演講MP3+雙語(yǔ)文稿:下一次軟件革命是什么？

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【演講人及介紹】Sara-Jane Dunn

計(jì)算生物學(xué)家薩拉·簡(jiǎn)·鄧恩（Sara-Jane Dunn），致力于生物學(xué)與計(jì)算之間的聯(lián)系，利用數(shù)學(xué)和計(jì)算分析來了解生命系統(tǒng)如何處理信息。

【演講主題】下一次軟件革命：生物細(xì)胞編程

【演講文稿-中英文】

翻譯者 Jiasi Hao 校對(duì) psjmz mz

00:12

The second half of the last century wascompletely defined by a technological revolution: the software revolution. Theability to program electrons on a material called silicon made possibletechnologies, companies and industries that were at one point unimaginable tomany of us, but which have now fundamentally changed the way the world works.The first half of this century, though, is going to be transformed by a newsoftware revolution: the living software revolution. And this will be poweredby the ability to program biochemistry on a material called biology. And doingso will enable us to harness the properties of biology to generate new kinds oftherapies, to repair damaged tissue, to reprogram faulty cells or even buildprogrammable operating systems out of biochemistry. If we can realize this --and we do need to realize it -- its impact will be so enormous that it willmake the first software revolution pale in comparison.

上世紀(jì)后半葉，全然是一個(gè)被科學(xué)革命所定義的時(shí)代：軟件革命。在一種硅半導(dǎo)體材料上對(duì)電子進(jìn)行編程的能力使得我們?cè)S多人曾無法想象的科技、公司和行業(yè)變?yōu)榭赡?。這如今已徹底改變了世界運(yùn)作的方式。不過，本世紀(jì)上半葉將要被一個(gè) 嶄新的軟件革命所轉(zhuǎn)化： 生物軟件革命。在一種名為生物的材料上 對(duì)生物化學(xué)進(jìn)行編程的能力 將會(huì)支持這一革命。如此一來，我們將能夠利用生物特征 去開發(fā)新型療法，去修復(fù)受損組織，去重編缺陷細(xì)胞，甚至利用生物化學(xué)構(gòu)建一個(gè)可編程的操作系統(tǒng)。如果我們能實(shí)現(xiàn)它——而且我們確實(shí)需要實(shí)現(xiàn)它——其影響將會(huì)如此巨大，以至于第一個(gè)軟件革命，相比之下，會(huì)變得微不足道。

01:20

And that's because living software wouldtransform the entirety of medicine, agriculture and energy, and these aresectors that dwarf those dominated by IT. Imagine programmable plants that fixnitrogen more effectively or resist emerging fungal pathogens, or evenprogramming crops to be perennial rather than annual so you could double yourcrop yields each year. That would transform agriculture and how we'll keep ourgrowing and global population fed. Or imagine programmable immunity, designingand harnessing molecular devices that guide your immune system to detect,eradicate or even prevent disease. This would transform medicine and how we'llkeep our growing and aging population healthy.

這是因?yàn)樯镘浖梢宰兏镎麄€(gè)醫(yī)療，農(nóng)業(yè)和能源領(lǐng)域，以及那些被 IT 人員掌控的部門。想象一下可編程植物：能夠更有效進(jìn)行固氮，或可以抵御新型真菌病原體，甚至能夠?qū)⑥r(nóng)作物編程為多年生而非一年生，使你的年產(chǎn)量可以翻倍。這會(huì)改變農(nóng)業(yè)，同時(shí)改變?nèi)虿粩嘣鲩L(zhǎng)的糧食需求的方法?；蛳胂罂删幊痰拿庖吡?，設(shè)計(jì)并利用能夠指導(dǎo)你免疫系統(tǒng)的分子設(shè)備去檢測(cè)、根除，甚至預(yù)防疾病。這將改變醫(yī)療，同時(shí)改變我們?cè)噲D保持不斷增長(zhǎng)且老齡化的人口健康的方法。

02:07

We already have many of the tools that willmake living software a reality. We can precisely edit genes with CRISPR. We canrewrite the genetic code one base at a time. We can even build functioningsynthetic circuits out of DNA. But figuring out how and when to wield thesetools is still a process of trial and error. It needs deep expertise, years ofspecialization. And experimental protocols are difficult to discover and alltoo often, difficult to reproduce. And, you know, we have a tendency in biologyto focus a lot on the parts, but we all know that something like flyingwouldn't be understood by only studying feathers. So programming biology is notyet as simple as programming your computer. And then to make matters worse,living systems largely bear no resemblance to the engineered systems that youand I program every day. In contrast to engineered systems, living systemsself-generate, they self-organize, they operate at molecular scales. And thesemolecular-level interactions lead generally to robust macro-scale output. Theycan even self-repair.

