From Newton to Hawking, scientists love wagers. Now Lewis Wolpert has bet Rupert Sheldrake a case of fine port that: "By 1 May 2029, given the genome of a fertilised egg of an animal or plant, we will be able to predict in at least one case all the details of the organism that develops from it, including any abnormalities." If the outcome isn't obvious, then the Royal Society will be asked to adjudicate.

    Lewis Wolpert

    I HAVE entered into this wager with Rupert Sheldrake because of my interest in the details of how embryos develop, and how our understanding of this process will progress. In my latest book, How We Live and Why We Die, I suggest that it will one day be possible to predict from an embryo's genome how it will develop, and I believe it is possible for this to happen in the next 20 years.

    I am, in fact, being a little over-keen because 40 years is a more likely time frame for such a breakthrough. Cells and embryos are extremely complicated: for their size, embryonic cells are the most complex structures in the universe.

    Animals develop from a single cell, a fertilised egg, which divides to produce cells that will form the embryo. How that egg develops into an embryo and newborn animal is controlled by genes in the chromosomes. These genes are passive: they do nothing, just provide the code for proteins. It is proteins that determine how cells behave. While the DNA in every cell contains the code for all the proteins in all the cells, it is the particular proteins produced in particular cells that determine how those cells behave.

    Every cell of the embryo contains many copies of several thousand different proteins. These proteins have a plethora of functions: acting as enzymes to break down and build other molecules, providing structures for the cell, interacting with each other, and many more. The complexity of the interactions between millions of molecules is amazing.

    As the proteins determine how the cells behave, it is their activity that causes the embryo to develop. Underlying this process, though, are the genes, as they control which proteins are made - including some proteins that activate specific genes. It is essential that there is this control over which cells continue to divide, and of mechanisms to pattern the embryo so that different cells develop into different structures, such as the brain or limbs.

    There is a huge incentive to understand these processes and so be able to work out the development of an embryo given only its genome. This ability could pave the way for regenerative medicine by allowing scientists to program stem cells to become structures that could replace damaged parts of the body.

    To win the bet, we will have to be able to predict the behaviour of almost all the cells in the embryo. In a small worm, say the nematode Caenorhabditis elegans, there are 959 cells, making it the ideal model to solve this problem. It is a major challenge, but advances in cell biology, systems biology and computing will take us there.

    Rupert Sheldrake

    LEWIS WOLPERT's faith in the predictive power of the genome is misplaced. Genes enable organisms to make proteins, but do not contain programs or blueprints, or explain the development of embryos.

    The problems begin with proteins. Genes code for the linear sequences of amino acids in proteins, which then fold up into complex three-dimensional forms. Wolpert's wager presupposes that the folding of proteins can be computed from first principles, given the sequence of amino acids specified by the genes. So far, this has proved impossible. As in all bottom-up calculations, there is a combinatorial explosion. For example, by random folding, the amino-acid chain of the enzyme ribonuclease, a small protein, could adopt more than 1040 different shapes, which would take billions of years to explore. In fact, it folds into its habitual form in 2 minutes.

    Even if we could solve protein-folding, the next stage would be to predict the structure of cells on the basis of the interactions of millions of proteins and other molecules. This would unleash a far worse combinatorial explosion, with more possible arrangements than all the atoms in the universe.

    Random molecular permutations simply cannot explain how organisms work. Instead, cells, tissues and organs develop in a modular manner, shaped by morphogenetic fields, first recognised by developmental biologists in the 1920s. Wolpert himself acknowledges the importance of such fields. Among biologists, he is best known for "positional information", by which cells "know" where they are within the field of a developing organ, such as a limb. But he believes morphogenetic fields can be reduced to standard chemistry and physics. I disagree. I believe these fields have organizing abilities, or systems properties, that involve new scientific principles.

    The Human Genome Project has itself set back the hopes it engendered. First, our genome contains only between 20,000 and 25,000 genes, far fewer than the 100,000 expected. In contrast, sea urchins have about 26,000, and rice plants 38,000. Moreover, our genome differs very little from the chimpanzee's genome, the sequencing of which was completed in 2005. As Svante P??bo, director of the Chimpanzee Genome Project, commented: "We cannot see in this why we are so different from chimpanzees."

    Second, in practice, the predictive value of human genomes turns out to be low. Everyone knows tall parents tend to have tall children, and recent studies on the genomes of 30,000 people identified about 50 genes associated with being tall or short. Yet together these genes accounted for only about 5 per cent of the inheritance of height. This is not the only example of "missing heritability". Steve Jones, professor of genetics at University College London says that "hubris has been replaced with concern", and he suggests the present approach is "throwing good money after bad".

