To find a specific sequence like that is not just less likely than winning the jackpot in the lottery, it is less likely than winning a jackpot every year since the Big Bang. (Location 96)
A tiny fraction of small and random heritable changes confers a reproductive advantage to the organisms that win this genetic lottery and, accumulating over time, such changes explain the falcon’s eye—and, by extension, everything from the falcon itself to all of life’s diversity. (Location 104)
Natural selection can preserve innovations, but it cannot create them. (Location 107)
Natural selection can preserve innovations, but it cannot create them. (Location 107)
Nature’s many innovations—some uncannily perfect—call for natural principles that accelerate life’s ability to innovate, its innovability. (Location 108)
Nature’s many innovations—some uncannily perfect—call for natural principles that accelerate life’s ability to innovate, its innovability. (Location 108)
Using experimental and computational technologies unimagined by Darwin or Rutherford, our goal is not to discover individual innovations, but to find the wellsprings of all biological innovation. (Location 111)
Darwin’s theory surely is the most important intellectual achievement of his time, perhaps of all time. (Location 128)
Darwin’s theory surely is the most important intellectual achievement of his time, perhaps of all time. (Location 128)
Germs of thought about an evolving natural world existed long before Darwin. (Location 131)
To a Platonist, basketballs, tennis balls, and Ping-Pong balls share an essence, their ball-like shape. It is this essence—perfect, geometric, abstract—that is real, not the physical balls, which are as fleeting and changeable as shadows. (Location 158)
Small islands have fewer species, opposite shores of the same continent harbor very different faunas, Europe and South America host completely different mammals.13 (Location 178)
wove them into the beautiful fabric of his theory. (Location 182)
The second one was the central role of natural selection, an insight inspired by the spectacular success of animal and plant breeders. (Location 183)
Darwin realized that natural selection is not so different from such human selection, except that it operates on a much grander scale, and over eons of time. Nature incessantly creates new variants of organisms, (Location 188)
Nature incessantly creates new variants of organisms, most inferior, a few of them superior, and all of these variants must pass through the sieve of natural selection. (Location 189)
The next step on biology’s path—explaining inheritance—was already made by the time Darwin died, but he did not know it. (Location 200)
What he saw was that these features often do not blend in the offspring. (Location 208)
How do mutations cause changes in phenotypes and bring forth innovations? (Location 238)
natural selection is not a creative force. It does not innovate, but merely selects what is already there. Darwin realized that natural selection allows innovations to spread, but he did not know where they came from in the first place. (Location 245)
Selection did not—cannot—create all this variation. (Location 255)
Hugo de Vries expressed it best when he said that “natural selection may explain the survival of the fittest, but it cannot explain the arrival of the fittest” (emphasis added). (Location 255)
“natural selection may explain the survival of the fittest, but it cannot explain the arrival of the fittest” (emphasis added). (Location 256)
Life can innovate, it has innovability. What is more, it can innovate while preserving what works through faithful inheritance. It can explore the new while preserving the old. (Location 258)
The real mystery of evolution is not selection, but the creation of new phenotypes. (Location 288)
That process began when a long-known fact became newly appreciated: Genetic change happens not just in individuals, but in populations. (Location 290)
If natural selection mattered, we would expect that the black moths would become more frequent over time. (Location 297)
Can we predict how rapidly they sweep through the population? Or conversely, if we have observed how fast they sweep, can we infer how strongly the dark color affects fitness, a moth’s chances of remaining hidden from birds? These were quantitative, mathematical questions, new to evolutionary thinking. And they created a new quantitative discipline within biology: population genetics. (Location 300)
One of the central insights of population genetics is to view a population not just as a collection of distinct organisms but as a collective pool of genes. (Location 303)
is to view a population not just as a collection of distinct organisms but as a collective pool of genes. (Location 304)
Their advantage need not be huge, but even a merely 1 percent increase in the dark-winged allele, from 50 percent to 51 percent in the first generation, could accumulate over time and allow the dark-winged variants to occupy a larger and larger percentage of the population. (Location 308)
At the same time, naturalists studied the frequencies of alleles in wild populations such as that of the peppered moth, and experimentalists created evolution in action in the laboratory, by studying laboratory populations of small, rapidly breeding animals such as fruit flies. (Location 314)
By the 1930s, the concept of natural selection, the nature of inheritance, and population thinking had been synthesized into a body of knowledge known as the modern synthesis, named after an eponymous book by the biologist Julian Huxley. (Location 326)
The architects of the modern synthesis focused on the genotype at the expense of the organism and its phenotype. (Location 333)
The modern synthesis could explain how innovations spread, but not how they originate. (Location 349)
Where the modern synthesis has a theory without phenotypes, the embryologists have phenotypes without a theory. Evo-devo, however, has taught us an (Location 364)
Proteins fold into intricate three-dimensional shapes that wobble and vibrate. (Location 413)
And to this day we are unable to predict either one from the underlying amino acid string, so complex and subtle are the rules underlying this folding. (Location 414)
If we cannot predict their shape, it is impossible to travel the road from the genotype all the way to the phenotype. But that road is where nature innovates. (Location 422)
They cooperate like worker bees in solving a complex task. (Location 424)
When molecular evolutionists took advantage of this technology, they discovered something nobody had expected: enormous amounts of genetic variation, everywhere, even in organisms that had not changed for many millennia. (Location 440)
because mutations tend to sprinkle genes randomly with letter changes. Something had happened to these mutations. (Location 452)
Animal and plant populations are chock-full of genetic variation. (Location 464)
Do most of them matter for phenotypic evolution? Are they necessary or irrelevant for life’s innovations? Their mere existence underlines how hard it is to understand phenotypic innovation and how it emerges from genetic change. (Location 467)
The relationship between genotype and phenotype is complex beyond imagination. (Location 490)
This centrality of computing is new, because for much of its history, biology was limited by data. (Location 521)