我們已經(jīng)擁有很多能讓生物軟件成為現(xiàn)實(shí)的工具。我們能使用 CRISPR 技術(shù)精確編輯基因。我們能每次重寫一個(gè)遺傳密碼。我們甚至能利用 DNA 開發(fā)一個(gè)合成電路。但是摸索出如何且何時(shí)使用這些工具依舊是一個(gè)試錯(cuò)的過程。它要求極高的專業(yè)性和多年的領(lǐng)域?qū)＞?。而且?shí)驗(yàn)方法難以發(fā)現(xiàn)，往往更是難以復(fù)制。在生物領(lǐng)域，我們傾向僅專注于局部，但我們都知道有些東西，例如飛行，單就羽毛進(jìn)行研究，是無法理解其原理的。所以生物編程還未能像電腦編程那樣簡(jiǎn)單。更糟糕的是，生物系統(tǒng)和你我每天編寫的工程系統(tǒng)幾乎毫無相似之處。相比工程系統(tǒng)，生物系統(tǒng)能自我生產(chǎn)、自我組織，并以分子規(guī)模運(yùn)作。這些分子層級(jí)的相互作用通常會(huì)導(dǎo)致穩(wěn)健的宏觀規(guī)模輸出，它甚至可以自我修復(fù)。

03:16

Consider, for example, the humble householdplant, like that one sat on your mantelpiece at home that you keep forgettingto water. Every day, despite your neglect, that plant has to wake up and figureout how to allocate its resources. Will it grow, photosynthesize, produceseeds, or flower? And that's a decision that has to be made at the level of thewhole organism. But a plant doesn't have a brain to figure all of that out. Ithas to make do with the cells on its leaves. They have to respond to theenvironment and make the decisions that affect the whole plant. So somehowthere must be a program running inside these cells, a program that responds toinput signals and cues and shapes what that cell will do. And then thoseprograms must operate in a distributed way across individual cells, so thatthey can coordinate and that plant can grow and flourish.

試想家中一盆不起眼的植物，比如你家壁爐臺(tái)上的那盆你老是忘記澆水的植物。盡管你會(huì)忘記，那盆植物每天都需要醒來并思考如何分配它所有的資源。它是生長(zhǎng)、進(jìn)行光合作用、產(chǎn)生種子，還是開花？這是這盆植物所需要做出的決定。但一盆植物沒有大腦來弄清這件事。這需要其葉片上細(xì)胞的幫助。它們需要針對(duì)環(huán)境做出反應(yīng)，并且做出影響整盆植物的決定。所以在那些葉片細(xì)胞中必定要有一個(gè)運(yùn)行的程序，一個(gè)能響應(yīng)輸入信號(hào)與提示，以及調(diào)整細(xì)胞行為的程序。之后，那些程序必須以分布式運(yùn)行，覆蓋每一個(gè)細(xì)胞單元，從而進(jìn)行協(xié)作讓植物茁壯成長(zhǎng)。

04:07

If we could understand these biologicalprograms, if we could understand biological computation, it would transform ourability to understand how and why cells do what they do. Because, if weunderstood these programs, we could debug them when things go wrong. Or wecould learn from them how to design the kind of synthetic circuits that trulyexploit the computational power of biochemistry.

