雷耶提出的一个问题。

Here's a question from Pam Strayer.

Speaker 0

你现在在哪儿?

Where are you?

Speaker 0

挥挥手。

Wave your hand.

Speaker 0

嘿。

Hey.

Speaker 0

如果你要给一个16岁或20岁的年轻人建议,该学什么才能成为下一代健康与科学的中坚力量,你会怎么说?你觉得未来会出现哪些新职业?

If you were advising a 16 or 20 year old on what to what to study to be part of the next generation of health and science, what advice would you give them, and what new kinds of careers do you see coming out?

Speaker 1

我觉得我们之所以能取得一些突破,而且小团队也能成功,关键在于我们真正做到了跨学科合作。

Well, I think one of the exciting things about what we've done and maybe why a small group has been successful is is there's we we have truly multidisciplinary teams.

Speaker 1

我们很多重大突破其实都来自数学、新算法和计算方法的创新。

Some of the biggest breakthroughs we have have been in mathematics, new algorithm development, new computer computational approaches.

Speaker 1

当然,我朋友和同事哈姆·史密斯和克莱德·哈钦森开发的那些DNA克隆和操控工具,纯粹就是工程学的应用。

Obviously, the tools that my friend and colleague, Ham Smith and Clyde Hutchinson have developed in terms of cloning and manipulating DNA, just straight engineering.

Speaker 1

没有任何一个科学领域是跟这个没关系的。

There is no field of science that is not applicable to this.

Speaker 1

就连天文学也是——我最近最兴奋的一个发现是,在我们自己的银河系里,就有十万颗地球大小甚至更大的行星,很可能都处在适合生命存在的‘金发区’。

Even astronomy, my my most exciting new number that comes out of astronomy is in our own galaxy, we have a 100,000 Earth and super Earth planets all likely to be in that sweet zone that could be compatible with life.

Speaker 1

这还只是我们银河系的情况。

That's just in our galaxy.

Speaker 1

所以当我们思考生命的普遍性时,老觉得生命是以人类为中心,这想法其实挺可笑的。

So when we think about the ubiquitous nature of life, we're pretty silly to constantly think it centers around human existence.

Speaker 0

你觉得生命会不会在地球、火星和其他地方之间来回传播?

What's your bet on whether life is going back and forth between Earth and Mars and other places?

Speaker 1

肯定是在互相传递的。

Well, it's definitely being exchanged.

Speaker 1

至于生命最初是从哪儿来的,我们还不知道。

Where it originated, we don't know.

Speaker 1

每年地球和火星之间大约有两百公斤的物质在相互交换。

There's roughly 200 kilograms of material exchange between Earth and Mars each year.

Speaker 1

如果这么大量的物质还没带上像耐辐射球菌这类能轻松存活的生物,那我才是地球上最惊讶的人。

If that's not carrying organisms like Deinococcus and other things that can easily survive, I will be the most surprised person on this planet.

Speaker 1

所以我确信,我们终将在火星上找到生命的迹象。

So I know we'll find indications of life on Mars.

Speaker 1

这些生命可能是我们带过去的,但也可能是火星上的东西反过来污染了地球。

It could be just because we've contaminated it, but it's possible it's contaminating Earth with a different set.

Speaker 1

我们到现在连地球上1%的生命形式都没搞清楚,路还长着呢。

We only know about 1% of life on our own planet, so we have a ways to go to understand that.

Speaker 0

据我了解,你现在已经开始用宏基因组测序技术,直接分析空气乃至平流层里的整个微生物群落了?

Well, you're as I understand it, starting to sample shotgun sequence whole populations in the air and all the way up to the stratosphere.

Speaker 0

随着你离地表越来越远,你发现了什么?

What do you find as you get farther and farther out from the surface?

Speaker 1

我们还在分析高空样本的数据,但最让人兴奋的是,我们现在开始研究太空尘埃里的凝胶了——因为有了新技术,单个DNA分子都能被扩增出来。

Well, we're still working on the data on the higher levels but perhaps the most exciting thing is we're starting to look at the gels with space dust because we have techniques now where we can amplify from a single molecule of DNA.

Speaker 1

要说外星生命有什么最明显的证据,那肯定就是大分子DNA了。

And there's nothing more indicative of life somewhere else than large macromolecules of DNA.

Speaker 1

我不知道从这些凝胶里能不能找到,但这次我们是头一回认真找。

So I don't know if from the gels we'll be able to find any, but we're looking for the first time.

Speaker 1

不过我觉得,我们已经在空间站周围布置好采样装置了。

But I think just we've about setting up sampling arrays on the space station.

Speaker 1

近地空间早就被我们污染得够呛了,不只是太空垃圾,连微生物都多得离谱。

We've contaminated near earth space pretty extensively not just with junk but with microorganisms to an extreme.

Speaker 1

最精彩的故事来了——我兄弟在NASA工作,他告诉我的,我这会儿说出去他怕是要挨骂:下次你看到流星的时候,其实以前宇航员在空间站里都是直接把厕所粪便排到太空里,后来才发现这玩意儿把太空污染得太厉害了。

Think that the most exciting story, my brother is here who works with NASA, he sent it to me, I'll probably get him in trouble for telling this story but next time you see a shooting star, so in the space station they used to just pump out the commodes into space and they realized they were really contaminating space.

Speaker 1

所以现在他们把粪便装进不锈钢容器,再扔回轨道上。

So now they pack them into the waste material into stainless steel containers and launch it back into orbit.