Because life is built of molecules, we need to understand molecules to understand innovation: not only the genotype embodied in DNA, but how this genotype helps build a phenotype. (Location 536)
He had no inkling of life’s true complexity (and many after him thought they could safely neglect it). But to crack the secret of innovation, we need to embrace it. (Location 543)
Luckily, though, we do not have to map every grain of sand in this new continent. If we care just about its topographical features, we can get away with studying fewer genotypes. (Location 557)
After mere days, many organic molecules—those normally created by living organisms—had appeared in Miller’s miniature world. (Location 633)
Life’s molecules can emerge in environments even more hostile than that of the early earth. That September an exploding fireball briefly created a second sun in the sky over Murchison, an Australian town of a few hundred souls some one hundred miles north of Melbourne. (Location 641)
As old as the earth itself, it had wandered through outer space for eons, yet it contained several of the amino acid building blocks of proteins, as well as purines and pyrimidines, which are important DNA building blocks. (Location 645)
Incidentally, the single most abundant three-atom molecule in interstellar clouds is water, another blow to the notion that we and our planet are oh so very special. (Location 656)
The first is that life’s molecules emerge spontaneously in the right environment. (Location 668)
The third is a lesson about innovation—I already mentioned it—that is still valid today: Innovation revolves around new molecules and the reactions that create them. To understand innovability, we need to understand the origins of these molecules. (Location 670)
But if the first life consisted of a single replicator, this molecular Adam (or Eve) would have to be spectacularly versatile, able to both carry information and copy itself. (Location 685)
Could they catalyze their own replication? Could they catalyze anything at all? The very purpose and structure of DNA made that seem unlikely. (Location 692)
transformed RNA from an ugly duckling into a white swan.23 RNA had been the stepchild of molecular biology, largely a messenger ferrying information from DNA to the ribosome, the hugely complex molecular machine that synthesizes proteins. (Location 697)
To find that first innovation, the origin of life itself, it would help if we could construct a simple molecule that replicates itself. (Location 709)
Another problem is that the first replicase would have needed to be unfathomably accurate, because a sloppy replicase would trigger an error catastrophe, a process discovered and baptized by the Nobel Prize–winning chemist Manfred Eigen. (Location 720)
The unwelcome stickiness of RNA and the catastrophic Eigen’s paradox are already daunting obstacles to the idea that replicators were life’s first innovations. (Location 744)
finding a sufficiently rich supply of raw materials—energy-rich molecules that also contain all the needed chemical elements, including carbon, nitrogen, and hydrogen. (Location 746)
What is more, absent a steady food supply, (Location 756)
All this leaves a gnawing suspicion that the replicator-first idea puts the cart before the horse. Seduced by the beauty of the double helix, its advocates have dreamed up a gleaming and sophisticated automobile factory—before reliable parts suppliers existed. (Location 766)
In other words, life started not with a replicator, but with a metabolism. (Location 771)
Its raw materials come straight from Mother Earth herself, through searingly hot fissures in the earth’s crust that overflow with nutrients, chemical energy, and the very catalysts that warm little ponds lack. (Location 801)
but it is not the most important one—it’s not the heat that makes a soup, but the ingredients. (Location 810)
A vent’s ways of provisioning life may be bizarre, but they are also highly effective, supporting oases with thousands of times more (Location 819)
organisms than the surrounding seabed. (Location 820)
The microbe called Methanopyrus kandleri can reproduce at temperatures above 122 degrees Celsius, which is higher than the temperature microbiologists use to sterilize their equipment.47 (M. kandleri gets too toasty to reproduce only at 130 degrees, although it still survives there.) (Location 825)
More important is that sources of energy and chemical elements are everywhere in their nutritious waters. (Location 839)
Since then, all ocean water would have passed through them more than ten thousand times, enough to seed the oceans many times over. (Location 840)
As if that were not enough, these laboratories also come equipped with catalysts, not enzymes but minerals such as iron sulfide and zinc sulfide, some of them floating as particles in the vent fluids, others coating the surface of the reaction chambers. (Location 847)
But because waters of all temperature mix around a vent, a suitable temperature niche exists for any one of proto-life’s chemical transformations. (Location 852)
With each turn, it transforms a starting molecule into two, each of which spawns a new cycle and all its molecules, eventually creating four molecules, and so on. (Location 883)
almost ready to crawl out of its cradle, but it still needed a travel bag. All of today’s life uses the same kind of material to pack up its molecules, lipid molecules that are amphiphilic, from the Greek words for “both” and “love.” An amphiphilic molecule “loves” both water and fat, (Location 902)
They can form vesicles, minute hollow droplets enclosed by a tiny spherical membrane, in which the lipid molecules are arranged, as shown in figure 2.59 (Location 906)
The citric acid cycle produces one of their precursors, and they arise even in extraterrestrial rocks like the Murchison meteorite. Heat up powdered meteorite with water, and you will find molecules that self-assemble into vesicles. (Location 914)
Self-organization permeates the universe so completely that most of us don’t even notice it. (Location 927)
Much older than life and natural selection, self-organization is how stars and solar systems form, how the earth accreted, how it acquired a moon, oceans, and an atmosphere, and how the continents started to shift. Self-organization creates the microscopic symmetry of a snowflake and the raging clouds of a hurricane, the shifting shapes of sand dunes and the timeless beauty of a crystal. We shouldn’t be surprised to find self-organization in life’s precursors, because it is everywhere else too. (Location 928)
If the RNA inside this cell replicated faster than the cell grew, it would divide until the vesicle was ready to burst. But if the cell outpaced the RNA in growing, the RNA inside would become increasingly dilute, and many droplets would spawn empty-shelled offspring. (Location 939)
And innumerable innovations have turned the metabolism of a modern cell—the Ferrari’s engine—into a miracle of chemical technology. (Location 947)
Modern metabolic engines are just like that. They can run on many different fuels. And more than that, they can also use each fuel as raw material to manufacture the smallest molecular parts of their body, parts the body needs to grow, to reproduce, and to heal. (Location 952)
Our earliest ancestors got by on a handful of reactions, but modern metabolism, like modern life in general, is much more complicated. (Location 966)
