You know, I've talked about some of these projects before -- about the human genome and what that might mean, and discovering new sets of genes. We're actually starting at a new point: we've been digitizing biology, and now we're trying to go from that digital code into a new phase of biology with designing and synthesizing life.
在這之前我已經討論過這些計畫中的一部分, 關於人類基因體和它們的意義, 以及發現新的基因。 我們事實上是在開啟一個新的轉捩點: 我們在發展數位生物學。 並且現在我們正嘗試從那些數位編碼走向 一個生物學的全新階段, 去設計與人工合成生命。
So, we've always been trying to ask big questions. "What is life?" is something that I think many biologists have been trying to understand at various levels. We've tried various approaches, paring it down to minimal components. We've been digitizing it now for almost 20 years; when we sequenced the human genome, it was going from the analog world of biology into the digital world of the computer. Now we're trying to ask, "Can we regenerate life or can we create new life out of this digital universe?"
我們總是試著提出一些重要的基本問題。 例如“生命的本質是什麼?”我想是許多生物學家 不斷地嘗試在 在不同層面去理解的問題。 我們嘗試了許多方法, 將生命解構成最小的組成單元。 到目前我們幾乎已經用了20年來將其數位化。 當我們在定序人類基因體時, 我們從生物學的類比世界 走進了電腦的數位世界。 現在我們試著去探討,我們是否能夠重新打造生命, 或者我們是否能從這個數位世界中, 創造新的生命?
This is the map of a small organism, Mycoplasma genitalium, that has the smallest genome for a species that can self-replicate in the laboratory, and we've been trying to just see if we can come up with an even smaller genome. We're able to knock out on the order of 100 genes out of the 500 or so that are here. When we look at its metabolic map, it's relatively simple compared to ours -- trust me, this is simple -- but when we look at all the genes that we can knock out one at a time, it's very unlikely that this would yield a living cell. So we decided the only way forward was to actually synthesize this chromosome so we could vary the components to ask some of these most fundamental questions. And so we started down the road of: can we synthesize a chromosome? Can chemistry permit making these really large molecules where we've never been before? And if we do, can we boot up a chromosome? A chromosome, by the way, is just a piece of inert chemical material. So, our pace of digitizing life has been increasing at an exponential pace.
這是一種微生物的基因序列圖, 名叫生殖道黴漿菌, 它有著生物物種裡最小的基因體 可以在實驗室中自我複製。 我們在試著看看是否 我們能找到一種更小的基因體。 我們能夠以數百基因的尺度去剔除 這500個基因,或者是你們現在所看到的。(生殖道黴漿菌只有521個基因) 但當我們來看它的新陳代謝的時候, 這其實是相對簡單的 相對我們來說的話。 相信我,這算簡單的。 但當我們在看所有這些所有基因 這些我們可以一次剔除一個的基因, 很難相信這種剔除基因的方法能產生出 一個活生生的細胞。 所以,我們認為唯一能繼續研究的方法 就是人工合成這些染色體 以便我們能改變它的組成 來繼續問這些最基本的問題。 於是我們開始沿著這條思路往下走 “我們能人工合成染色體嗎?” 化學方法真的可以讓我們製造 這些我們從未合成過的 超大分子嗎? 而且,就算我們可以,我們能啟動它嗎? 染色體,順便說下,只是一些無活性的化學物質。 我們來看,我們將生命數位化的的步調不斷地 以指數成長。
Our ability to write the genetic code has been moving pretty slowly but has been increasing, and our latest point would put it on, now, an exponential curve. We started this over 15 years ago. It took several stages, in fact, starting with a bioethical review before we did the first experiments. But it turns out synthesizing DNA is very difficult. There are tens of thousands of machines around the world that make small pieces of DNA -- 30 to 50 letters in length -- and it's a degenerate process, so the longer you make the piece, the more errors there are. So we had to create a new method for putting these little pieces together and correct all the errors.