如果我們能夠了解那些生物程序，如果我們能夠明白那些生物計(jì)算，這將會(huì)轉(zhuǎn)變我們對(duì)細(xì)胞的行為方式和行為原因的理解能力。因?yàn)?，如果我們了解那些程序，?dāng)出現(xiàn)問題時(shí)，我們可以為它們排錯(cuò)?；蛭覀兛梢韵蛩鼈儗W(xué)習(xí)如何設(shè)計(jì)這樣 能充分利用生物化學(xué) 計(jì)算能力的合成電路。

04:34

My passion about this idea led me to acareer in research at the interface of maths, computer science and biology. Andin my work, I focus on the concept of biology as computation. And that meansasking what do cells compute, and how can we uncover these biological programs?And I started to ask these questions together with some brilliant collaboratorsat Microsoft Research and the University of Cambridge, where together we wantedto understand the biological program running inside a unique type of cell: anembryonic stem cell. These cells are unique because they're totally naïve. Theycan become anything they want: a brain cell, a heart cell, a bone cell, a lungcell, any adult cell type. This naïvety, it sets them apart, but it alsoignited the imagination of the scientific community, who realized, if we couldtap into that potential, we would have a powerful tool for medicine. If wecould figure out how these cells make the decision to become one cell type oranother, we might be able to harness them to generate cells that we need torepair diseased or damaged tissue. But realizing that vision is not without itschallenges, not least because these particular cells, they emerge just six daysafter conception. And then within a day or so, they're gone. They have set offdown the different paths that form all the structures and organs of your adultbody.

我對(duì)這個(gè)想法的熱情，讓我進(jìn)入了數(shù)學(xué)、計(jì)算機(jī)科學(xué)和生物學(xué)的交叉領(lǐng)域。工作中，我專注于一個(gè)概念：生物學(xué)計(jì)算。這代表著不斷詢問細(xì)胞在計(jì)算什么，以及我們?nèi)绾文芙忾_這些生物程序的奧秘？我開始和微軟研究院與劍橋大學(xué)的一些出色的合作人士一起詢問這些問題，我們想要了解在一種獨(dú)特細(xì)胞中運(yùn)行的生物程序：胚胎干細(xì)胞（ ES 細(xì)胞）。這些細(xì)胞很獨(dú)特，因?yàn)樗鼈兎浅Ｖ赡郏次锤叨确只Ｋ鼈兡軌蚍只癁樗鼈兿胍兂傻臇|西：一個(gè)腦細(xì)胞，一個(gè)心臟細(xì)胞，一個(gè)骨細(xì)胞，一個(gè)肺細(xì)胞，任何一種成熟細(xì)胞。這一稚嫩狀態(tài)讓這些細(xì)胞變得與眾不同，但也激發(fā)了科學(xué)界的想象力?？茖W(xué)家們意識(shí)到，如果我們能挖掘這一特性的潛力，我們將會(huì)擁有一個(gè)強(qiáng)大的醫(yī)療工具。如果我們能搞清這些細(xì)胞是如何決定自己要發(fā)育為何種細(xì)胞的，我們或許能夠利用 ES 細(xì)胞的這一能力，生成我們需要的細(xì)胞，來修復(fù)攜帶疾病的或受損的組織。但這一愿景的實(shí)現(xiàn)存在著挑戰(zhàn)，不僅是因?yàn)檫@些特定細(xì)胞在受孕的 6 天后才出現(xiàn)，之后大約在 1 天內(nèi)，就會(huì)消失。它們走上了不同的道路，共同形成成年人體的所有結(jié)構(gòu)和器官。

05:59

But it turns out that cell fates are a lotmore plastic than we might have imagined. About 13 years ago, some scientistsshowed something truly revolutionary. By inserting just a handful of genes intoan adult cell, like one of your skin cells, you can transform that cell back tothe naïve state. And it's a process that's actually known as"reprogramming," and it allows us to imagine a kind of stem cellutopia, the ability to take a sample of a patient's own cells, transform themback to the naïve state and use those cells to make whatever that patient mightneed, whether it's brain cells or heart cells.

