Arrival of the Fittest: Solving Evolution's Greatest Puzzle

by Andreas Wagner

  What’s baffling about such genes is why they would exist at all. Not only does a superfluous gene waste scarce resources, but mutations that incessantly rain down on DNA would eventually erode it, transforming it over time into something like an abandoned building that crumbles to dust over the years.3

  Many of these “purposeless genes” were unearthed after the genome of an organism that we already met in chapter 5 had become fully sequenced. It is a microbe, the brewer’s yeast Saccharomyces cerevisiae that helps us make beer and wine, and it is as useful for understanding cell biology as fruit flies are for embryology.4 The yeast genome in hand, biologists realized that thousands of its genes had an unknown role in the microbe’s life. To reveal this role, 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.5 The logic of the experiment is essentially like analyzing the workings of a car by eliminating one part at a time: Remove the disk rotor, and if stepping on the brake pedal no longer slows the car, you have learned that the rotor is needed for braking. In the same way, if you knock out a particular yeast gene and find that its cells can no longer divide, the gene was involved in cell division. Knock out a fruit fly gene and if the mutant no longer forms wings, you know that the gene helps build wings.

  The results of gene knockout experiments had trickled into the scientific literature gene by gene, until gene-knockout technology became powerful enough to delete thousands of genes. That’s what researchers at Stanford did in impressive experiments starting in the late 1990s, when they used the list of yeast genes revealed by the yeast genome and set out to delete every single yeast gene. They created some six thousand different yeast mutants, each of them missing a gene, placed these mutants into chemical environments where their unmutated ancestor could have thrived, and examined each mutant for specific defects, clues about the missing gene’s function.6

  What they found was completely unexpected. Thousands of these mutants do just as well as their ancestor and show no obvious defects. The genes that had been deleted to create these mutant genomes served no obvious purpose. Since then, scientists have blocked countless genes in many other organisms. And these genes tell the same story as a vowel-free English sentence: Like natural language, life is robust—in this case to gene deletions.7

  Discoveries like this do mostly one thing: They create new questions. One of them was how? What mechanism creates robustness?

  For some genes the mechanism was straightforward. These genes were duplicates, stretches of DNA that occur more than once in a genome, like pages in a book that someone has photocopied twice by mistake. Gene duplications happen when an organism copies or repairs DNA, and are by no means rare: About half of the genes in our own genome have duplicates.8 Since identical duplicates can do the same job, one of them can take over if you knock out the other.9 Like the redundant power supplies that hospitals use to safeguard against power failure, like redundant computer memory to prevent data loss, like redundant circuitry in commercial aircraft to prevent crashes, some genes are only “useless” until they’re needed.10

  But many of the dispensable genes have no duplicate—they are single-copy genes—and for them the causes of robustness are not as simple.

  We understand those causes best for genes that encode the enzymes of metabolism. A metabolism’s chemical reaction network resembles the dense road network of a city’s core, like that formed by the right-angled streets of midtown Manhattan. A driver who wants to get from 42nd Street and Second Avenue to 48th Street and Seventh Avenue has any number of choices for following the street grid six blocks north and seven blocks west. The major arteries have multiple lanes—think of them as redundant, because even if one is blocked, the driver can continue in another. But even a complete roadblock is not a problem, because the driver can use a different part of the grid, and a really intrepid driver might even cut through parking lots with entrances on two parallel streets. Such detours slow down but don’t halt the journey.

  A knocked-out metabolic gene is a bit like a blocked road that halts the flow of molecules through a network of metabolic reactions. The detours around the roadblock are alternate metabolic pathways, sequences of chemical reactions that can absorb the backed-up molecular traffic, synthesize needed molecules in different ways, and ensure that life in metabolism city goes on.11 This isn’t just an abstract metaphor. Biotechnologists can create metabolic roadblocks by knocking out metabolic genes, and when they do, organisms like brewer’s yeast often survive by rerouting the flow of essential molecules. In metabolism, this kind of robustness is even more important than redundancy.12

  Robustness isn’t limited to metabolism and whole genomes. It is just as pervasive in individual proteins like lysozyme. This protein kills bacteria by destroying their wall of protective molecules. It appears not only in human saliva, tears, and even mother’s milk, but in a large number of other animals, and even in viruses that attack bacteria.13 When scientists want to find out how a protein like this works, they do something akin to knocking out genes in a genome, but on a smaller scale—they change individual letters in the protein’s amino acid string and observe the effects of each change. When they engineered more than two thousand lysozyme variants, each one with a single altered amino acid, they found that some sixteen hundred variants—more than 80 percent—could still kill bacteria. Proteins like lysozyme, and there are many, are as robust as metabolisms. And the same holds for regulation circuits—we already heard about a circuit in the bacterium Escherichia coli that can be rewired in the laboratory without ill effects (chapter 5).