The other eight we have to get from food. In addition, we need thirteen vitamins to live, but can synthesize only two of them, vitamins D and B7 (biotin).65 E. coli can cook all of them up from scratch. (Location 981)
Another part is that E. coli is a phenomenal survivor, thriving not only on the rich nutrient broth of our guts but also in an austere nutrient desert where only seven small molecules supply chemical elements and energy. (Location 985)
From these few ingredients, E. coli can manufacture everything it needs, all sixty-odd biomass building blocks, and from them, the entire cell. But that’s not all. You can remove (Location 987)
We do know, however, that we all come from a single common ancestor. (Location 1021)
Given the powers of self-organization, I would not be surprised if life arose many times, in hydrothermal vents, in warm ponds, or who knows where else. (Location 1022)
This is not a matter of opinion. It has to be true, for a single reason: standards. More accurately, universal standards. (Location 1024)
Even old technologies suffer from this problem: (Location 1029)
All organisms on the planet, from single-celled bacteria to the blue whale, use a standard means to store energy, the molecule adenosine triphosphate (ATP). (Location 1034)
This is a bit depressing, if you extrapolate from the present to your chances of leaving descendants in the distant future. But it also contains a hopeful message, at least for frequent travelers: Wait another four billion years, and you may not need an outlet adapter. (Location 1055)
The first is that life needed to innovate even before it became life—by creating the first autocatalytic metabolisms and the earliest replicators. (Location 1061)
First, innovations created new combinations of chemical reactions, such as those that form life’s building blocks and that built the first replicators. (Location 1062)
Second, innovation required molecules that could help other molecules react. (Location 1063)
Third, innovation created new regulation, the key to coordinate complex life. (Location 1064)
Primitive metabolism has grown into a giant network in which chemical reactions are combined and recombined to permit life’s expansion into every conceivable habitat. (Location 1065)
And regulation, a seemingly mundane process, has become an innovation industry all by itself, bringing forth multicellular organisms with limbs, a heart, and a brain. (Location 1068)
That is, its books contain all possible strings of characters—twenty-six letters and a few punctuation marks. (Location 1084)
but they have nothing on the chemical language of what may be life’s oldest library of creation, the one devoted to metabolism. (Location 1101)
But creating any one of them requires the chemical language of metabolism, the chemical reactions that create the building blocks of life and thus ultimately all living matter. The library’s chemical language can express life itself—all of it. (Location 1102)
While not quite as large as the number of texts in the universal library of human books, it is still much larger than the number of hydrogen atoms in the universe. The metabolic library is also hyperastronomical. (Location 1136)
the library of metabolisms contains all “meaningful” metabolisms—those that allow an organism to survive—and many more, because not all metabolisms are meaningful, just as not all books (Location 1138)
you would find books that surprise you. They contain novel thoughts, ideas, and inventions. (Location 1143)
novel phenotypes that manufacture new molecules or use new fuels. In short, innovations. (Location 1145)
But far from resting on its early laurels, evolution is still discovering such texts, much faster than we can decipher them, in billions and trillions of organisms alive today. Some of these texts appeared less than a hundred years ago—a mere moment in evolutionary time. (Location 1148)
Ammonia (NH3), for example, isn’t just the gas in household cleaners with the sharp, unpleasant odor that makes your eyes burn, but a highly toxic waste product of animal metabolism. (Location 1169)
This metabolic innovation involves five common chemical reactions, each one independently useful to organisms long before the need to detoxify ammonia appeared. (Location 1174)
their ancestors already harbored a chemical blueprint for making urea, still seen in cartilaginous fish like sharks and rays that swam through the oceans long before modern fish appeared. (Location 1178)
Extreme environments are no picnic, but life can be even harder if you face predators and parasites, and especially if escaping them is not an option. (Location 1200)
they develop chemical weapons, molecules so toxic that animals avoid them. Plants are not alone in using chemical warfare, but they are especially adept at it, perhaps because they are, literally, rooted to one spot. (Location 1202)
One of them is the nicotine produced by tobacco plants that some of us blissfully inhale through cigarettes, even though it is so toxic that some farmers use it as an insecticide. (Location 1205)
Some of nature’s ways to find new metabolic texts are familiar, because they dominate in large multicellular animals like (Location 1222)
so that each of our children starts with a new deal. (Location 1224)
Since the shuffling of sexual reproduction occurs between highly similar genomes—two human genomes share 99.9 percent of their DNA letter sequence—it is not the most effective way to create new metabolisms. (Location 1227)
And while mutations can create new proteins, including new enzyme catalysts, they are rare, which means the process is rather slow. (Location 1229)
way of using energy or building organic structures can make its value known only at the speed that it spreads throughout a population, and animals that produce a new generation every few decades—or even every few months—can’t innovate any more rapidly than that. (Location 1231)
but a microbial one: It is the bacteria in the four-stomached cows that convert gigantic cellulose molecules into easily digested glucose. (Location 1244)
hint that the real geniuses of innovation are the smallest organisms on the planet: bacteria. (Location 1245)
This is an example of horizontal gene transfer, a phenomenon tragically unavailable to disadvantaged humans but rampant in microbes. (Location 1255)
And it doesn’t even shuffle a whole genome, but usually just transfers a few genes. (Location 1259)
If all this horizontal gene transfer went on unchecked, the size of a genome would constantly increase over time and become grotesquely bloated. (Location 1269)
Only some edits will improve a text, because the recipient cannot pick and choose which new genes it gets—they are a random subset of the donor’s genome. (Location 1281)
Most bacterial genomes are just as packed with genes trafficked from other sources, many with an unknown origin, though this is scarcely surprising. (Location 1296)
life is experimenting with every conceivable combination of new genes, rereading, editing, and rejuggling its metabolic texts without pause, yielding an enormous and still growing diversity of metabolisms. (Location 1329)
Likewise, a text in the metabolic library needs to be read to reveal its meaning: the metabolic phenotype that determines which fuels an organism can use, and which molecules it can manufacture. (Location 1332)
They include the melanins that protect our skin against radiation, that camouflage a lion’s fur, and that color the ink of an octopus. (Location 1334)