我們編寫基因編碼的能力 進步得卻非常緩慢, 不過也還是在增加的。 我們最近的研究將會把編寫基因的速度提升至指數曲線的程度。 我們於15年前開始這項工作。 實際上它經過了好幾個階段。 在我們做最初的試驗前,先進行了一次生物倫理學的評估。 但結果是人工合成DNA 是非常困難的。 全世界有十幾萬台設備 在製造小片斷的DNA, 長度在30到50個字元, DNA 的合成是一個衰減的過程,製造的片斷越是長, 所產生的錯誤就越多。 所以我們得發展一種新的方法 把這些小片斷組合在起並修正所有產生的錯誤。
And this was our first attempt, starting with the digital information of the genome of phi X174. It's a small virus that kills bacteria. We designed the pieces, went through our error correction and had a DNA molecule of about 5,000 letters. The exciting phase came when we took this piece of inert chemical and put it in the bacteria, and the bacteria started to read this genetic code, made the viral particles. The viral particles then were released from the cells and came back and killed the E. coli. I was talking to the oil industry recently and I said they clearly understood that model.
我們的第一次嘗試,從Phi X 174基因體(噬菌體) 的數位資訊開始。 它是一種能殺死細菌的小型病毒。 我們設計了它的基因片斷,並經過了錯誤校正, 於是就擁有了一條 長約5,000字元的DNA。 最令人興奮的階段是當我們把這段沒有活性的化學物質 放入細菌體內, 細菌開始讀取基因編碼, 並製造了病毒粒子。 接著病毒粒子從細菌中被釋放出來, 再返回來殺死了細菌 (E.coli,大腸桿菌,革蘭氏陰性菌)。 我最近與石油行業有一些交流, 我覺得他們對這個模式理解得非常透徹。
(Laughter)
(笑聲)
They laughed more than you guys are. (Laughter)
他們比你們笑得大聲多了。
And so, we think this is a situation where the software can actually build its own hardware in a biological system. But we wanted to go much larger: we wanted to build the entire bacterial chromosome -- it's over 580,000 letters of genetic code -- so we thought we'd build them in cassettes the size of the viruses so we could actually vary the cassettes to understand what the actual components of a living cell are. Design is critical, and if you're starting with digital information in the computer, that digital information has to be really accurate. When we first sequenced this genome in 1995, the standard of accuracy was one error per 10,000 base pairs. We actually found, on resequencing it, 30 errors; had we used that original sequence, it never would have been able to be booted up. Part of the design is designing pieces that are 50 letters long that have to overlap with all the other 50-letter pieces to build smaller subunits we have to design so they can go together. We design unique elements into this.
因此我們認為這種情況實際上 是一種軟體能在一個生物系統內 打造自己的硬體。 但我們還想再擴大規模。 我們希望製造整條細菌染色體。 一條超過580,000字元長度的基因編碼。 我們認為應該在以病毒大小的基因卡匣中建造它們 這樣我們可以改變這些基因卡匣 來理解 一個活細胞的實際組成是什麼? 設計 (準確的掌握正確的資訊) 是非常重要的, 並且如果你在電腦上開始使用數位資訊, 那這些數位資訊必須十分準確。 當我們在1995年第一次定序這基因體時, 準確率的標準是每10,000個鹽基對一個錯誤。 實際上我們發現,在重新定序時, 平均是30個錯誤。如果我們使用原先的序列, 這組基因永遠不可能被啟動。 設計工作的一部分是 設計50個字元長度的片斷 並和其他的50字元長的片段相互重疊 以構建較小的次單元。 我們要設計使他們能組合在一起。 因此我們在裡面設計了一個特別的元素。
You may have read that we put watermarks in. Think of this: we have a four-letter genetic code -- A, C, G and T. Triplets of those letters code for roughly 20 amino acids, such that there's a single letter designation for each of the amino acids. So we can use the genetic code to write out words, sentences, thoughts. Initially, all we did was autograph it. Some people were disappointed there was not poetry. We designed these pieces so we can just chew back with enzymes; there are enzymes that repair them and put them together. And we started making pieces, starting with pieces that were 5,000 to 7,000 letters, put those together to make 24,000-letter pieces, then put sets of those going up to 72,000.
