The Day of the Mutators New Scientist 14 February 1998
Martin Brookes in a science writer based in London
YOU don't have to travel far these days to study evolution. In fact you don't even have to venture outdoors. A colony of bacteria growing in a dish of agar should do just fine. Okay, so it might be great fun to seek out exotic species on the GalApagos Islands or in the Amazonian rainforest. But whether you are peering through binoculars at a baboon's backside or staring down a microscope into a piece of over-populated plastic, the fundamentals remain the same. Evolution is nature's way of solving problems. The main problem, of course, for a bacterium or any other organism, is how to survive long enough to reproduce. In the struggle for existence, genetically distinct individuals compete for limited resources. Those that do best produce more offspring and become the major genetic shareholders of the next generation. Random mutations and sexual reproduction shuffle genes to create offspring with new genetic combinations. And every generation, natural selection sifts through the competitors, eliminating combinations that don't work, and adapting organisms to their enviroranents. But what happens if the envirorunent isn't stable, but is constantly changing? How does evolution cope with a moving target? This is a problem that pathogenic bacteria such as Salmonella or Escherichia coli know well. For them, the problems come thick and fast in the form of a vicious molecular bombardment, courtesy of their host's immune system and, sometimes, antibiotic reinforcements. Still, they manage to evolve quickly, on the hoof, to find new genetic solutions. A bad bout of food poisoning is living proof that somehow, for a time, the bacteria have got the better of your defences.
To fuel their evolutionary escapology bacteria rely on random mutations-rare, unforeseeable and uncontrollable mistakes in the process that copies DNA from one generation to the next. Here or there, without planning, the DNA of a gene is copied incorrectly. More often than not, these mutations are harmful rather than beneficial-the biological equivalent of throwing a spanner into the works. With such blind and basic machinery, it is a wonder that bacteria are so flexible and adaptive. And this is the puzzle that is driving biologists to dishes teeming with hundreds of thousands of microbes. By studying their growth and genetic alterations, scientists are beginning to shed light on how bacteria evolve and evade their enen-des so effectively. Oddly, it seems that a bacterium sometimes finds evolutionary success through biochemical failure. Evolution uses some very peculiar tricks when it comes to making organisms that are not only adapted, but adaptable as well. The problem confronting a population of bacteria can be visualised more clearly in a mathematical context than in a strictly biological one. Faced with a changing environment, bacteria need to explore a vast range of alternative genetic solutions. An adaptive landscape is a useful metaphoric tool, often used bv evolutionary theorists to describe this genetic prospecting. Imagine an abstract mathematical space and an undulating surface within it, complete with hius and valleys. The height of any point on the landscape corresponds to the extent to which a given genetic constitution produces an organism well-suited to its environment. Movement on the landscape corresponds to changes in the organism's genes, and the highest peaks represent those combinations which give an organism the highest fitness, as measured by reproductive success. This is, adn-Littedly, a fantastically oversimplified picture. For the possible directions of movement are extremely limited in a three-dimensional landscape. An organism can move north or south, east or west, or anv combination of these directions. But real organisms have a huge number of -enes that can mutate independentlv of one another. And each gives a [email protected] possible direction for change. The bacterium E. coli, for instance, has about 4 000 genes. So the true adaptive landscape for E. coli crawls up and down in a mind-boggling space of 4 000 dimensions. StiR, even in a weird landscape of such high dimension, the basic idea is the same. Fuelled by mutation and driven by natural selection, organisms will tend to march uphill in the landscape toward fitness peaks and, having arrived, stay there. A particular adaptive landscape is fixed as long as an organism's environment doesn't change. But genetic combinations that were favoured in one environment will not necessarily be favoured in another. If their environment changes, a population sitting proudly on a mountain top mav suddenly find itself down in a valley. In order to survive in this new environment, organisms are banking on mutations to inch them towards the top of a new peak on the landscape.