judgment: If you can’t make all essential biomass molecules, your sentence is death, and it is carried out immediately. Organisms with a mutation that has compromised the ability to synthesize essential molecules don’t just fail to live long enough to reproduce. They don’t live at all. (Location 1341)
A genotype tells us which reactions a metabolism can catalyze, the molecules these reactions consume, and the molecules they produce. To decipher its meaning, we would first need to know which nutrients are available—without the right ingredients, you cannot bake a cake—and whether the metabolism can use them to build an essential biomass molecule such as tryptophan. (Location 1346)
The world changes all the time, and no matter how successful a metabolism is today, it will almost certainly become unsuccessful at some point in the future, like an economy that depends on exhaustible fossil fuels. (Location 1372)
Organisms that depend on a single, specific combination of nutrients are evolutionary dead ends, and ongoing innovation is needed to survive.34 (Location 1374)
To count how many such phenotypes exist, the different combinations of a hundred-odd fuels on which an organism could be viable, we just need to keep in mind that an organism may (1) or may not (0) be able to live on each fuel—these two and no other possibilities exist. (Location 1387)
Designing a space to house the library of all possible metabolisms would be challenging, in part because its volumes exceed the number of hydrogen atoms in the universe. (Location 1401)
In other words, each metabolic text has not two, not four, but thousands of neighbors, as many as there are biochemical reactions, each of these neighbors differing in a single letter and reaction. Shelves that can hold this sort of inventory aren’t easy to find. (Location 1416)
As our reaction universe increased from one to two to three reactions, its metabolic texts occupied the endpoints of a line, a square, or a cube, which exist in a one-, two-, and three-dimensional space. (Location 1425)
The edges of a hypercube are equally long, adjacent edges are at right angles to one another, and each corner corresponds to a possible metabolism. And such cubes in high-dimensional space turn out to have curious properties well suited to house the metabolic library. (Location 1435)
In other words, we can arrange the library’s metabolic texts on the corners of a hypercube in a 5,000-dimensional space. (Location 1439)
You cannot cram the metabolic library into three puny dimensions. It needs thousands of dimensions to breathe. (Location 1440)
City neighborhoods are useful because of proximity—everything is reachable within a few easy steps—and neighborhoods in the metabolic library are important for the same reason. Evolution can reach them in a few small steps, minor edits in a genotype. (Location 1452)
This diversity will be crucial to understanding innovability, as we shall see shortly. (Location 1456)
it walks farther and farther, to more and more distant shelves in the library. (Location 1457)
We can travel enormous distances through the library and encounter very different stories with the same moral, everywhere. (Location 1462)
because the library contains many more metabolisms than the number of organisms that have existed on earth since life began. Even after 3.8 billion years of evolution, life has explored only a tiny fraction of the library. (Location 1465)
what was around the next corner of the library for evolution to proceed. (Location 1467)
rather than simply live in it, we need to have some way to grasp where new and meaningful texts are. (Location 1468)
A catalog is like a map for this library—it is a genotype-phenotype map that tells us where to find the genotypes with any one phenotype. (Location 1473)
Take a metabolism with any one phenotype, such as viability on glucose, and ask, What (Location 1479)
On the one hand, the odds against finding just one useful metabolism are vast. (Location 1486)
There has to be more than one metabolism—perhaps even many—that solves the problem of surviving on glucose. (Location 1487)
Nature would make a simple and brutal evaluation of the new text: life or death. (Location 1492)
Because each step alters a text at random, this walk is a random walk through the metabolic library, similar to how a drunkard might stagger home from a night out at the bar, with one difference: Each step in our random walk must encounter a text with the same meaning, the same phenotype. (Location 1497)
because the starting text would have no viable neighbors. We would be rooted to the spot. The same would be true if there were a few such texts scattered widely through the library—we could not reach them without destroying viability on the way. (Location 1500)
then these neighbors are minor variations on the manual. The first question: Do any of them contain sufficient information to produce all sixty biomass building blocks from glucose? (Location 1535)
The neighborhood of any one text contains many other viable texts like it. But nothing had prepared us for what came next, when we began to venture further. (Location 1539)
We had walked, computationally speaking, almost all the way through the library—80 percent of the distance that separates the furthest volumes—before we were finally unable to find a glucose-viable text by taking a single step. (Location 1544)
These random walks had led just as far away as the first one. Each of them led to a metabolism that differed in almost 80 percent of its reactions from E. coli. (Location 1548)
These texts were just as different from each other as they were from that of E. coli—they encoded metabolisms with very different sets of chemical reactions. The library does not have clearly distinct sections, like rooms that separate all texts on history from those on science.44 (Location 1557)
Viable metabolisms can have very different texts—they share as little as 20 percent of their reactions—and form a vast connected genotype network in the metabolic library. (Location 1580)
First, many metabolisms are viable on the same fuel molecules—it matters little which fuels you choose. (Location 1589)
It crowdsources, employing huge populations of organisms that scour the library for new texts. (Location 1598)
Imagine a hapless organism that steps off the path connecting viable metabolisms by encountering a change—perhaps a gene deletion—that disrupts the metabolic instructions for manufacturing a key molecule. (Location 1601)
and that, from one stack to the next, endlessly meandering swirls of living things that try new combinations of chemical reactions over and over and over again. Some die. (Location 1605)
That action would vanish if genotype networks did not exist. If only one text could confer viability on any one fuel, then all members of a population would have to share that text, crowding around it in the library. (Location 1607)
Genotype networks are the first of two keys to innovability. And now for the second: the immense diversity of the neighborhoods where these explorations begin. (Location 1611)
But these odds change if a crowd of readers can browse the library along a genotype network that extends far through the library. Because genotype networks are so large, the population could explore thousands of neighborhoods and increase the odds of finding the new lifesaving phenotype. (Location 1621)