你們可能聽說過我們在其中加入了浮水印。 想想看 基因編碼有四個字元:A、C、G和T。 三個字元的不同組合 編碼了大約20種氨基酸 而每種氨基酸有其相對應的 基因編碼字元組合。 所以我們能使用基因編碼來撰寫詞彙 句子,想法。 最初,我們所做的就是用它來簽名。 有些人有點失望我們沒用它來做首詩。 我們設計了這些片斷 讓它能被酵素來裁切。 這些酵素是用來修復他們並把他們組合在一起的。 接著我們開始製造片斷, 從7,000字元長度的片斷開始, 把他們組合在一起製造出24,000字元長度的片斷, 再把幾組片斷合併,變成了長72,000字元的片斷。
At each stage, we grew up these pieces in abundance so we could sequence them because we're trying to create a process that's extremely robust that you can see in a minute. We're trying to get to the point of automation. So, this looks like a basketball playoff. When we get into these really large pieces over 100,000 base pairs, they won't any longer grow readily in E. coli -- it exhausts all the modern tools of molecular biology -- and so we turned to other mechanisms. We knew there's a mechanism called homologous recombination that biology uses to repair DNA that can put pieces together. Here's an example of it: there's an organism called Deinococcus radiodurans that can take three millions rads of radiation.
在每個階段,我們大量產生了這些片斷 因此我們可以給他們定序 因為我們希望發展出一個十分可靠的生產過程 等會兒你就將看見。 我們試著將這些過程自動化 這看起來就像是一場籃球賽的對戰圖 當這些非常大的片斷 超過100,000鹽基對時 他們就很難繼續在大腸桿菌裡長得更長了。 在試盡了各種現代分子生物學的工具後。 我們嘗試其他的方法。 我們知道有個機制叫同源重組, 在生物學上用來修復DNA, 它能把片斷組合在一起, 這裡有一個例子。 有一種微生物名為 耐輻射奇異球菌 能夠承受三百萬雷得 (rads, 輻射單位) 的輻射量。
You can see in the top panel, its chromosome just gets blown apart. Twelve to 24 hours later, it put it back together exactly as it was before. We have thousands of organisms that can do this. These organisms can be totally desiccated; they can live in a vacuum. I am absolutely certain that life can exist in outer space, move around, find a new aqueous environment. In fact, NASA has shown a lot of this is out there.
你能看到在上圖中,它的染色體散佈在各個地方。 暴露在輻射之後經過12到24小時, 它將自己又組合回之前的原狀。 我們有數千種生物有這種能耐。 這些生物能夠完全脫離水。 他們能存活在真空中。 我完全確信外太空存在著生命, 他們四處游走,並找到一個新的有水的環境。 實際上,NASA已經展示過很多這樣的例子。
Here's an actual micrograph of the molecule we built using these processes, actually just using yeast mechanisms with the right design of the pieces we put them in; yeast puts them together automatically. This is not an electron micrograph; this is just a regular photomicrograph. It's such a large molecule we can see it with a light microscope. These are pictures over about a six-second period.