Speaker 1

所以啊,你看到流星的时候,那可不是普通的星星,那是从太空掉下来的‘好东西’。

So when you see a shooting star, that's good shit from space.

Speaker 0

我们之前请过一位嘉宾,叫拉斯特·施韦卡特,是位宇航员。

One of our previous speakers was Rusty Schweikert, one of the astronauts.

Speaker 0

他说,他在轨道上时,最美丽的景象之一就是日落时的尿液排放。

He said that when he was in orbit, one of the most beautiful things you see in orbit is what they call a urine dump at sunset.

Speaker 0

尿液喷出来的时候,阳光照进去,地球在下面一片漆黑,那景象美得不得了。

As it sprays out, of course, the sun blasts into it, the earth is dark below, and it's quite gorgeous.

Speaker 0

现在他们也不这么做了。

They don't do that either.

Speaker 1

除非有感染,不然尿液应该是无菌的,不过……

Well, unless they have disease, the urine should be sterile, but

Speaker 0

尿液本来就是无菌的。

The urine should be sterile.

Speaker 0

我们在军队里学过,可以用尿液来清洗伤口。

We were taught in the army to use it as a as a on wounds.

Speaker 0

对吧?

Right?

Speaker 0

因为它特别干净,拿来冲洗伤口完全没问题。

Because it's it's so sterile you can wash them.

Speaker 0

你在越南的时候没这么干过?

Didn't you do that in Vietnam?

Speaker 1

没有。

No.

Speaker 1

我是海军的。

I was in the navy.

Speaker 1

我们有更先进的办法。

We had better techniques.

Speaker 0

更贵呗。

More expensive.

Speaker 0

当兵的谁不省着点花。

We all save money in the army.

Speaker 0

有个问题来自泰勒·埃莫森。

Here's a question from Tyler Emerson.

Speaker 0

你当时是反对还是支持公布1918年流感病毒的基因组?

Were you against the publication of the 1918 influenza flu genome or for it?

Speaker 0

为什么呢?

Why or why not?

Speaker 0

我记得比尔·乔伊和我们另一位演讲者雷·库兹韦尔都强烈反对这件事。

I remember Bill Joy and one of our other speakers, Ray Kurzweil were ferociously against that.

Speaker 1

是的。

Yeah.

Speaker 1

当时这么做 absolutely 是对的,原因如下。

It was it was absolutely the right thing to do and here's why.

Speaker 1

当时看那个基因序列,虽然我们研究所是全球两大主要测序机构之一,负责测序了大部分流感病毒样本,

Looking at that sequence, it was not obvious even though comparing it to my institute is one of two major institutions sequencing most of the viral isolates from around the world.

Speaker 1

但光看1927年的流感序列,根本看不出它为啥这么致命。

We could not tell looking at the '27 flu sequence why it was so virulent.

Speaker 1

我们也不知道该怎么针对它研发出有效的疫苗。

And we didn't also know how to make the right vaccines against it.

Speaker 1

所以不仅公开序列是正确的决定,我觉得后来政府新成立的委员会批准CDC用合成基因技术重建它,也是对的。

So not only publishing it was the right thing, I think the this new committee in the government approving it to be made through the synthetic genomic processes at the CDC.

Speaker 1

这其实是第一个真正意义上的《侏罗纪公园》场景,因为RNA是从1918年去世的一名士兵和一位埋在永久冻土中的女性身上提取出来的。

It's actually the first true Jurassic Park scenario because it was RNA isolated from a soldier that had died in 1918 and also a woman that was buried in the permafrost.

Speaker 1

她的肺里还保存着那段RNA。

The RNA still exists in her lungs.

Speaker 1

科学家把这段RNA测了序,然后在实验室里重新合成了病毒。

The RNA was sequenced and the virus regenerated in the laboratory.

Speaker 1

现在我们知道是什么让这个病毒如此致命,也能据此筛查风险,新疫苗也正在针对这些特性研发。

We now know what parts of the virus lead to its extreme lethalness and we can now screen for that and also new vaccines are being designed against that.

Speaker 1

这可能是流感病毒研究领域最重要的突破之一。

So it's probably gonna be one of the most important breakthroughs in at least flu virus virology.

Speaker 1

我觉得比尔·乔伊那些人,对这类研究特别担心,其实完全是想岔了——他现在自己反而在资助一堆公司干同样的事。

I I think killjoy and others that really worry about these things, you know, just just take the wrong approach and, you know, you know, he he's now funding all kinds of companies to do the same thing.

Speaker 0

拉里·布里连特和谷歌.org,还有那些密切关注疫情动向的人,都在努力阻止下一场大流行。

Larry Brilliant and Google dot org and and the guys who are paying close attention to where trying to head off the next pandemic.

Speaker 0

他们的口号就是:早发现,早应对。

And, you know, the the mantra there is early detection, early response.

Speaker 0

这些东西能帮助早期发现吗?

Is this stuff gonna help early detection?

Speaker 0

我们能不能在更贴近地面的地方做监测,别让疫情的发现总是从医院里死去的护士开始?

Can we do monitoring much closer to the ground so that the detection of a pandemic doesn't begin with dead nurses in a hospital somewhere?

Speaker 0

读取

Reading

Speaker 1

基因测序当然可以。

the genetic code certainly can.