但事實(shí)證明，細(xì)胞的命運(yùn)比我們所想象的更具有可塑性。大概在 13 年前，一些科學(xué)家們展示了一些極具革命性的東西：通過把少量基因?qū)氤墒旒?xì)胞，例如你的一個(gè)皮膚細(xì)胞，你可以把這個(gè)成熟細(xì)胞轉(zhuǎn)化回未分化狀態(tài)。這一過程被稱為“重編程”。這讓我們聯(lián)想到“干細(xì)胞烏托邦”，這種能力可以采集患者自身的細(xì)胞樣本，將其轉(zhuǎn)化回未分化的原始形態(tài)，并使用那些細(xì)胞制造患者可能需要的細(xì)胞，不論是腦細(xì)胞，還是心臟細(xì)胞。

06:38

But over the last decade or so, figuringout how to change cell fate, it's still a process of trial and error. Even incases where we've uncovered successful experimental protocols, they're stillinefficient, and we lack a fundamental understanding of how and why they work.If you figured out how to change a stem cell into a heart cell, that hasn't gotany way of telling you how to change a stem cell into a brain cell. So we wantedto understand the biological program running inside an embryonic stem cell, andunderstanding the computation performed by a living system starts with asking adevastatingly simple question: What is it that system actually has to do?

但在過去的 10 年，搞清楚如何改變細(xì)胞命運(yùn)仍然是一個(gè)試錯(cuò)的過程。即使是在那些我們已經(jīng)發(fā)現(xiàn)了成功實(shí)驗(yàn)方法的情況下，它們?nèi)耘f低效，而且我們?nèi)鄙訇P(guān)于它們?nèi)绾我约盀楹芜\(yùn)作的基本理解。如果你能摸清如何把一個(gè)干細(xì)胞誘導(dǎo)為一個(gè)心臟細(xì)胞，你依然不知道如何把一個(gè)干細(xì)胞誘導(dǎo)為一個(gè)腦細(xì)胞。所以我們想要了解在 ES 細(xì)胞中運(yùn)行的生物程序，而且，了解該生物系統(tǒng)中所運(yùn)行的計(jì)算 始于提出一個(gè)極為簡(jiǎn)單的問題： 這個(gè)系統(tǒng)到底需要做什么？

07:21

Now, computer science actually has a set ofstrategies for dealing with what it is the software and hardware are meant todo. When you write a program, you code a piece of software, you want thatsoftware to run correctly. You want performance, functionality. You want toprevent bugs. They can cost you a lot. So when a developer writes a program,they could write down a set of specifications. These are what your programshould do. Maybe it should compare the size of two numbers or order numbers byincreasing size. Technology exists that allows us automatically to checkwhether our specifications are satisfied, whether that program does what itshould do. And so our idea was that in the same way, experimental observations,things we measure in the lab, they correspond to specifications of what thebiological program should do.

計(jì)算機(jī)科學(xué)實(shí)際上已有一套策略來執(zhí)行軟件和硬件的功能。當(dāng)你編寫程序時(shí)，你用代碼編寫了一個(gè)軟件，你希望這個(gè)軟件能夠正確運(yùn)行，你希望它具備完善的功能與性能，能防止錯(cuò)誤，做到這些的成本很高。所以當(dāng)一個(gè)開發(fā)者編寫程序時(shí)，他們能編寫出一套技術(shù)規(guī)范。這些是你的程序應(yīng)該做的“工作”。或許它能比較兩個(gè)數(shù)的大小，或?qū)?shù)字進(jìn)行正序排序。這樣的技術(shù)存在：允許我們自動(dòng)檢查我們的代碼是否符合技術(shù)規(guī)范，程序是否在完成它的本職工作。于是我們的想法很類似，實(shí)驗(yàn)觀察值，也就是我們?cè)趯?shí)驗(yàn)室中測(cè)量的東西，符合生物編程本職工作中怎樣的技術(shù)規(guī)范？

08:10

So we just needed to figure out a way toencode this new type of specification. So let's say you've been busy in the laband you've been measuring your genes and you've found that if Gene A is active,then Gene B or Gene C seems to be active. We can write that observation down asa mathematical expression if we can use the language of logic: If A, then B orC. Now, this is a very simple example, OK. It's just to illustrate the point.We can encode truly rich expressions that actually capture the behavior ofmultiple genes or proteins over time across multiple different experiments. Andso by translating our observations into mathematical expression in this way, itbecomes possible to test whether or not those observations can emerge from aprogram of genetic interactions.