Different neighborhoods must contain different novel phenotypes. (Location 1623)
we chose pairs of metabolic texts that had the same phenotype (viability on glucose) but that were otherwise very different. (Location 1627)
Because we knew that different neighborhoods contain different innovations, we expected the list to grow over time, as new phenotypes became accessible. But we expected that we would run out of new phenotypes eventually. Wrong. Long after our notepads were full, we were still encountering innovations. (Location 1643)
For a library whose readers have no catalog and can only take random steps, and where missteps are punishable by death, it would be disastrous, because they would be stuck on whatever shelf they started. (Location 1660)
Even more uncanny: Life’s other libraries are organized the same way. (Location 1664)
B. saida survives by producing antifreeze proteins that lower the freezing temperature of its body fluids, much like the antifreeze in a car’s engine coolant. (Location 1671)
Change the amino acid sequence needed to produce a particular protein and, presto, huge areas of the earth’s oceans become livable. (Location 1673)
you would first be astonished by how many different kinds of molecules there are, millions of them. (Location 1676)
These regulatory proteins allow the information encoded in a gene to become transformed into an amino acid string. (Location 1688)
I do not just mean the molecular shape of the twenty kinds of amino acids in proteins, and the order in which they are strung together—the primary structure of a protein. (Location 1693)
The economy of living organisms, like that of the human world, is constantly changing, and in response, evolution brings forth new protein shapes, innovations that take on new jobs. These jobs open whenever life needs to solve a new problem, like that of surviving the menacing knives of growing ice crystals. (Location 1726)
the innovations that fill these jobs are often discovered more than once. (Location 1729)
Such minimal changes can have dramatic consequences for life, as the bar-headed goose from Central Asia could tell us. It is one of the world’s highest-flying birds. It has (Location 1743)
Molecular innovations like the Arctic cod’s antifreeze or the bar-headed goose’s oxygen-binding hemoglobin are valuable because they expand an organism’s habitat, which means more food, better survival, and more offspring. (Location 1750)
such as the ability to discriminate between one kind of food and another, to choose a nutritious rather than a poisonous plant for dinner. (Location 1752)
They are the unfortunate side effect of our continual improvement of antibiotics, the result of a biological arms race of bacteria against biotechnologists. (Location 1762)
Curiously, when our own body cells go rogue, proliferate wildly, and evolve rapidly—in cancer—they often use similar efflux pumps to rid themselves of unwanted cancer drugs. (Location 1768)
They show how minute alterations of no more than a few atoms can have effects that percolate through an organism that is a million times as large and alter the life of its descendants forever. (Location 1778)
The task requires comparing many old proteins and the new ones they brought forth. Thousands of them. (Location 1789)
The universal protein library is the collection of all proteins that life has created, and all proteins that it could create. (Location 1799)
Each protein text perches on one vertex of this hypercube, and just like in the metabolic library, each protein has many immediate neighbors, proteins that differ from it in exactly one letter and that occupy adjacent corners of the hypercube. (Location 1811)
A neighborhood like this is already large, and it would be even larger if you changed not one but two or more amino acids. Clearly, this can’t be bad for innovation: With one or a few amino acid changes, evolution can explore many proteins. (Location 1817)
those that help them live. (Location 1826)
protein is meaningful only if it is useful, and defective mutant proteins that do not fold properly have lost their meaning. (Location 1826)
Evolution explores the protein library through huge populations of organisms. (Location 1839)
To imagine the sheer number of these solutions is difficult, but that says more about the limits of our imagination than about life’s innovability. (Location 1878)
We also need to find out where these solutions are and how they are organized—in meticulous stacks or thrown together in unruly piles. (Location 1880)
Every one of these organisms harbors thousands of proteins, and each is only the last link in an unbroken chain of protein creation that goes back billions of years. (Location 1883)
But an altered protein does not always lose its function and meaning. (Location 1895)
Legumes like soybeans, peas, and alfalfa can extract vital nitrogen from its nearly unlimited supply in the air. (Most other plants need to extract nitrogen from the soil, where it is often scarce, unless a farmer has applied fertilizer.) (Location 1924)
To protect those enzymes, plants manufacture globins, which keep oxygen safely away from the bacteria. (Location 1928)
A genotype network connects globins and extends its tendrils far through the protein library. (Location 1942)
sheets and helices are arranged like the staves of a barrel. The stunning fact is that some enzymes with this fold do not have a single amino acid in common. (Location 1948)
Life’s enormous tree and all its proteins, however vast and beautiful, is but a smeared reflection in a filthy mirror, a faint shadow of the vast Platonic realm that genotype networks inhabit. (Location 1959)
details. I had seen Evandro’s quiet, pensive personality before, in people whose minds constantly grapple with the deep mysteries of life. (Location 1972)
The neighborhoods of two proteins contain mostly different functions, even if the two proteins are close together in the library. (Location 1983)
The protein library has neighborhoods that are highly diverse, just like the metabolic library. (Location 1985)
We can organize RNA texts into a hypercubic library—not quite as large as that of proteins, but still formidable—where (Location 1999)
just as natural selection would demand. (Location 2051)
Like many good experiments, this one carries more than one powerful message. (Location 2060)
The first is that many RNA texts can express the molecular meaning of the starting fuser and splitter molecules. (Location 2060)
Such laboratory evolution experiments monitor how evolution transforms entire populations over many generations. RNA molecules are especially attractive for such experiments, and for the same reason that they were central to early life. (Location 2073)
The trick satisfied natural selection’s key requirement that a molecule’s function be preserved for its survival to the next generation. (Location 2093)
After the first generation, many molecules had already mutated, and only some mutants had survived. (Location 2096)
the molecules in the population differed from the starting RNA by an average of five letters, and some by as many as ten letters. The billion readers had spread out in the library. (Location 2097)
The spread-out population found an RNA molecule that excelled at the new task eight times more rapidly than the highly concentrated population.65 (Location 2108)
Even simple enzymes are more difficult to understand than most human machines. (Location 2120)