Speaker 1

不过这事儿还是挺让人惊讶的,我之前提过,全球做科学采样其实挺难的。

It's still amazing though, I mentioned some of the issues which are doing scientific sampling around the world.

Speaker 1

有些国家,尤其是东南亚地区,甚至中国和俄罗斯,都不想让外界知道他们有多少流感病例。

There's a number of countries particularly in Southeast Asia and even China and Russia to some extent that don't want the world to know how much flu they have.

Speaker 1

样本很难运出来。

It's hard to get the samples out.

Speaker 1

所以很多时候,都是人死了,我们才听说有疫情。

So quite often you hear first about people dying than getting the samples.

Speaker 1

所以技术是现成的。

So the technology is there.

Speaker 1

要是全球都部署起来,实时检测根本不是问题。

You know, if it was set up around the world, it would be easy to get instant detection.

Speaker 1

但问题在于我刚说的那个政治障碍,还有航空运输。

The problem is the political problem that I just mentioned and air transportation.

Speaker 1

我们亲眼看到SARS从新加坡多快就传到了多伦多。

We saw how fast SARS moved from Singapore to Toronto.

Speaker 1

幸运的是,SARS的传染力远不如流感病毒。

Fortunately, SARS is not anywhere near as virulent as is the flu virus.

Speaker 1

所以我们得加强监测,但我真觉得,我们现在有的合成基因技术,才是能及时研发出疫苗的关键。

So we need to step up the surveillance, but I actually think the synthetic genomic techniques that we have are what's gonna create vaccines in time.

Speaker 1

现在我们是又晚了一年,还缺钱。

We're year late and a dollar short right now.

Speaker 1

要是现在来个超强毒株,我们可就真悬了。

So if this was a really virulent virus right now, we'd be in serious difficulty.

Speaker 1

疫苗的有效率只有百分之四十左右。

The vaccine is only what forty percent effective.

Speaker 1

从识别出当前病毒到赶在疫情前生产出疫苗,整个流程太慢了,根本来不及。

There's just not time with the slow processes from even knowing what the current virus is to getting the vaccine in time.

Speaker 1

所以我们得彻底改变这个状况。

So we need to change that dramatically.

Speaker 0

你说的‘即时检测’,是指这周、本月,还是这小时就能做到?

So instant virus means this week or this month or this hour?

Speaker 0

到底能有多快?

What how fast can

Speaker 1

我的意思是,其实完全可以做到在……

you do I mean, it could be done in

Speaker 0

抱歉,我是说‘即时疫苗’。

Instant vaccine, sorry.

Speaker 1

疫苗部分还得靠检测来验证有效性。

Well, the vaccine part needs to be proven in terms of the detection.

Speaker 1

如果我们有样本,一天内就能测序几百甚至上千个病毒分离株。

We can sequence hundreds to thousands of isolates in a day if we have the material.

Speaker 1

现在最大的瓶颈是没法从各国拿到病毒样本。

The rate limiting step is getting the viral isolates from different countries right now.

Speaker 1

疫苗那边得做测试、拿资金、大规模生产,才能知道能不能真赶得上速度。

The vaccine side needs to be tested and funded, built at a scale to see if it can be done fast enough.

Speaker 0

这是来自长NAF基金会的劳拉的问题。

Question from Laura from the Long NAF Foundation.

Speaker 0

你刚才跟我们讲了这里惊人的、全球尺度的生物多样性。

You've been telling us about an incredible richness of really planetary scale biodiversity here.

Speaker 0

那我们还用在乎那只花斑猫头鹰吗?

So should we still give a hoot about the spotted owl?

Speaker 0

嗯,

Well,

Speaker 1

人们似乎更关心那些能用眼睛看到的物种,而不是我们看不见的、极其丰富的微生物世界。

people care more apparently about species that they can see with their own visual acuity than this extreme diversity that we have in the invisible world.

Speaker 1

你看看现在生物学教材,里面讲生物多样性,几乎全都是我们肉眼能看见的东西。

If you look at even modern textbooks in biology, they list diversity as mostly accounting things that we can see with our own eyes.

Speaker 1

而不是那些得靠显微镜或者DNA测序仪才能发现的生物。

Not things that you need a microscope or a DNA sequencer to see and detect.

Speaker 1

我们有各种各样独特的多细胞鸟类和哺乳动物,我觉得都值得保护。

We have all kinds of unique varieties of multicellular birds and mammals that I think are worth protecting.

Speaker 1

但很多正随着我们剧烈改变环境而迅速消失。

A lot of them going out of, you know, out of existence pretty quickly with what we as we change the environment pretty dramatically.

Speaker 0

那这项技术怎么帮上保护它们的忙呢?

How would this technology help that process of preserving that?

Speaker 1

我不觉得它能直接救下猫头鹰,但我们现在不是只有一只金丝雀当预警,而是有成千上万种生物在发声。

I'm not sure it's gonna help the spot at all, but it certainly instead of having a canary in a coal mine, we have tens of thousands of organisms.

Speaker 1

比如说,要是我们在旧金山湾漏油前就采了样本的话……

For example, had we taken the samples out of San Francisco Bay before the oil spill

Speaker 0

对。

Uh-huh.

Speaker 1

我们本可以清楚地告诉你,那次漏油事件后到底发生了什么变化,以及那片海域的生物系统花了多久才恢复。

We could have told you exactly what changed as a result of that oil spill and how long it really took that to recover in terms of the biology that's there.