所以我們只需要找到一個(gè)方法來編譯這個(gè)新型的技術(shù)規(guī)范。比方說，你在實(shí)驗(yàn)室忙活了很久，你一直在測(cè)量基因，發(fā)現(xiàn)如果基因 A 是活躍的，那么基因 B 或 C 也會(huì)看似活躍。如果我們能用一種邏輯語(yǔ)言，就可以將這種觀察編寫為一種數(shù)學(xué)表達(dá)：如果 A ，那么 B 或 C 。這是一個(gè)非常簡(jiǎn)單的例子，只是為了解釋清楚我的意思。我們可以編譯很多豐富的表達(dá)，在多個(gè)不同的實(shí)驗(yàn)中，隨著時(shí)間的推移，這些表達(dá)可以捕捉多種基因或蛋白質(zhì)的行為。運(yùn)用這種方法，把我們的觀察值編譯為一種數(shù)學(xué)表達(dá)，現(xiàn)在有可能測(cè)試這些觀察結(jié)果是否可以從基因相互作用的程序中得到。

09:04

And we developed a tool to do just this. Wewere able to use this tool to encode observations as mathematical expressions,and then that tool would allow us to uncover the genetic program that couldexplain them all. And we then apply this approach to uncover the geneticprogram running inside embryonic stem cells to see if we could understand howto induce that naïve state. And this tool was actually built on a solver that'sdeployed routinely around the world for conventional software verification. Sowe started with a set of nearly 50 different specifications that we generatedfrom experimental observations of embryonic stem cells. And by encoding theseobservations in this tool, we were able to uncover the first molecular programthat could explain all of them.

我們開發(fā)了一個(gè)工具來實(shí)現(xiàn)這個(gè)目的。我們能用這個(gè)工具將觀察值編譯為 數(shù)學(xué)表達(dá)。該工具能讓我們發(fā)現(xiàn)可以解釋 所有原因的遺傳程序。之后，我們運(yùn)用這個(gè)方法 來揭示 ES 細(xì)胞中運(yùn)行的遺傳程序，來看看我們是否能理解 如何誘導(dǎo)未分化狀態(tài)的細(xì)胞。這個(gè)工具實(shí)際上是建立在 經(jīng)常被部署在世界各地 用于傳統(tǒng)的軟件驗(yàn)證 的解算器上的。我們從一套將近有 50 個(gè)不同的技術(shù)規(guī)范開始，這些是我們從對(duì) ES 細(xì)胞的實(shí)驗(yàn)觀察值中得出的。利用這個(gè)工具，通過編譯這些觀察值，我們能夠揭開第一個(gè)能夠解釋所有分子的程序。

09:52

Now, that's kind of a feat in and ofitself, right? Being able to reconcile all of these different observations isnot the kind of thing you can do on the back of an envelope, even if you have areally big envelope. Because we've got this kind of understanding, we could goone step further. We could use this program to predict what this cell might doin conditions we hadn't yet tested. We could probe the program in silico.

這本身聽著是一種壯舉，是吧？將所有的觀察值協(xié)調(diào)到一起，不是那種你可以在信封背面做的事情，即使你有一個(gè)很大的信封。因?yàn)槲覀冇兄@樣的理解，我們能夠再進(jìn)一步。我們能夠用這個(gè)程序在尚未測(cè)試的條件下，來預(yù)測(cè)這個(gè)細(xì)胞可能會(huì)做什么。我們能夠在硅上探索該程序。

10:16

And so we did just that: we generatedpredictions that we tested in the lab, and we found that this program washighly predictive. It told us how we could accelerate progress back to thenaïve state quickly and efficiently. It told us which genes to target to dothat, which genes might even hinder that process. We even found the programpredicted the order in which genes would switch on. So this approach reallyallowed us to uncover the dynamics of what the cells are doing.