that a genotype network could accelerate the population’s discovery of this solution. (Location 2121)
Science can explain general principles of innovability even if it cannot predict any individual innovation. (Location 2127)
Their lactase gene was turned on—in technical terms, it was expressed—which means that their bodies transcribed the DNA instructions for lactase into RNA and translated this RNA into the needed enzyme. (Location 2137)
Genes like the lactase gene, which our bodies can turn on or off, are regulated genes. (Location 2139)
And they spread blazingly fast, from zero to more than 90 percent of some populations, in a blip of time, the eight thousand or so years since humans first discovered the pastoral lifestyle. (Location 2143)
Surprising as it may seem, lactose-induced indigestion is deeply connected with innovation. (Location 2146)
And no understanding of innovability would be complete without grasping how new regulation appears. (Location 2151)
Common sense suggests that cells should regulate beta-gal to avoid wasting these materials, but if common sense were the surest guide to nature’s ways, biologists would have little to (Location 2193)
A population that initially contains 50 percent of such wasteful cells would contain less than 1 percent after eighty days, and fewer than one in a million after merely three hundred days. (Location 2203)
Cells leave them off by default and activate them only when needed—through transcriptional regulators that help rather than prevent DNA polymerase from transcribing a gene. (Location 2211)
One of regulation’s roles in metabolism is that of a penny-pinching manager, requisitioning just the right amount of ingredients, anxious not to squander money on even as little as an extra potato. (Location 2219)
Each recipe is a sophisticated gene expression program encoded in the genome. It tells cells just when and how much to make of each protein ingredient in an organism. (Location 2222)
What is more, evolution has untiringly created new recipes that brought forth ever-new dishes, innovations in cells, tissues, and organs, as well as entirely new kinds of bodies that emerge through the shifting and enormously complex patterns of regulation. (Location 2226)
And the identity of an innovative cell type is really a new fingerprint, caused by a new pattern of gene regulation.15 (Location 2245)
Through other regulators. And their regulators? Through yet other regulators. All these regulators often form daisy chains, regulation cascades like that shown in figure 15. (Location 2261)
This state of a circuit (e.g., “on,” “off,” “on,” “off,” “off”) is the gene expression pattern that ultimately creates a cell’s molecular fingerprint, because each of the circuit genes regulates many other genes. (Location 2286)
If a gene’s activator, for example, is abundant in the front like bicoid, the gene would be turned on by bicoid in the front, but nowhere else. (Location 2314)
If we could predict the regulatory dance that shapes embryos from flies to humans, we could predict how organs, tissues, and cells form, and why different organisms have very different body plans. (Location 2341)
in the form of computers that can describe a circuit’s choreography through mathematical equations, process these equations in their silicon brains, and predict a circuit’s gene expression patterns. (Location 2345)
John’s nonconformism surely was an asset in his research, because he swam with bold strokes against the mainstream. (Location 2350)
And like a good flight simulator, this one worked—not a small achievement. (Location 2360)
It can mimic the early development of fruit flies, and does so at enormously accelerated speed. (Location 2360)
Limbs—old and new—owe their existence to a family of regulators that are used in building the bodies of thousands of organisms, from jellyfish to humans. (Location 2375)
Study not just one circuit but many, an entire library of circuit genotypes and their expression phenotypes. (Location 2453)
This emerging research field joins experimental data with mathematics and computation to find out how molecular parts like a fly’s regulators cooperate to shape whole biological systems, that is, organisms.51 Mathematicians (Location 2545)
with a circuit, we computed its expression code, altered a wire—adding or eliminating regulation of one gene—and thus stepped to a random neighbor with the same expression code, and from that to the neighbor’s neighbor, and so on, until we could not go further without changing the expression code. (Location 2584)
Our explorations also taught us that all circuits with the same expression code are typically connected in the library. (Location 2593)
And he found, as we had, that regulation circuits are sturdy enough to be rewired.57 Ninety-five percent of his rewired circuits function normally. (Location 2606)
Nature has solved the same regulation problem in two different but equally adequate ways. Not only that, but a path of small mutational steps connects these solutions, because the species shared a common ancestor. (Location 2613)
There are many trillion possible expression codes, but the immediate neighborhood of any one circuit contains at most thousands of other circuits—those differing in one wire—too few to find all possible expression codes nearby. (Location 2621)
We found that most expression phenotypes in the neighborhood of A are different from expression phenotypes in the neighborhood of B—regardless of A and B’s phenotype, number of genes, or wiring. Different neighborhoods contain different phenotypes. (Location 2626)
Circuits with the same gene expression phenotype are organized in vast and far-reaching genotype networks. (Location 2629)
How could innovability in metabolism, in proteins, and in regulation circuits have the same source, a library full of chemical meaning with a common cataloging system? (Location 2636)
self-organization, a peculiar kind of it. We will turn to it next. (Location 2638)
Disorder: bad. Order: good. (Location 2646)
Order and information remain central to evolution, but in recent years we have also learned, thanks to genotype networks, that perfect order is as hostile to innovation as total disorder. (Location 2647)
Nature doesn’t just tolerate disorder. It needs some disorder to discover new metabolisms, regulatory circuits, and macromolecules—in short, to innovate. (Location 2648)
A deeper reason is that there are many more ways to build a pirate ship than those contained in Lego’s instruction book. (Location 2653)
but in fact so widespread that it deserves to be called a hallmark of life: robustness, (Location 2656)
Software bugs like this cause billions of dollars in economic loss every year. Human language is robust. Programming language, not so much. (Location 2661)
Many genes apparently serve no purpose. (Location 2670)
they began to engineer “knockout mutations” into the genome, so called because they delete a single gene, an entire meaningful paragraph from a genomic text. (Location 2679)
Thousands of these mutants do just as well as their ancestor and show no obvious defects. (Location 2690)
Like natural language, life is robust—in this case to gene deletions. (Location 2692)
found that some sixteen hundred variants—more than 80 percent—could still kill bacteria. (Location 2722)
But the importance of robustness goes far beyond that. It explains the mystery of genotype networks and of innovability. (Location 2731)