Speaker 1

所以我们现在在全球范围内努力做的,就是从主要的珊瑚礁区域采集样本。

So that's what we've tried to do on a global basis is get samples from the major coral reefs.

Speaker 1

你知道,大家都喜欢印度洋和其他地方那些美丽的沙滩。

You know, everybody loves beautiful sandy beaches the Indian Ocean and other parts of the world.

Speaker 1

可这些沙滩,其实是珊瑚礁死亡后留下的痕迹。

These are a result of coral reefs dying.

Speaker 1

温度只要升高几度,通常就会让珊瑚礁大批死亡。

Just a few degree temperature change usually ends up killing coral reefs.

Speaker 1

很多人以为是那些能耐受温度变化的共生细菌被杀死了。

Many people think it's because it's killing the symbiotic bacteria that can deal with the temperature changes.

Speaker 1

但现在,我们终于有了第一批数据,至少能开始追踪这些变化了。

But we now have the first measurements to at least try try to do that to track these.

Speaker 1

所以这可能是最彻底的环境影响评估——亲眼看看究竟发生了什么变化。

So it's it's it could be the ultimate environmental impact statement to see what is changing.

Speaker 1

对于海上油井来说,真正监测那里发生的情况可能很有必要。

It's probably good for offshore oil wells to really measure what's happening there.

Speaker 1

那些以为通过向海洋投放铁元素就能获得碳信用的人,

Perhaps these people that think they can get c o two credits by seeding the oceans with iron.

Speaker 1

我们大多数人觉得,这些可能是当今地球上最危险的实验了。

Most of us think those are some of those most dangerous experiments being done on the planet right now.

Speaker 0

咱们再多聊聊这个。

Let's see more about that.

Speaker 0

为什么这么说?

Why is that?

Speaker 1

迹象表明,这可能会对海洋造成不可逆的伤害。

Well, the indications are it could cause irreversible damage to the ocean.

Speaker 1

只要有一点点这种风险,你说我们干嘛要干这种事,就为了让少数几个团体赚钱?

And anything that has even a slight risk of that, you know, why are we doing that so a few groups can make money off of it?

Speaker 1

这简直就是疯了。

It's just an insane experiment.

Speaker 0

有人想让你跟着那次科考,去采样铁元素投放前后的变化。

One wants you to go along in that expedition to sample what happens before and after the iron Yeah.

Speaker 0

就是投放铁元素。

Seeding.

Speaker 0

那具体会怎样呢?

Well, what

Speaker 1

铁是限制性营养元素,你撒一点下去,藻类就会疯狂爆发。

happens so iron is a limiting nutrient, so you sprinkle a little iron on, you get huge algae blooms.

Speaker 1

藻类死后沉入海底,理论上能封存更多碳,但会耗尽大量其他营养物质。

Then the algae dies off and presumably sinks down in the ocean and you get more, but it's going to deplete a lot of other nutrients.

Speaker 1

我们西海岸,尤其是俄勒冈附近,已经出了问题。

We have a problem off the West Coast, particularly off of Oregon.

Speaker 1

现在那儿出现了大片的死亡区。

There's these huge dead zones now.

Speaker 1

一点氧气都没有。

No oxygen whatsoever.

Speaker 1

所以鱼类和哺乳动物游进去了。

So fish mammals swim into there.

Speaker 1

它们基本上是被憋死的。

They basically die from asphyxiation.

Speaker 0

这跟风有关,不是因为铁。

Whatever it's caused by wind, not by iron.

Speaker 1

跟风有关?

By wind?

Speaker 0

对。

Yeah.

Speaker 0

洋流上涌的模式变了。

It's changed the upwelling pattern.

Speaker 0

没错。

Yeah.

Speaker 0

里根说过这话吗?

Did Ronald Reagan say that?

Speaker 0

不是。

No.

Speaker 0

是俄勒冈州的科学家说的。

Scientists in Oregon said that.

Speaker 0

风的变化本身可能就会发生,尤其是现在这么多风力发电。

Changing wind will be its own maybe that'll happen with all this wind generation.

Speaker 0

很多人在家里、浴室、厨房里滥用抗生素。

Lots of people using antibiotics in their personal life, in the bathroom, in the kitchen.

Speaker 0

他们把所有那些细菌都杀光了。

They they head off all those germs.

Speaker 0

照你这么说,一点希望都没有了。

From what you're saying, there's no hope.

Speaker 1

岂止是没有希望。

Well, not only no hope.

Speaker 1

我的意思是,对我们人类来说,最糟糕的事莫过于活在一个完全无菌的环境里。

I mean, if the worst thing for us as a species is to try and live in a sterile environment.

Speaker 0

好吧。

Okay.

Speaker 1

细菌是我们生理机能中关键的一部分。

Bacteria are a key part of our physiology.

Speaker 1

所以我觉得,你根本逃不开细菌——这地球上可能有几千万甚至上亿种细菌,但绝大多数根本不在乎我们。

So I think the notion that you can never escape bacteria, you know, of the tens, maybe hundreds of millions of species on this planet, most of them don't care about us.

Speaker 1

真正会感染人类的,其实就那么几种,哪怕那些和我们共生的细菌里,也寥寥无几。

That there's only a few handfuls that truly infect humans even the ones that you know share our bodies.

Speaker 1

大多数根本不是病原体。

Most of those are not pathogens.

Speaker 1

但没人搞清楚,到底是哪个临界点一变,那些一直和我们和平共处的细菌突然就致病了。

It's not understood at all the thresholds that change when all of a sudden bacteria we have associated with start causing disease.