  The most obvious benefit of such robustness is that it keeps organisms alive. Its importance goes back all the way to the first self-replicating RNA molecules and the fatal error catastrophe, in which small errors compound over time until replication becomes impossible (chapter 2). That was a true catch-22: RNA molecules have to self-replicate with few errors to acquire the ability to self-replicate with few errors. But only a bit of the robustness in today’s RNA could lower the bar for this problem to a manageable height: Because a few replication errors in a robust molecule do not erode its ability to self-replicate, robustness provides a stay of execution by error catastrophe, perhaps long enough to stumble upon better replicators.14

  But the importance of robustness goes far beyond that. It explains the mystery of genotype networks and of innovability.

  To see why, we need to revisit nature’s libraries, where each metabolism (or protein, or regulation circuit) is represented by a single text, and where each of this text’s neighbors differs in a single letter, a single reaction, or a single enzyme and its gene. We know from gene deletion experiments that many of these neighbors, for example metabolisms where a single reaction has been eliminated through a gene knockout, suffer no ill effects. 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. An organism like this is robust. The extent of its robustness is reflected in the number of its neighbors—variants a single small change away—whose phenotype remains unaffected by the change: The more neighbors with the same phenotype, the more robust the organism is.15 Think of this phenomenon at its theoretical limits: If a metabolism, or a protein, or a regulatory circuit had no viable neighbors it would be maximally fragile. Change one of its parts, and death follows. At the other extreme, if every possible change were viable, if every neighboring metabolism had the same phenotype, the metabolism would be maximally robust: No single change could kill it.16

  These extremes do not exist in the real world. No real organism completely lacks robustness, and no organism is perfectly robust. But all organisms, their structures and activities, are to some extent robust, and it is precisely this robustness that allows populations to explore nature’s enormous libraries. The number of texts with any one meaning in these libraries is vast, but these texts fill a tiny fraction of the library, like a
droplet of molecules in an ocean. In the complete absence of robustness, many texts might tell the same story, but none of their neighbors would. No explorer could browse one text and find a neighboring one with a single page—or word, or letter—changed but its meaning nonetheless intact. Genotypes with the same phenotype would be like stars in the sky—a billion twinkles isolated by light-years of empty space.

  Luckily, the biological world is different. Starting at any one robust text, we can step to one of its many neighbors with the same meaning, and we can step to one of its robust neighbors, and so on, never changing this meaning, and thus exploring ever-new regions of 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.

  Genotype networks are yet another example of the pervasive self-organization we first encountered in chapter 2—the same phenomenon that pervades both the living and nonliving worlds, from the formation of galaxies to the assembly of membranes. But they are a peculiar example of self-organization. Unlike galaxies, which self-assemble through the gravitational attraction of cosmic matter, or biological membranes, which self-organize through the love-hate relationship of lipid molecules with water, genotype networks do not emerge over time. 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: Life is robust. This robustness is both necessary for genotype networks—otherwise synonymous texts would be isolated from one another—and it is sufficient.17 Wherever metabolisms, proteins, and regulatory circuits are robust, genotype networks emerge.

  Robustness is sufficient to create genotype networks, but genotype networks alone are not sufficient for evolution. The reason is that evolution must meet two demands, seemingly at odds with one another. It must be simultaneously conservative and progressive, like some aviation pioneer embarking on a transatlantic flight in the Wright brothers’ original flyer: 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. Nature must keep what works alive while exploring the new. Genotype networks are essential for exploration. But they aren’t made for conservation.

  This bears emphasizing, because the exciting new discoveries about genotype networks can tempt us to forget the critical importance of natural selection. Conservation is the job of natural selection—evolution’s memory—and its power to conserve even tiny improvements, given enough time, is so great as to seem absurdly unbelievable. Literally so. In the Origin Charles Darwin wrote about eyes, surely among the most spectacular innovations in life’s history, “To suppose that the eye with all its inimitable contrivances for adjusting the focus to different distances, for admitting different amounts of light, and for the correction of spherical and chromatic aberration, could have been formed by natural selection, seems, I freely confess, absurd in the highest degree.”18

  When light passes through our eye, the lens projects a fantastically accurate, undistorted image of the outside world onto our light-sensing retina. To do so, it must refract light’s path, changing its direction at a precise angle.19 It’s not just the lens’s shifting shape that makes this possible, but also the less appreciated and peculiar lens material—an ancient innovation that required nothing but new regulation.

  Shine a flashlight obliquely onto a body of water, and you will see that the light ray kinks at the surface. Dissolve sugar in the water, and the kink’s angle gets sharper—the more sugar you dissolve, the sharper it gets. (The food industry uses this principle to measure the amount of sugar in wine, soft drinks, and juices.) Our eyes refract light just like that, except that they use proteins instead of sugar. These proteins—crystallins—occur at very high concentrations in the lens, which allows the lens to refract light strongly.