這是我們藉由上述程序所製造出來的染色體分子的真實顯微照片 這些程序,事實上就是在酵母菌中放入我們正確設計的片斷 再利用酵母菌遺傳工程的方法 最後酵母菌會自動地將他們組合起來。 這並不是電子顯微照片; 它僅僅是普通的光學顯微鏡。 這是如此之大的一個分子 我們可以直接用光學顯微鏡觀察它。 這些是間隔約為六秒的照片。
So, this is the publication we had just a short while ago. This is over 580,000 letters of genetic code; it's the largest molecule ever made by humans of a defined structure. It's over 300 million molecular weight. If we printed it out at a 10 font with no spacing, it takes 142 pages just to print this genetic code. Well, how do we boot up a chromosome? How do we activate this? Obviously, with a virus it's pretty simple; it's much more complicated dealing with bacteria. It's also simpler when you go into eukaryotes like ourselves: you can just pop out the nucleus and pop in another one, and that's what you've all heard about with cloning. With bacteria and Archaea, the chromosome is integrated into the cell, but we recently showed that we can do a complete transplant of a chromosome from one cell to another and activate it. We purified a chromosome from one microbial species -- roughly, these two are as distant as human and mice -- we added a few extra genes so we could select for this chromosome, we digested it with enzymes to kill all the proteins, and it was pretty stunning when we put this in the cell -- and you'll appreciate our very sophisticated graphics here. The new chromosome went into the cell. In fact, we thought this might be as far as it went, but we tried to design the process a little bit further.
這是我們所發表的最新的研究成果。 這是超過580,000字元長的基因編碼。 這也是由人類設定結構並製造的最大的分子。 它的分子量超過3億。 如果我們以10號字體不間斷地將其列印出來。 總共需要142頁 來列印這些基因編碼 好了,那我們該如何來啟動一段染色體,我們該如何活化它? 顯然處理一個病毒非常簡單 處理一個細菌就複雜多了 以真核生物如我們人類來說, 啟動染色體也還算簡單。 你只需取出一個細胞核 然後放入另一個細胞中, 這就是大家所聽到的「複製」的方法。 而在古細菌中,它們的染色體與整個細胞是一體的, 但最近我們也顯示了我們可以做一個完整的移植 將染色體從一個細胞轉移到另一個細胞中 並活化它。 我們從一種微生物中純化出染色體。 大致上,這兩種之間的差別就如同人類和老鼠般。 我們加上了一些新的基因 這樣我們就能篩選這些染色體。 我們用酵素來分解掉 染色體上所有的蛋白質。 當我們將它放入細胞時發生的情況非常驚人 你們應該會喜歡 我們製作得非常精緻的示意圖: 新的染色體進入細胞。 實際上我們原以為這個過程就到此為止了。 但是我們試圖將這個過程設計得更深入一些。
This is a major mechanism of evolution right here. We find all kinds of species that have taken up a second chromosome or a third one from somewhere, adding thousands of new traits in a second to that species. So, people who think of evolution as just one gene changing at a time have missed much of biology.
這是一個重要的演化機制。 我們發現所有接受了 第二段染色體的物種 或來自其他地方的第三方染色體, 其自身增加了數千種新特徵 在一秒鐘內。 原本人們以為在演化的過程中 每次只會有一個基因發生變化 的觀念忽略了生物的許多實際情況。
There are enzymes called restriction enzymes that actually digest DNA. The chromosome that was in the cell doesn't have one; the chromosome we put in does. It got expressed and it recognized the other chromosome as foreign material, chewed it up, and so we ended up just with a cell with the new chromosome. It turned blue because of the genes we put in it. And with a very short period of time, all the characteristics of one species were lost and it converted totally into the new species based on the new software that we put in the cell. All the proteins changed, the membranes changed; when we read the genetic code, it's exactly what we had transferred in.
有一種酵素叫做限制酶 能夠分解DNA 原先細胞中的染色體中 沒有這種酶 而當我們置入一段擁有這種酶的染色體 它表現了出來,並且辨認出 另一段染色體是外來物質, 它就將其消化,最後我們就有了 一個包含有新的DNA的細胞 我們放入的基因導致它變成了藍色。 在非常短的一段時間裡, 所有的原先物種的特徵全部消失了, 並完全轉化成另一新物種 基於我們放入細胞的新軟體。 所有的蛋白質都不一樣了, 細胞膜也改變了 -- 當我們讀取它的基因編碼,它正是我們轉入的那種。
So, this may sound like genomic alchemy, but we can, by moving the software of DNA around, change things quite dramatically. Now I've argued, this is not genesis; this is building on three and a half billion years of evolution. And I've argued that we're about to perhaps create a new version of the Cambrian explosion, where there's massive new speciation based on this digital design.