Speaker 1

但真正这么干的,其实少之又少。

But very few of them do.

Speaker 1

问题在于,这些化学杀菌剂会把所有微生物一锅端,结果反而催生了严重的变异。

The trouble with these the chemical killers kill the whole spectrum of life and leads to major mutations.

Speaker 1

所以现在出现了新型耐药性金黄色葡萄球菌,你想想,去年死于这种细菌的人,比美国死于艾滋病的人还多。

That's why we now have, you know, I think when you think about new emerging infections, the new completely antibiotic resistant Staph aureus, it's now killed more people in this last year than HIV in The US.

Speaker 1

这纯粹是因为抗生素用得太滥了。

It's due just to over application of antibiotics.

Speaker 1

我不确定是不是有人太执着于给浴室或双手杀菌,但医疗领域滥用抗生素绝对是主因。

I'm I'm not sure whether it's you contribute any of it to people trying to sterilize their bathrooms or their hands, but certainly to the widespread use of antibiotics in the medical community.

Speaker 1

这种耐药菌传播起来有多快,现在还说不准。

It's not clear how rapidly that could spread.

Speaker 1

如果你没到快死的地步,现在真别随便去医院——在医院感染金黄色葡萄球菌的概率,比 anywhere else 高多了。

If you're not near death, don't want to go to a hospital right now because you have a higher chance of getting a staph aureus infection in the hospital than you do any place else.

Speaker 1

是这样。

It's

Speaker 0

你们的技术能解决这个问题吗?

Does your technology have a workaround for that?

Speaker 1

目前还不行。

Not right now.

Speaker 1

我的意思是,我们可以尝试组合式地研发新抗生素。

I mean, we can try combinatorial production of new antibiotics.

Speaker 1

海洋里有海量的化学物质还没被探索过,而细菌产生的大多数物质,其实都是用来杀其他细菌的。

With this huge chemical diversity in the ocean that really has not been sampled, most of the chemicals that bacteria produce are to kill other bacteria.

Speaker 1

没错。

Right.

Speaker 1

有些生物我们已经发现了,它们能产生类似柴油的物质。

There there are some organisms that we have that actually produce diesel fuel like materials.

Speaker 1

这些物质闻起来就像柴油,它们用这个来当抗生素,把周围的细菌都干掉。

They actually smell like diesel fuel using that as an antibiotic around them.

Speaker 1

我们可能只发现了环境中实际存在的抗生素的百万分之一。

So we've probably sampled, know, one millionth of the antibiotics that are available in the environment that could be used.

Speaker 1

制药行业根本没动力去研发抗生素和抗病毒药。

There's a complete disincentive in the pharmaceutical industry to make antibiotics and antivirals.

Speaker 1

公司更愿意做慢性病药物,因为利润高得多,比治急性病强多了。

Companies would far rather treat chronic diseases because they can make a much higher profit than treating acute diseases.

Speaker 1

所以像礼来这样的公司,干脆把抗生素部门全关了。

So companies like Eli Lilly completely shut down their antibiotic department.

Speaker 1

我们倒是挖到了几个不错的人才,但说实话,这只能帮上一点忙。

We hired some good people out of that but you know that's helping some areas.

Speaker 1

可现在的情况恰恰相反——我们比任何时候都更需要新的抗生素和抗病毒药物。

But it's we're going the opposite direction right now when we need new antivirals and new antibiotics more than ever.

Speaker 0

这么说来,这其实也回应了之前那个关于职业方向的问题。

So it sounds like one of the career directions to speak to the earlier question.

Speaker 0

大家现在满世界跑热带雨林,找那些能抗癌的次级代谢物,但听你这么一说,海洋可能才是更好的宝库。

So, you know, people are going through the jungles of the world looking for wonderful secondary metabolites that will be useful against cancer and things It like sounds like you're saying that the oceans may be even a better place to collect.

Speaker 0

我倒不觉得……

I don't

Speaker 1

说不上更好,但那儿基本还没被开发过。

know if it's better but it's largely untapped.

Speaker 1

那里的化学物质复杂程度,远超我们化学家现在能合成的任何东西。

The chemical complexity far exceeds what our chemists can make right now.

Speaker 1

但再说一次,新兴的合成生物学给了我们机会去复制和改造这些通路——我们只要把基因路径提取出来,放进细胞里,就能在实验室里合成这些化学物质。

But again the new biology, synthetic biology gives us a chance to replicate and change that because we can just take the gene pathways, put them in cells and make the chemicals in the lab.

Speaker 1

现在有不少人正在考虑,把所有已发现生物体里的这些通路都挖出来,制造出一大批全新的分子,它们的复杂程度远超我们目前用的那些,因为化学合成根本做不出来。

And so a number of people now are thinking about taking these pathways out of all the organisms that we've discovered and just making whole new sets of molecules that just greatly exceed the complexity of what we're currently using because you can't make them chemically in the lab.

Speaker 1

所以我觉得可选的路子多得很。

So I think there's a lot to choose from.

Speaker 1

关键是谁来干、谁来买单,有没有激励机制,甚至能不能把产品推上市场。

It's a question who's gonna do it, who's gonna pay for it, is there the incentives and the the ability to even get stuff out of the market.