  Crystallins are so uncannily good at refracting light that it’s tempting to think that they were tailor-made for constructing lenses, and therefore rare. Not true. Many crystallins are metabolic enzymes, the very same enzymes that promote chemical reactions elsewhere in the body, albeit in smaller numbers. Different organisms use different enzymes as crystallins. What distinguishes them from other proteins is that they do not clump easily, not even when they are expressed at the extreme concentrations needed in the eye.20 Eyes build their lenses out of proteins like the one that detoxifies alcohol, just because they confer transparency—the same way you might use an old brick as a bookend simply because it happens to be heavy. Crystallins are also some of the sturdiest proteins around, so long-lived that the crystallins that make up the lens of the human eye last an entire lifetime, from birth to death.21 But sometimes they wear out and start to clump, making the lens milky white. When this happens a cataract has formed, with consequences both well known and disastrous: blindness.22

  Though Darwin knew nothing of protein chemistry, he did suspect—and today we know—that the fancy eyes of vertebrates with their sophisticated lenses are the last in a long list of gradual improvements. Long before our ancestors started co-opting nonclumping metabolic proteins, their ancestors, like some worms and starfish, were using flat patches of light-sensitive cells that were at least good enough to find a shadow to cower in and hide from predators. After millions of years, these cells eventually congregated in shallow bowls, eyecups that can detect light’s direction better, which deepened into pit eyes that can detect it very well, and even further into pinhole cameras whose tiny openings can produce real images. From there it was one more step to lenses, transparent tissues of higher density that—thanks to crystallins—could focus light. Eventually these lenses became able to flex or move to create sharp images.

  All these small, gradual improvements are worth preserving, and natural selection did. We know, because many animals still have them: eyecups in some flatworms, pit eyes in some snails, pinhole camera eyes in the nautilus—a relative of squids that builds many-chambered shells—and simple lenses in organisms as primitive as jellyfish.23

  It’s a bit like the stunning grandeur of medieval cathedrals, with soaring spires, columns of heavy massive stones assembled with exquisite precision, and vaulted ceilings so high that our gaze gets lost in their semidarkness. The finished product—like the human eye—is literally incredible without the knowledge that it was built one brick at a time.

  The same is true for all molecular innovations. The amino acid text of the Arctic cod’s antifreeze proteins didn’t originate in a single step, like Athena springing from the brow of Zeus. But every single letter of an ancestor’s amino acid text that changed in the right direction, lowering a body fluid’s freezing point by as little as a tenth of a degree, could expand its descendants’ habitat by miles. A greater range means a larger and more varied food supply. It means a change well worth preserving, and a long sequence of such tiny changes can expand life’s frigid frontier by long distances. Genotype networks are crucial to find each such change, and natural selection is crucial to preserve it.

  Better variants that improve an organism incrementally are important for innovation, but they are not the only kind of change that DNA experiences. 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.

  That neutral changes could matter for innovation—and why—was not always clear. In fact, the relationship between natural selection and neutral change was central to a historical controversy that tore at the fabric of Darwinism in the last third of the twentieth century. The revolution in molecular biology, then well under way, had revealed that populations of wild organisms, from mammals to fruit flies and down to bacteria, harbored astonishing amounts of genetic variation: The DNA of thousands of genes in members of the same species varied in its letter se
quence. Most scientists, good Darwinians as they were, believed that the fate of most of these variants was determined by natural selection—variants that appeared frequently must improve survival or reproduction.

  But these selectionists were opposed by a vocal minority, the neutralists, who argued that most of these variants make no difference to the organism and are invisible to selection. At least when they first appear, they are neutral. In the eyes of some, like the paleontologist Stephen Jay Gould, the very existence of neutral change compromised the importance of natural selection in evolutionary innovation.24

  The history of science and technology offers loose analogies for how neutral changes—dormant discoveries—can become valuable for future innovations. Number theory provides one such analogy. It is a branch of mathematics about which the American mathematician Leonard Dickson reportedly said, “Thank God that number theory is unsullied by any application.”25 This was as true in 1919 as it had been since Euclid, but within decades unrelated developments—digital computers and networked communication between them—placed the theorems of number theory at center stage of the Internet economy, where they ensure the secure communications that make e-commerce and online banking possible. 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. He reportedly said that it was “of no use whatever” and “just an experiment that proves Maestro Maxwell was right.” Less than forty years later, his discoveries led to the first commercially licensed radio station in the world—KDKA in Pittsburgh, which still broadcasts on the frequency band of 1020 kilohertz.26