所以我們行動(dòng)了起來：我們依據(jù)實(shí)驗(yàn)室檢測(cè)值生成了預(yù)測(cè)，并發(fā)現(xiàn)該程序非常具有可預(yù)測(cè)性。它告訴我們?nèi)绾文軌蚣铀偌?xì)胞返回未分化狀態(tài)的過程，使之快速且有效。它告訴我們可以針對(duì)哪些基因進(jìn)行操作，又有哪些基因會(huì)阻礙這一過程。我們甚至發(fā)現(xiàn)了一個(gè)能夠預(yù)測(cè)基因開啟順序的程序。這個(gè)方法讓我們得以揭秘細(xì)胞行為的動(dòng)態(tài)。

10:47

What we've developed, it's not a methodthat's specific to stem cell biology. Rather, it allows us to make sense of thecomputation being carried out by the cell in the context of geneticinteractions. So really, it's just one building block. The field urgently needsto develop new approaches to understand biological computation more broadly andat different levels, from DNA right through to the flow of information betweencells. Only this kind of transformative understanding will enable us to harnessbiology in ways that are predictable and reliable.

我們開發(fā)的不只是一種僅限于干細(xì)胞生物的方法。相反，這能幫助我們理解在遺傳相互作用的環(huán)境下細(xì)胞內(nèi)在的計(jì)算程序。所以這其實(shí)只是拼圖中的一塊。該領(lǐng)域急需開發(fā)新方法來更廣泛地在不同層次上了解生物計(jì)算，從 DNA 到細(xì)胞間的信息流。只有這樣的變革性理解才能夠使我們以可預(yù)測(cè)和可靠的方式利用生物學(xué)。

11:21

But to program biology, we will also needto develop the kinds of tools and languages that allow both experimentalistsand computational scientists to design biological function and have thosedesigns compile down to the machine code of the cell, its biochemistry, so thatwe could then build those structures. Now, that's something akin to a livingsoftware compiler, and I'm proud to be part of a team at Microsoft that'sworking to develop one. Though to say it's a grand challenge is kind of anunderstatement, but if it's realized, it would be the final bridge betweensoftware and wetware.

但是對(duì)于編程生物學(xué)，我們也將需要開發(fā)允許實(shí)驗(yàn)人員和計(jì)算科學(xué)家使用的工具和語(yǔ)言來設(shè)計(jì)生物函數(shù)，并將這些設(shè)計(jì)編譯成細(xì)胞的機(jī)器代碼，也就是它的生物化學(xué)，這樣我們就可以構(gòu)建這些結(jié)構(gòu)。這就類似于一個(gè)活的生物軟件編譯器，我非常自豪能成為微軟開發(fā)此類軟件團(tuán)隊(duì)的一員。盡管，說這是一個(gè)很大的挑戰(zhàn)有點(diǎn)輕描淡寫，但如果能實(shí)現(xiàn)，這將會(huì)成為軟件和濕件最后的橋梁。

11:57

More broadly, though, programming biologyis only going to be possible if we can transform the field into being trulyinterdisciplinary. It needs us to bridge the physical and the life sciences,and scientists from each of these disciplines need to be able to work togetherwith common languages and to have shared scientific questions.

但更廣泛地說，如果我們能夠?qū)⑵滢D(zhuǎn)變?yōu)檎嬲目鐚W(xué)科領(lǐng)域，編程生物學(xué)才會(huì)變成可能。這需要我們搭建起物理與生命科學(xué)的橋梁，來自相關(guān)學(xué)術(shù)背景的科學(xué)家們需要能夠利用共同語(yǔ)言進(jìn)行合作，并分享共同的科學(xué)問題。

12:16

In the long term, it's worth rememberingthat many of the giant software companies and the technology that you and Iwork with every day could hardly have been imagined at the time we firststarted programming on silicon microchips. And if we start now to think aboutthe potential for technology enabled by computational biology, we'll see someof the steps that we need to take along the way to make that a reality. Now,there is the sobering thought that this kind of technology could be open tomisuse. If we're willing to talk about the potential for programming immunecells, we should also be thinking about the potential of bacteria engineered toevade them. There might be people willing to do that. Now, one reassuringthought in this is that -- well, less so for the scientists -- is that biologyis a fragile thing to work with. So programming biology is not going to besomething you'll be doing in your garden shed. But because we're at the outsetof this, we can move forward with our eyes wide open. We can ask the difficultquestions up front, we can put in place the necessary safeguards and, as partof that, we'll have to think about our ethics. We'll have to think aboutputting bounds on the implementation of biological function. So as part ofthis, research in bioethics will have to be a priority. It can't be relegatedto second place in the excitement of scientific innovation.