Speaker 1

这障碍太大了,我觉得可能正因如此,制药行业才更倾向于开发利润更高的药物,而不是抗生素或抗病毒药。

It's it's a huge hurdle and I think maybe that's why the the pharmaceutical industry is going for much higher profit molecules than antibiotics and antivirals.

Speaker 0

当你跟这个行业的人聊,或者前几天你跟石油行业的人聊的时候,你们都聊些什么?

When you speak to people in that industry or the other day when you're speaking to people in the oil industry, what do you talk to them about?

Speaker 0

你会跟他们说这些吗?对吧。

You say this kind of stuff or Yeah.

Speaker 0

那你跟石油公司的人到底说了啥?

What did you say to the oil guys?

Speaker 1

我跟他们说,颠覆性技术就要来了,他们不仅得做好准备,还得主动参与,帮着加速这个进程。

I told them that they that disruptive technologies were coming and that they not only need to prepare for it but contribute to it to help it come faster.

Speaker 1

所以他们是解决问题的一部分,不只是问题本身。

So they're part of the solution, not just part of the problem.

Speaker 0

他们都在鼓掌。

They're clapping.

Speaker 0

那些人真的鼓掌了?

Did those guys clap?

Speaker 1

反响挺好的。

I I I it was a good response.

Speaker 0

我的意思是,

I mean,

Speaker 1

我总算平安出来了。

I I got out of there alive.

Speaker 0

这可是个好兆头。

It's a good sign.

Speaker 0

你刚才还说,压载水换水根本没用,你知道的,海量的海洋细菌从一个热闹的海域被带到另一个热闹的海域,来回倒腾。

You were in vain a moment ago against ballast swapping that, you know, vast quantities of ocean bacteria picked up in one seething part of the world and released into another seething part of the world and swapped back and forth.

Speaker 0

你觉得这本身就有害吗?还是怎么说?

Do you see this as inherently harmful or or what?

Speaker 1

这很难说,毕竟已经这么干了这么多年了。

It's hard to know because it's been going on for so many years.

Speaker 1

像斑马贻贝幼虫这种东西一来,确实会造成大麻烦,影响范围很广。

It's certainly harmful when you get things like zebra butt muscle larvae and you know, that's a huge impact in areas.

Speaker 1

现在东海岸出现的这些新物种,到底是因为压载水带来的,还是人家把水族箱的水直接倒进海里,还不太清楚。

It's not clear whether all these new species in on the East Coast are are from that or just people emptying out their aquariums.

Speaker 1

这些生物其实是有选择性的,比如光照条件,我之前跟你举过例子。

You know, there's a certain selectivity with these organisms based on things such as sunlight as I gave you an example of.

Speaker 1

到底会怎样,对环境影响有多大,现在还不明确。

It's not clear what happens and how much it changes the environment.

Speaker 1

以前从来没人认真测过。

Nobody's measured it before.

Speaker 1

所以不管它是增加了还是减少了生物多样性,我们一再看到,一旦出现失衡——比如环境中突然冒出以前没有的新病毒,或者某些生物突然成为优势物种——后果往往都很灾难性。

So whether it's contributing to more diversity or less diversity, we know over and over again when you get an imbalance, new viruses appearing in an environment that weren't there before, new organisms that become dominant, it has a pretty catastrophic response.

Speaker 1

你看那些沿海的牡蛎产业,比如切萨皮克湾,以前可是牡蛎产量大户。

Look at all the oyster industries around, you know, the Chesapeake Bay used to be a huge oyster industry.

Speaker 1

旧金山湾以前也是。

San Francisco Bay used to be.

Speaker 1

现在呢,有病毒把那儿的牡蛎全给灭了。

There's now viruses that have wiped out all the oysters.

Speaker 1

这些病毒到底从哪儿来的,现在到底是什么,都没人说得清。

Maybe it came from nobody knows where they came from or even what they are right now.

Speaker 1

说真的,这种做法听起来就像个蠢实验,不过现在大多数船在跨洋航行时,都会逐步更换压载水了。

You know, it seems like a silly experiment to do and now most ships change their ballast water sort of progressively as they cross oceans.

Speaker 1

他们连油污和其他废物也一并排掉,不过——

They also dump all their oil and things out too but

Speaker 0

听上去我觉得,我那些环保圈的朋友该赶紧推动你提到的这些技术,好好监测、诊断这些事儿才对。

It sounds to me like my fellow environmentalists should be jamming ahead in some of the technology you're talking about to or monitoring for all these various things, doing diagnostics.

Speaker 0

你光看一个样本里的基因组成,就能判断它来自世界哪个地方、是什么样的水。

Like, you were able to tell just by looking at the population of genes in a particular sample what part of the world it came from, what kind of water it came from.

Speaker 0

所以同样的道理,应该也能用在人的蛀牙和其他方面上。

So presumably the same kind of things will go on with human cavities and all the rest of it.

Speaker 0

不仅能知道是谁,还能看出他们具体有什么问题等等。

Not only be able to tell who but what their problems are and all the rest of it.

Speaker 1

而且你还能通过这个判断人来自哪里。

Well, you can also tell where people have come from.

Speaker 1

比如有研究显示,士兵刚被派到沙漠里没多久,口腔里的微生物就全换成了当地环境里的那些。

It's been shown, for example, as we send soldiers to the desert in a very short time in the desert, all the bugs in their oral cavity swap out to what's in that local environment.

Speaker 1

但目前没人清楚这对长期健康或疾病有什么影响,尤其是当环境再次发生变化的时候。

Nobody really knows what impact that has on long term health or disease and as this happens and and the environments get changed again.