This means that even when the genotype has changed, there need not be any change in the phenotype, in the organism itself and its observable features. (Location 2735)
Genotypes with the same phenotype would be like stars in the sky—a billion twinkles isolated by light-years of empty space. (Location 2748)
nature’s libraries that harbor untold innovations. Robustness allows some disorder in genotypes, and permits nature to explore new configurations of its Lego blocks through the genotype networks it helps create. (Location 2751)
They exist in the timeless eternal realm of nature’s libraries. But they certainly have a form of organization—so complex that we are just beginning to understand it—and this organization arises all by itself. And as with galaxies and membranes, the principle behind their self-organization is simple: (Location 2756)
It must be simultaneously conservative and progressive, like some aviation pioneer embarking on a transatlantic flight in the Wright brothers’ original flyer: (Location 2763)
Certain in the knowledge that he must invent a new design to complete the journey, he must also keep the old one in the air until he does. (Location 2764)
Nature must keep what works alive while exploring the new. Genotype networks are essential for exploration. But they aren’t made for conservation. (Location 2765)
memory—and its power to conserve even tiny improvements, given enough time, is so great as to seem absurdly unbelievable. (Location 2767)
but also the less appreciated and peculiar lens material—an ancient innovation that required nothing but new regulation. (Location 2775)
The finished product—like the human eye—is literally incredible without the knowledge that it was built one brick at a time. (Location 2802)
Many mutations neither harm nor help when they first arise. Such neutral changes are a consequence of life’s robustness and the disorder it allows. (Location 2809)
In a similar vein, the German physicist Heinrich Hertz, whose experiments validated the electromagnetic theory of James Clerk Maxwell, saw no practical purpose to his discovery. (Location 2825)
Kimura asserted that most genetic variation seen in nature is neutral. (Location 2832)
Neutral change provides the browsers of nature’s libraries with a safe path to innovations through treacherous territory of meaningless texts. Without genotype networks and the neutral changes they allow, the exploration of nature’s libraries would be just about impossible. (Location 2834)
them? If we only step to the text’s neutral neighbors—those with the same hammerhead shape—and determine the shape of all their neighbors, we already find 962 new shapes. (Location 2849)
But we can say with certainty that countless millions and billions of new shapes are near them, all explorable because evolution’s readers can spread out along the genotype network without suffering death. (Location 2854)
congregating near a text describing a circuit with a specific expression code that helps shape some body part, like a bird’s wing. (Location 2868)
The further the readers must travel to find it, the more time they need to find this innovation. (Location 2870)
Common sense dictates that the same applies to the library, that a new expression code is like a single needle in a haystack many times the size of the universe. (Location 2873)
In other words, starting from anywhere in the library—anywhere—you need not walk very far, only fifteen steps away from a genotype network, before finding the genotype network of any other circuit. (Location 2881)
The circle around this dot has a radius that is 15 percent as long as the sides—this is how far a reader would have to travel from a genotype network, on average, before finding a specific new expression code, as we had found out from exploring the circuit library. (Location 2885)
The more dimensions they have—the larger their collection of metabolisms or molecules—the smaller the distance to find specific innovations. (Location 2905)
The astonishing fact that evolution needs to explore one 10-100th of a library to secure the arrival of the fittest goes a long way to explain how blind search produces life’s immense diversity. (Location 2911)
because the haystack contains more than one needle. (Location 2914)
and they are organized into sprawling but navigable networks. (Location 2915)
They form a dense tissue of networks, each genotype network surrounded by many others, interwoven with them on all sides, a tissue so complex that it looks nowhere the same, consisting of millions, billions, or more of different strands, each one corresponding to a different phenotype. (Location 2917)
Because genotype networks and their fabric are a consequence of robustness, robustness is immensely valuable to innovation. (Location 2922)
The ideal of simplicity is not just an aesthetic ideal or a philosophical principle. In engineering it also has an economic angle. (Location 2939)
but scientists have known for many years that just two molecules interacting in the right way could achieve the same goal. (Location 2945)
What looks like a wastefully complex suite of genes is actually the secret to survival in more than one environment. (Location 2950)
A large collection of metabolic reactions makes an organism viable in multiple environments. In biology, increased complexity means increased robustness to environmental change. (Location 2957)
Duplicate genes, like humans, are created equal, but they do not stay that way for long. They accumulate mutations that alter their DNA and its molecular meaning, and lead to increased specialization on one environment. (Location 2959)
scarce. The redundancy of many gene duplicates is more apparent than real, because they ensure robustness to changing environments. (Location 2963)
they must also design for changing environments. (Location 2964)
To do that well you need a more complex fore-and-aft rig with two sails, a jib in front of the mast and a mainsail behind. Navigating a changing environment—current, waves, and wind—needs complex technology. (Location 2968)
Over time, unchanging environments result in less complexity, because robustness becomes less important. (Location 2970)
Its cells live inside the aphid’s cells, where they provide their host with a vital service: They manufacture essential food molecules, especially amino acids that aphids cannot manufacture themselves, and that plant sap does not contain. Buchnera is a tiny food factory that keeps aphids alive. (Location 2981)
Now its metabolic network has a puny 263 metabolic reactions. (Location 2997)
It takes no genius to see why Buchnera could survive all these deletions and become so much simpler than E. coli. (Location 3001)
To survive in a simple, unchanging world, a simple metabolism does the trick, and complexity becomes not only superfluous but wasteful. (Location 3004)
We call such networks minimal metabolisms. (Location 3028)
One lesson from such minimal metabolisms is that living in many environments generally requires complexity. (Location 3030)
These reactions are neutral in one environment, but they can become essential in a different environment. (Location 3039)
At the core of this innovability is the self-organized multidimensional fabric of genotype networks, hidden behind life’s visible splendor, but creating this splendor. It is the hidden architecture of life. (Location 3045)