長(zhǎng)遠(yuǎn)來看，值得記住的是：當(dāng)我們第一次開始在硅微芯片上編程時(shí)，幾乎無法想象有一天會(huì)出現(xiàn)我們?nèi)缃衩刻於夹枰蚪坏赖哪切┐笮蛙浖竞图夹g(shù)。如果我們現(xiàn)在開始思考由計(jì)算生物學(xué)支持的科技潛能，我們將會(huì)看到為實(shí)現(xiàn)這一目標(biāo)一路上需要做出的努力。如今存在一種令人警醒的想法：這種科技可能會(huì)被濫用。如果我們?cè)敢馓接懢幊堂庖呒?xì)胞的潛力，我們也應(yīng)該考慮到改造后的細(xì)菌成功躲避那些免疫細(xì)胞的可能。可能有些人打算從事這方面的研究。關(guān)于這個(gè)話題也存在一個(gè)令人欣慰的想法——科學(xué)家大概不這么認(rèn)為——生物太脆弱，在工作中難以把控。所以編程生物學(xué)不會(huì)進(jìn)入你的生活。但因?yàn)槲覀儾艅偲鸩剑晕覀兛梢源竽懬抑?jǐn)慎的往前走。我們可以事先提出難題，我們可以采取必要的保護(hù)措施，同時(shí)，作為其中的一部分，還需要思考我們的道德標(biāo)準(zhǔn)，我們將需要思考那些生物函數(shù)實(shí)行的界限。所以其中的生物倫理學(xué)研究將被優(yōu)先考慮。在令人激動(dòng)的科學(xué)創(chuàng)新中，這個(gè)話題不能屈居第二。

13:35

But the ultimate prize, the ultimatedestination on this journey, would be breakthrough applications andbreakthrough industries in areas from agriculture and medicine to energy andmaterials and even computing itself. Imagine, one day we could be powering theplanet sustainably on the ultimate green energy if we could mimic somethingthat plants figured out millennia ago: how to harness the sun's energy with anefficiency that is unparalleled by our current solar cells. If we understoodthat program of quantum interactions that allow plants to absorb sunlight soefficiently, we might be able to translate that into building synthetic DNAcircuits that offer the material for better solar cells. There are teams andscientists working on the fundamentals of this right now, so perhaps if it gotthe right attention and the right investment, it could be realized in 10 or 15years.

但我們這場(chǎng)旅行的最終目的地將會(huì)是突破性的應(yīng)用以及突破性行業(yè)，從農(nóng)業(yè)，醫(yī)療，到能源和材料，甚至計(jì)算機(jī)技術(shù)本身。試想，有一天，我們能使用終極綠色能源為地球提供可持續(xù)的動(dòng)力，因?yàn)槲覀円呀?jīng)能夠模仿植物在千年前發(fā)現(xiàn)的東西：如何利用我們現(xiàn)有太陽(yáng)能電池?zé)o法比擬的效率來利用太陽(yáng)能。如果我們能理解讓植物高效吸收太陽(yáng)光的量子相互作用的程序，我們或許能將其編譯為能夠?yàn)樘?yáng)能電池提供更好材料的合成 DNA 電路。現(xiàn)在有一些團(tuán)隊(duì)和科學(xué)家正著手于解決這個(gè)課題的基本問題，如果這個(gè)課題能獲得足夠的關(guān)注和正確的投資，在未來的 10 或 15 年內(nèi)，或許就有可能實(shí)現(xiàn)。

14:27

So we are at the beginning of atechnological revolution. Understanding this ancient type of biologicalcomputation is the critical first step. And if we can realize this, we wouldenter in the era of an operating system that runs living software.

我們正處在科技革新的開端。了解這種古老的生物計(jì)算類型是關(guān)鍵的第一步。如果我們能意識(shí)到這件事，就將進(jìn)入一個(gè)擁有能夠運(yùn)行生物軟件的操作系統(tǒng)的時(shí)代。

14:42

Thank you very much.

非常感謝。

14:43

(Applause)

（掌聲）