Speaker 1

所以咱们政府里有些部门,已经在用这些数据来追踪人了。

So there are certain branches of our government that are using this information to try and track people.

Speaker 1

有人问我,我们能不能用这方法,通过下水道里的DNA来找到本·拉登。

I I I was asked if I if we could use these techniques to track bin Laden by finding his DNA in sewer water.

Speaker 1

我说了,我可不是干这事儿的人选。

I I I said I was not the right guy to do that experiment.

Speaker 1

所以啊。

So

Speaker 0

相信我,早有人在计划做这个实验了。

Trust me, there are others who are being planned to do it.

Speaker 0

顺便说一句,这在动物身上早就用得很多了。

And it's done a lot with animals, by the way.

Speaker 0

比如粪便,你就能

With a scat, you can

Speaker 1

看出一大堆信息,

tell a whole lot

Speaker 0

比如它们在哪待过、干了啥、吃啥,诸如此类。

about, you know, where they were, what they do, what they eat or Yeah.

Speaker 0

估计有了这技术,以后会更准。

Presumably that will increase with this.

Speaker 0

不过,我那些环保圈的朋友对转基因食品、棉花、农作物这些东西都特别怀疑。

But also my fellow environmentalists are highly dubious about genetic modification in foods and cotton and crops and things like that.

Speaker 0

你对这个怎么看?

What's your view on that?

Speaker 1

我觉得吧,要在每个领域都站对立场,其实挺难的。

Well, I think, you know, it's hard to be right all the time in each area.

Speaker 1

现在的环境变化得太快了,我们真的很难完全意识到。

It's, you know, we have a dramatically changing environment that it's really hard to realize.

Speaker 1

我们都习惯觉得,生活就像我们从小熟悉的那样,简单又安稳。

You know, we we all like to think life is nice and simple as we've each of us have known it.

Speaker 1

所以我才总喜欢拿人口数字来说事儿,想让这事儿更贴近咱们个人的生活。

And that's why I try to use the number about the population and trying to, you know, personalize it.

Speaker 1

就在我们这一辈子的时间里,世界已经变得完全不一样了。

It's a very different world changing within a single lifetime.

Speaker 1

你开头不是也提到过这一点吗?

You mentioned that in your introduction.

Speaker 1

我们得想办法应对即将达到九十亿的人口。

We have to find a way to cope with the soon to be 9,000,000,000 people.

Speaker 1

你知道,环境正在变化。

You know, the environment is changing.

Speaker 1

如果我们不聪明地应对,人们就会直接砍伐焚烧,种那些最赚钱的作物,不管是当燃料还是口粮。

If we don't do it intelligently, people are just gonna do slash and burn to grow whatever is the most profitable crop either to provide fuel or food for their populations.

Speaker 1

现在我们看到的正是这种情况。

That's what we see happening right now.

Speaker 1

所以我觉得环保人士应该第一个拥抱这些新技术,而不是排队去阻拦它们。

So I think environmentalists should be the first to embrace these new technologies, not be lining up to try and stop them.

Speaker 1

我觉得,要完成这个转变,需要很多团体多动动脑筋。

It's gonna take, I think, a little bit more thinking on the part of numerous groups to make that transition.

Speaker 0

有人会问,鱼的基因放到番茄里,这也太怪了吧。

Well, there's a question and people say, okay, a fish gene and a tomato is just too weird.

Speaker 0

这不符合达尔文的进化论。

And and Well that's not Darwinian.

Speaker 0

而且啊

And and

Speaker 1

但番茄本身也不是什么‘达尔文式’的天然产物,你知道吧,没人会为了吃野生番茄去拼命。

But tomatoes are not Darwinian in the sense that, know, people fight for eating their natural tomatoes.

Speaker 1

野生番茄,就是那种小得像我拇指大小的青果子,根本不能吃,特别苦。

You know, natural tomatoes, a small green thing about the size of my thumb that's non edible, it's really bitter.

Speaker 1

我们人类早就在这颗星球上长期选育各种作物了,大多数人以为的‘天然’,其实大多是盲目改造出来的。

So we've been doing selection of species on this planet for a long time and what most people think is natural has been engineered usually blindly.

Speaker 1

现在我们懂了基因和基因组,如果有人提议,干脆把不同物种的基因随机拼在一起,看看能出什么结果——

You know, now that we know about the genetic code and the genome, if people are gonna propose, let's just randomly mix these genomes together from these diverse species, let's see what we get.

Speaker 1

这叫农业,就是大伙儿今晚来之前一直在吃的东西。

It's called agriculture, it's what everybody ate before coming here tonight.

Speaker 1

所以我们得把这事放到过去一百年里,人类随机混搭植物、动物、细菌的现实背景里来看。

So I think we need to put it in the context of what the reality has been going on in the last century of randomly mixing plant, animal, bacterial organisms together.

Speaker 1

所以,鱼的基因和番茄结合,到底哪里不自然了?

So what's so unnatural about a fish gene and a tomato?

Speaker 1

其实这两个基因本来就在你的基因组里。

Both those genes exist in your genome anyway.

Speaker 0

所以我从你、还有霍金斯和其他做这行的人那儿听到的是,基因本身挺能到处跑的。

So one of the things I'm getting from you and from Hawkins and others working in this field is that genes themselves are pretty migratory.