這可能聽起來像基因體煉金術, 但我們的確能通過轉移DNA軟體, 來劇烈地改變事物。 現在,我要聲明這不是創世紀 -- 這是建立在35億年的演化上的 並且我認為我們可能 會創造新一版的寒武紀大爆發 出現大量的新物種 基於這種數位設計
Why do this? I think this is pretty obvious in terms of some of the needs. We're about to go from six and a half to nine billion people over the next 40 years. To put it in context for myself: I was born in 1946. There are now three people on the planet for every one of us that existed in 1946; within 40 years, there'll be four. We have trouble feeding, providing fresh, clean water, medicines, fuel for the six and a half billion. It's going to be a stretch to do it for nine. We use over five billion tons of coal, 30 billion-plus barrels of oil -- that's a hundred million barrels a day. When we try to think of biological processes or any process to replace that, it's going to be a huge challenge. Then of course, there's all that CO2 from this material that ends up in the atmosphere.
為什麼要這樣做? 我認為出於一些需求我們這樣做的原因是非常明顯的。 我們的人口將在接下來的40年中 從65億變成90億 以我自己來舉例 我出生於1946年 現在世界上就變成了三個人 對於我們中每一個從1946年就存在的人; 在接下來的四十年內,就變成了四個。 我們在為65億人提供食物,潔淨的淡水, 醫藥,燃料上 都十分困難。 換作90億人那更是難上加難了。 我們使用超過50億頓的煤, 300多億桶的石油。 也就是每天一億桶。 當我們嘗試思考生物方法 或者任何能替代它的方法, 這會是一個巨大的挑戰。 接下來,當然, 這份資料是關於CO2 被排放在大氣層中的二氧化碳。
We now, from our discovery around the world, have a database with about 20 million genes, and I like to think of these as the design components of the future. The electronics industry only had a dozen or so components, and look at the diversity that came out of that. We're limited here primarily by a biological reality and our imagination. We now have techniques, because of these rapid methods of synthesis, to do what we're calling combinatorial genomics. We have the ability now to build a large robot that can make a million chromosomes a day. When you think of processing these 20 million different genes or trying to optimize processes to produce octane or to produce pharmaceuticals, new vaccines, we can just with a small team, do more molecular biology than the last 20 years of all science. And it's just standard selection: we can select for viability, chemical or fuel production, vaccine production, etc.
我們現在從全球各地的發現 有了一個包含約兩千萬組基因的資料庫, 並且我樂於把它們看作是未來的設計元件。 電機業只有十來種元件, 再看看從中能得到的多樣性。 目前我們主要的限制來自於 生物學的現實 以及我們的想像力。 我們現在擁有這樣的技術, 是因為有快速的人工合成方法 能做出我們所謂的「組合基因體」。 我們現在所擁有的製造一個大型機器人的能力 能讓我們每天製造一百萬個染色體。 當你想著加工這兩千萬組不同的基因, 並嘗試去優化這些步驟 以產生辛烷或者製造藥物, 新的疫苗, 我們就能改變,即使是一個小團隊, 完成更多的分子生物學工作 比過去20年科學史所做過的還多。 並且這只是標準選擇。 我們可以以生存能力來選擇, 化學或燃料生產, 疫苗生產等等。
This is a screen snapshot of some true design software that we're working on to actually be able to sit down and design species in the computer. You know, we don't know necessarily what it'll look like: we know exactly what their genetic code looks like. We're focusing on now fourth-generation fuels. You've seen recently, corn to ethanol is just a bad experiment. We have second- and third-generation fuels that will be coming out relatively soon that are sugar, to much higher-value fuels like octane or different types of butanol.