    Wolpert is not alone in believing in the predictive value of the genome. Governments, venture capitalists and medical charities have bet and are still betting billions of dollars on it. More than a case of fine port is at stake.

    A brief history of wagers

    Scientific wagers date back to Greece in the 5th or 6th century BC and were often a rhetorical device for thinking about a subject. In their current form, they can also help stimulate fresh thinking.

    One of the famous wagers of the more modern era was announced by Christopher Wren in 1684. He would give a book worth 40 shillings to anyone who could deduce Kepler's laws from the inverse-square law. Isaac Newton took this seriously and his deliberations eventually became his Principia - but too late to claim the prize.

    In 1959, physicist Richard Feynman bet $1000 that it was impossible to build a motor no bigger than 1/64 of an inch on each side. He lost: electrical engineer Bill McLellan succeeded. Feynman was said to be disappointed because he hoped his bet would stimulate new technology, but McLellan's motor used existing techniques.

    從牛頓到霍金，科學(xué)家們都愛打賭。如今Lewis Wolpert跟Rupert Sheldrake打賭說："到2029年5月1日，只需一顆受精卵，無論動物還是植物，我們就能預(yù)測出至少在一種情況下這顆受精卵成長過程的全部細(xì)節(jié)，包括所有異常情況。"如果結(jié)果并不明顯，Lewis Wolpert就會接受英國皇家學(xué)會的審判。

    Lewis Wolpert的獨白：

    之所以跟Rupert Sheldrake打賭是因為我對胚胎成長的過程很感興趣，并且希望能對其有更深入的了解。在我最近出版的《How We Live and Why We Die》中，我認(rèn)為總有一天人們能從胚胎的基因中預(yù)測出它成長的過程，我也相信這一設(shè)想會在未來的20年內(nèi)實現(xiàn)。

    實際上，我可能過于心急了，40年時間對實現(xiàn)這一突破似乎更有可能。因為細(xì)胞和胚胎結(jié)構(gòu)極其復(fù)雜：單從尺寸上來講，胚胎干細(xì)胞是宇宙中最復(fù)雜的結(jié)構(gòu)。

    動物們從一顆受精卵衍化而來，受精卵產(chǎn)生組成胚胎的細(xì)胞。染色體中的基因控制著卵子變成胚胎和新生動物的過程。但是這些基因十分懶惰：它們什么也不做，只為蛋白質(zhì)提供編碼。因此是蛋白質(zhì)決定了細(xì)胞的行為。而細(xì)胞中的DNA包含所有細(xì)胞蛋白質(zhì)的編碼，只有個別細(xì)胞產(chǎn)生的特殊蛋白質(zhì)才決定細(xì)胞行為。

    胚胎中的每一個細(xì)胞都包含上千種不同蛋白質(zhì)的復(fù)制品。這些蛋白質(zhì)功能過剩：它們會像酶一樣分解物質(zhì)，或形成其它分子，或為細(xì)胞賦予結(jié)構(gòu)，有些還會與其它蛋白質(zhì)進(jìn)行互動等等。數(shù)百萬蛋白質(zhì)分子同時進(jìn)行活動的復(fù)雜狀態(tài)令人吃驚。

    蛋白質(zhì)決定細(xì)胞行為，蛋白質(zhì)的活動促使胚胎發(fā)展。但是這一過程的始作俑者是基因，包括某些需要蛋白質(zhì)激活的基因，因為它們控制蛋白質(zhì)的形成�；�因的控制必不可少，只有它們決定哪些細(xì)胞繼續(xù)，這樣不同的細(xì)胞才會成長為不同的結(jié)構(gòu)，如大腦和四肢。

    只有了解基因，才能從一顆受精卵中判斷胚胎的發(fā)展。科學(xué)家們還可以將研究結(jié)果應(yīng)用到再生醫(yī)學(xué)上去，用干細(xì)胞培育器官來替換身體內(nèi)的壞死部分。

    要想贏得這場戰(zhàn)斗的勝利，我們必須能夠預(yù)測胚胎中所有細(xì)胞的行為。以某種小型土壤線蟲為例，它有959個細(xì)胞，是解決這一問題的理想模型。很顯然，這是一項巨大的挑戰(zhàn)，但是細(xì)胞生物學(xué)，系統(tǒng)生物學(xué)和計算機技術(shù)的發(fā)展會幫助我們將夢想變成現(xiàn)實。