Speaker 0

它们在基因组之间、物种之间、属之间到处迁移,哪儿都去。

They wander from genome to genome and species to species and genus to genus and all over the place.

Speaker 0

你也是这么看的吗?

Is this your sense of things?

Speaker 1

事实上,我最近参加了一个节目,和理查德·道金斯一起,我就跟他说,我现在看这个世界完全是基因中心的视角。

Well, in fact, I was on a recent program with Richard Dawkins and I told him that I've begun to think of the world totally in a gene centric point of view.

Speaker 1

对。

Mhmm.

Speaker 1

基因组其实就是这些基因的各种独特组合。

That genomes are just unique combinations of those.

Speaker 1

基本上,组合方式是无限多的。

There's basically an infinite number of combinations.

Speaker 1

我们只知道其中一小部分。

We know a few of them.

Speaker 1

就像我之前说的,那些大的我们靠肉眼就能看到。

We see the big ones as I mentioned with our own visual acuity.

Speaker 1

地球上还有几百万,甚至上千万种等着我们去发现。

We have another several million if not tens of millions to discover on this planet.

Speaker 1

如果我们将来把这些当作设计模块来用,就能真正利用这些信息做出些独特的东西。

And if we use them as design components going forward, we can really harness that information to do something unique.

Speaker 1

基因组的结构很重要。

You know, genome structure is important.

Speaker 1

调控机制也极其关键。

Regulation is very important.

Speaker 1

从单细胞生物到拥有十万亿个细胞的生物,中间需要大量精密的调控。

When we go from single cell organisms to having a 100,000,000,000,000 cells, there's a lot of key regulation that does go on.

Speaker 1

我们离完全复制这个过程还差得远,但正用这些工具去理解它——我觉得,越早搞懂,我们在这儿生存下去的机会就越大。

We're a long way from mimicking that but we're using these tools to try and understand it to you know, I think the sooner we understand it, the better chance we have surviving here.

Speaker 0

你想往更复杂的层面走,比如真核生物和更大的动物,对吧?

You want to move on up the complexity chain into eukaryotes and bigger animals in terms of

Speaker 1

我觉得这至关重要。

I I think it's essential.

Speaker 1

说到长远的未来,很多人认为人类只有两条生存出路。

Know, when you talk about the long now futures, many people have argued humans have two chances for survival.

Speaker 1

要么去找个新星球去殖民,要么干脆改造人类,让我们能适应更高的二氧化碳浓度,或者改变生理结构,好在我们自己搞坏的地球上活下来。

Let's find another planet to go contaminate and move there or let's engineer humans to survive in higher CO2 concentrations or altered biology so we can survive on the best we're making here.

Speaker 1

这两种观点,现在很多人都在这么想。

Those are the two long term current views that many people hold for humanity.

Speaker 1

但我更希望我们能有第三条路——趁还没到那一步,先想办法改造环境。

I'd like to think we have a third alternative of trying to change the environment before we get to that point.

Speaker 1

当然了,如果把设计思维用在植物上,比如专门培育一种能在干旱环境里生存、几乎不用水、甚至能靠海水生长、还能产出燃料或食物原料的植物,再配上抗病能力、可控的繁殖特性,那可太棒了,你说是吧?

But certainly engineering, if you apply design theory to plants, you just design a plant for a specific purpose that will live in an arid environment, need very little water, maybe even live off of salt water and produce useful feedstocks for fuels or food, that could be a pretty nice thing, designing disease resistance, the kind of replication you want, etcetera, you know.

Speaker 1

我们本身就是活着的机器。

We are living machines.

Speaker 1

我们是可以被设计的,我认为在你们基金会关注的时间范围内,改造人类是不可避免的。

We are designable and I think it will be in the time course that your foundation looks at, it will be inevitable to engineer humans.

Speaker 0

太好了。

Great.

Speaker 0

还有两个问题。

Two more questions.

Speaker 0

一个是来自JD Ross Leahy的。

One from JD Ross Leahy.

Speaker 0

你在解释时用了好多计算机的比喻,比如启动、软件、硬件。

You use a lot of computer metaphors in your explanations, boot it up, software, hardware.

Speaker 0

你觉得计算机程序和你研究的生物体之间,最主要相似和不同的是什么?

What do you see as the main similarities and the main differences between computer programs and the organisms you work work with?

Speaker 0

啊?

With?

Speaker 1

目前我们还没几个计算机能靠自己的软件来制造硬件呢。

Well, we don't have too many computers yet that can build their own hardware from their software.

Speaker 1

我觉得这是个动态的过程,有些人正朝着这个方向努力。

I think dynamic, you know, some people are hoping to get there.

Speaker 1

说实话,我们在某些生产线上已经走了一半了。

You know, we're partway there in some assembly lines.

Speaker 1

生物系统能做到非常灵活的自我构建。

Biological systems can do this very dynamically.

Speaker 1

你真的能用软件直接造出硬件来。

You can actually build the computer from the software.

Speaker 1

我觉得至少目前来看,这是个关键区别。

I think that's it's an important difference at least for now.

Speaker 1

比如微生物,它们能大规模复制自己,产出工业可用的产物。

I think the microorganisms for example can produce things on scale, copies of themselves on scale that can be used for industrial purposes.

Speaker 1

你看看垃圾填埋场,我们其实也在大规模生产电脑。

When you look at landfills, obviously we're producing computers on some sort of scale.

Speaker 0

但是

But

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