這是一張螢幕截圖 截取的是一些我們 實際坐下來工作時在電腦中 真正用來設計物種的設計軟體。 我們並不一定要知道它(設計的物種)看起來是怎樣。 我們確切地知道它們的基因編碼究竟是什麼樣的。 我們目前把焦點放在“第四代燃料”上。 你們最近看到了將穀物轉化成乙醇 只是一個糟糕的試驗。 很快我們將會擁有 第二及第三代燃料。 就是糖轉化成更高價值的燃料 例如辛烷或不同種類的丁醇。
But the only way we think that biology can have a major impact without further increasing the cost of food and limiting its availability is if we start with CO2 as its feedstock, and so we're working with designing cells to go down this road. And we think we'll have the first fourth-generation fuels in about 18 months. Sunlight and CO2 is one method ... (Applause) but in our discovery around the world, we have all kinds of other methods.
但我們認為生物學唯一能 產生一個巨大影響的同時又不 增加食物的支出與限制其可利用性的方法 是在於我們是否能開始用二氧化碳作為它的原料。 所以我們正在進行設計新的細胞能朝這條路發展下去。 並且我們認為將會取得第一份第四代燃料 在18個月內。 陽光和二氧化碳是其中一個方法 -- (掌聲) -- 但我們從全世界各地的發現中, 我們還有許多種其他方法。
This is an organism we described in 1996. It lives in the deep ocean, about a mile and a half deep, almost at boiling-water temperatures. It takes CO2 to methane using molecular hydrogen as its energy source. We're looking to see if we can take captured CO2, which can easily be piped to sites, convert that CO2 back into fuel to drive this process.
這是一種微生物,1996年被記載 它生活在深海。 大約1.5英里深, 幾乎是在沸騰的水溫中。 它將二氧化碳轉化成甲烷 使用氫分子最為它的能量來源。 我們在看是否能把 收集到的二氧化染 它們非常方便就能被引進處理站, 轉化成燃料, 來驅動這個過程。
So, in a short period of time, we think that we might be able to increase what the basic question is of "What is life?" We truly, you know, have modest goals of replacing the whole petrol-chemical industry --
因此在很短的時間內, 我們覺得我們或許可以增加對於"生命是什麼?" 的基本問題的理解。 我們的確 有著替換整個 石油化工行業的小小目標。
(Laughter) (Applause)
(笑聲)(掌聲)
Yeah. If you can't do that at TED, where can you? --
如果你不能在TED做到這些,哪里還有可能呢?
(Laughter)
(笑聲)
become a major source of energy ... But also, we're now working on using these same tools to come up with instant sets of vaccines. You've seen this year with flu; we're always a year behind and a dollar short when it comes to the right vaccine. I think that can be changed by building combinatorial vaccines in advance. Here's what the future may begin to look like with changing, now, the evolutionary tree, speeding up evolution with synthetic bacteria, Archaea and, eventually, eukaryotes. We're a ways away from improving people: our goal is just to make sure that we have a chance to survive long enough to maybe do that. Thank you very much.
成為一項主要的能源。 並且我們也在使用同樣的工具 製造了幾組即時疫苗。 你們都看到今年出現的流感, 我們總是要慢上一年的時間並且在缺乏資金的情況下 才等到有用的疫苗。 我認為這情形是可以改變的 透過預先製造混合疫苗。 這是未來可能會呈現的情況 藉由改造基因, 現在的演化樹 會加速演化的速度 這將會應用到人造細菌,古細菌 最終到真核生物上。 我們正在一條離改善人類生活越來越遠的路上。 我們的目標就是確保我們能有機會活到 足夠長的時間或許就能做到這件事了。非常感謝大家。
(Applause)
(掌聲)