    Rupert Sheldrake的獨白：

    Lewis Wolpert竟然寄希望于基因真是異想天開�；�因促使組織制造蛋白質(zhì)這的確沒錯，但是它們既沒有計劃，也不能解釋胚胎們的發(fā)展。

    一切問題的根源在于蛋白質(zhì)�；�因控制蛋白質(zhì)中線性氨基酸類的編碼，這些氨基酸再折疊形成復(fù)雜的立體結(jié)構(gòu)。Wolpert認(rèn)為只需特定基因的氨基酸就能判斷蛋白質(zhì)折疊的結(jié)果。迄今為止，這是根本不可能的。因為蛋白質(zhì)折疊的可能性數(shù)不勝數(shù)。例如，通過隨機折疊，核糖核酸酶（一種小型蛋白質(zhì)）的氨基酸鏈能形成超過1040種不同的結(jié)構(gòu)，單這一種蛋白質(zhì)就需要數(shù)億年的時間來探索。而實際上，氨基酸鏈折疊的過程只需兩分鐘。

    即使我們能抓住蛋白質(zhì)折疊的規(guī)律，下一步就是通過分析數(shù)百萬蛋白質(zhì)和其它分子之間的相互作用，來預(yù)測細(xì)胞的結(jié)構(gòu)。這勢必會引發(fā)另一次更大規(guī)模的信息爆炸，因為這一過程產(chǎn)生的可能性比宇宙中所有的原子數(shù)量還要多。

    僅憑分析隨機分子排列的規(guī)律不可能解釋器官的形成。相反，早在20世紀(jì)20年代發(fā)育學(xué)家們就認(rèn)識到細(xì)胞，組織和器官是按照特定的模式而生長，這種模式是由形態(tài)發(fā)生場所而決定的。Wolpert知道這些場所的重要性。在生物學(xué)家之中，他以知曉"位置信息"而聞名，位置信息就是細(xì)胞"知道"其在生長器官中的位置，比如四肢。但是他認(rèn)為形態(tài)發(fā)生場所會被周圍的化學(xué)或物理作用而削弱。這一點我不認(rèn)同。我相信形態(tài)發(fā)生場所具有組織能力或者系統(tǒng)功能，對其的研究將會發(fā)現(xiàn)新的科學(xué)原理。

    人類基因組計劃就證明了這一預(yù)測很不現(xiàn)實。首先，我們的基因組只包含2萬至2萬5千個基因，與預(yù)期的10萬相去甚遠(yuǎn)。相比較，海膽有2萬6千個基因，而谷類植物的基因有3萬8千個。此外，據(jù)2005年的研究顯示人類與黑猩猩基因差別很小。黑猩猩基因組計劃的負(fù)責(zé)人Svante P??bo曾說過："我們不能從黑猩猩的基因組中判斷出為什么我們與黑猩猩不一樣。"

    其次，實際上，人類基因組的預(yù)測價值很低。每個人都知道高個家長容易有高個孩子，而最近對3萬人的基因組進(jìn)行鑒定后發(fā)現(xiàn)只有50個基因與人的高矮有關(guān)。這些基因加在一起只對身高遺傳起到5%的作用。這并不是"失傳現(xiàn)象"的唯一例證。倫敦大學(xué)學(xué)院的遺傳學(xué)教授Steve Jones說過："驕傲已蒙蔽了憂慮的雙眼。"他認(rèn)為目前的研究方向是"賠了夫人又折兵".

    Wolpert并不是唯一一個堅信人類基因組預(yù)測價值的人。政府部門，資本家們以及慈善機構(gòu)都在上面下注，一擲千金。這樣做的結(jié)果很危險。

    科學(xué)家打賭簡史

    科學(xué)家打賭的歷史可以追溯到公元前5、6世紀(jì)的希臘，那時打賭是一種用來刺激人們思考的手段。就現(xiàn)在來看，打賭仍舊可以激發(fā)人們的靈感。

    現(xiàn)代最著名的打賭發(fā)生在1684年。Christopher Wren打賭如果有人能用平方反比定律推論開普勒定律，他就會將一本價值40先令的書送給這個人。Isaac Newton經(jīng)過深思熟慮最終形成了他的著名理論，但對于領(lǐng)取獎賞為時已晚。

    1959年，物理學(xué)家Richard Feynman打賭1000美元，預(yù)言不可能有人制造出邊長不超過六十四分之一英尺的馬達(dá)。最終電機工程師Bill McLellan抱得美元歸。Feynman稱這一結(jié)果令他很失望，他本希望這次能刺激人們進(jìn)行技術(shù)創(chuàng)新，但是McLellan制造的馬達(dá)仍使用現(xiàn)有技術(shù)。

    1975年，Stephen Hawking與同伴宇宙學(xué)家Kip Thorne曾打賭天鵝座X-1是否含有黑洞，賭注是輸家為贏家訂閱雜志。結(jié)果Hawking認(rèn)輸，也恰好從這時起Hawking開始花費大量時間研究黑洞。