Trial and error, for one thing. Thomas Edison, an archetype of inventive genius, “tested no fewer than 6,000 vegetable growths, and ransacked the world for the most suitable filament material” until he eventually stumbled upon bamboo as the best solution for the fickle filaments of his incandescent light bulb. (Location 3064)
“you need the willingness to fail all the time. (Location 3070)
The historical battlefields of science and technology are littered with brilliant minds who took wrong beliefs to their graves. (Location 3082)
Despite the cliché of human innovators conjuring unimagined worlds from the depths of their minds—from Archimedes in his bathtub to Einstein in his patent office—the truth is that technological innovation depends on the same kind of crowdsourcing that biological innovation uses when its chemical libraries are explored by armies of browsers. (Location 3088)
The more explorers, the more solutions can be explored, with correspondingly greater odds of success. (Location 3096)
Multiple origins are possible because the problems of technology—like those of biology—have multiple solutions. (Location 3107)
Environmental engineers—they seek to solve the same problem to forestall catastrophic climate change—have already come up with several further carbon-scrubbing technologies that use molecules like monoethanolamine and sodium hydroxide. (Location 3114)
Edison said it well: “To invent, you need a good imagination and a pile of junk.” (Location 3128)
Innovation is combinatorial. It combines old things to make the new. (Location 3142)
In his book The Nature of Technology the economist W. Brian Arthur goes further to say that even entire “technologies somehow must come into being as fresh combinations of what already exists.” (Location 3153)
All evolutionary innovations, discovered as they are in searches through nearly infinite libraries, are combinatorial, just as new books combine old letters into new meanings. (Location 3156)
recipes that use some form of mutation and selection to solve really difficult real-world problems, entirely inside a computer. (Location 3168)
by instructing a computer to start with a completely arbitrary solution—any solution at all, no matter how bad. (Location 3189)
If so, the program selects that mutant. (Location 3191)
Military planners use them to plot optimal routes for unmanned drones that patrol hostile territories. (Location 3195)
Fund managers use them to predict the movements of financial markets. (Location 3197)
Nature is better at recombination, much better, for one simple reason: standards. (Location 3203)
but also on standardized (Location 3212)
ways of measuring quantities like temperature, mass, or electric charge. (Location 3212)
It allows nature to cobble together—blindly, without any ingenuity—the astronomical numbers of genotypes needed to find innovations. (Location 3218)
If we could take a small number of different objects, create a standard way to link them, and recombine them into every conceivable configuration—mindlessly—our powers to innovate could be just as immeasurable as those of nature. (Location 3224)
Mathematicians describe this process more precisely, by saying that a circuit calculates the values of a function, that it takes an input and computes an output. (Location 3258)
One of the simplest such functions is the AND function, which is needed whenever one searches, for example, an electronic database of sheet music for a specific composition, such as Mozart’s Magic Flute. (Location 3265)
Most integrated circuits are hardwired in the factory, but robots like YaMoR are equipped with programmable hardware, chips that can be rewired to alter what some logic gates do—changing an AND gate into an OR gate, for example—and how these gates are wired. (Location 3298)
With more than a million logic gates, such chips are not just simple toys but powerful and flexible computing engines that could eventually help machines learn much as we do—by rewiring their own hardware—and create autonomous robots that can not just explore the world but also learn about its potholes and other pitfalls. (Location 3301)
A programmable circuit’s logic gates and wiring are an analog of a genotype that can be altered to explore new computations, the analog of new phenotypes. (Location 3305)
These principles already suffice to create chips that play chess more powerfully than mankind’s best, to find a single page in a million different books, or to “print” objects in three dimensions. (Location 3315)
Are entire libraries of digital circuits—huge circuit collections that can be created through recombining logic gates in every possible way—organized like the library of biological circuits? The answer can tell us whether the warp drives of biological innovation could be mounted on the spaceships of technological innovation. (Location 3317)
The networks of circuits he found reached even farther through the library than the genotype networks from earlier chapters: (Location 3344)
most circuits one could walk all the way through the circuit library without changing a circuit’s logic function. (Location 3344)
biology. More than 80 percent of functions are found near one circuit but not the other. (Location 3351)
We already know that they continually rewire the synaptic connections between our neurons, but perhaps our brains also explore new connections in the same way that organisms explore a genotype network. (Location 3367)
When Karthik analyzed logic circuits that differed in their complexity—their number of logic gates—he found that the simplest circuits could not be rewired without destroying their function. (Location 3371)
Such simple circuits have no innovability, because they cannot explore new configurations and computations. (Location 3373)
Just as in biology, innovability comes from complexity, apparently unnecessary, but actually vital. (Location 3376)
Like oil and water, simplicity and innovability don’t mix. (Location 3377)
itself: With a limited number of building blocks connected in a limited number of ways, you can create an entire world. (Location 3379)
Enormously complex patterns can emerge, a huge and unpredictable variety of forms, including “self-replicating” clusters of cells that spawn more of themselves. (Location 3392)
to understand life and its diversity through the language of mathematics and computation. (Location 3395)
regulate their own molecules and help them survive. And while these circuits are very different from digital computers—for one thing, they are self-assembled from organic molecules—they hint at a deep unity between the material world of biology and the conceptual world of mathematics and computation, a unity that Conway and Darwin could barely have guessed at. (Location 3407)
More than that, the mathematics of biology allowed us to see that these libraries self-organize with a simple principle, as simple as the gravitation that helps mold diffuse matter into enormous galaxies. (Location 3414)
The question whether knowledge—especially mathematical knowledge—is created or discovered has occupied philosophers for more than twenty-five hundred years, at least since Pythagoras and certainly since Plato. (Location 3420)
In so doing it can shift the debate about discovery versus invention—uncomfortably abstract for millennia—from its traditional focus on languages like that of mathematics to incorporate experimental science. (Location 3437)