Trouble is, the navigational skills of organisms on an adaptive landscape are limited-they cannot anticipate where they should go. And the mutations that must take them there are random. For a bacterium, the verv next mutation is more likely to cause touble than help. But Richard Moxon, a biologist from the John, Radcliffe Hospital at Oxford University, points out that the randomness of mutations does not imply the lack of any con-, straint. Some genes are much more likely' to mutate than others, and Moxon is convinced that these highly mutable genes are accident prone by design. If you take away radiation and chemical nasties from an organism's environ-' ment, the mutation rate will diminish, but it won't disappear. Mutations are not just the result of insults from outside the cell. They can also come about as a consequence of "honest" mistakes in DNA metabolism. All cells possess a suite of enzymes which maintain the upkeep of the DNA, and ensure that it is faithfully replicated before being passed on to the next generation. For example, proofreading enzymes detect and correct chemical defects in the DNA, and polymerase enzymes catalyse the synthesis of a replica DNA molecule prior to cell division (see Diagram, above). Although these enzymes are efficient, they do make mistakes. Errors may be 'overlooked" or the wrong base may be inserted into a new DNA template. These n-dstakes in DNA metabolism are not distributed uniformly across the genome. They tend to occur again and again at specific 'hypermutable" genes that contain chen-dcal banana skinsrepetitive motifs embedded in their DNA sequence-which increase the chances of genetic shp-ups. Apart from being accident black spots, these genes have something else in common-they code for cell surface proteins. Cell surface proteins are naturally in the front line of the evolutionary war between an invading bacterium and its host. For the host, they are the visible signatures of foreign intruders and the primary targets for its defence mechanisms. To stem the tide of a bacterial infection, molecules produced by the host's immune system must first recognise and lock on to these proteins. In order to deceive the host, bacteria set up novel arrays of targets on their cell surface, which the host's immune system is unable to recognise. To do this requires rapid and frequent changes to the structure and conformation of the cell surface proteins.
Moxon believes that the high mutation rates of genes coding for these proteins has evolved to give bacteria flexibility where it is most needed. 'Hypermutable genes are those which generate useful biological noise at the cell surface," he says. Because mutations are, on average, likely to have detrimental effects, most genes-those which carry out the basic -housekeeping" functions for the ceflare selected to have a low mutation rate. But a hn-dted set of genes, the so-called contingency genes, are selected to have a high mutation rate. This combination of highly mutable contingency genes and more sedate housekeeping genes promotes flexibility where it is most needed, while minin-dsing the risks associated with genetic mutations. "We're dealing with two strategies side by side," says MoxonTo what does this correspond in the adaptive landscape? Any change in a housekeeping gene is catastrophic. So there must be a high and narrow ridge runninge landscape (see Diagram). Changes to housekeeping genes correspond to movement off the edge of the ridge, the precipitous faces of which reflect the high cost of altering crucial elements.
Changes in the hills: a bacterium evolved to a fitness peak (a) may suddenly find itself in a valley (b). Mutations being rare, the next generation would also be stuck nearby (blue). A high mutation rate enables bacteria to evolve rapidly in one generation and to find a new peak (red)
'A mutation in a mutator gene can alter the efficiency of a proofreading enzyme and ultimately lead to mutational mayhem across the genome'
Mutations in contingency genes, on the other hand, correspond to movement along the ridge, which may wander gently up and down. By restricting mutations to the contingency genes, bacteria ensure that mutations don't throw them off the cliff, but still maintain flexibility where they need it. So, the chances of a mutation being beneficial are increased (see "Restricted wandering"). But contingency genes are nbt the only way in which bacteria can optin-dse their genetic prospecting. Last year, so-called mutator genes were discovered in the organism's problem, solving ar-moury. Mutator genes code for the enzvmes involved in DNA metabolism. Their name is appropriate, for a mutation in a mutator gene can alter the efficiency of a proofreading enzyme and ultimately lead to mutational mayhem across the genome. A supermarket provides an analogy. To be successful, your local food emporium depends on ordered efficiency. Products are neatly arranged on their designated shelves by a small army of underpaid workers. The job of the floor manager-the human equivalent of the mutator geneis to check that the shelf-stackers are putting the foodstuffs in the right places. But if the floor m anager develops a fondness for extended liquid lunches, the results could be disastrous. Before too long, baked beans in the wine section and nappies in the frozen foods will send confused and disgruntled shoppers scurrying for the exits.
The point is, of course, that an inefficient caretaker, be it in the form of a mutator gene or a supermarket floor manager, can leave a once ordered system in chaos. "A mutation in a mutator gene was always thought to be bad news for the organism," says Paul Sniegowski, "but weird and surprising stuff turns up when you study bacteria." Sniegowski, a biologist from the University of Pennsylvania, is speaking from experience. He has just spent four long years studying 10 000 generations of bacteria, and believes that "inefficient caretakers" just might have their uses. At the start of the study, Sniegowski and his colleagues set up 12 genetically identical populations of E. coli in an environment lacking a vital nutrient. 'When the populations were started, they weren't adapted to this environxnent, so there was lots of potential for adaptation," says Sniegowski. After 10 000 generations, 3 of the 12 populations had mutation rates that had risen from 0.002 to 0.2 mutations per gene per generation. The mutation rates of the other nine populations remained unchanged. When Sniegowski introduced normal working copies of the mutator gene into the three hypermutable populations, the ancestral mutation rate was restored. This confirmed that the high mutation rate had been caused by a mutation in a mutator gene.
'For an organism facing a wildly fluctuating environment, high mutability of mutator genes could be an adaptation in itself'
How can populations with such high mutation rates survive? The answer may be surprisingly simple. An "inefficient caretaker" will prompt a cascade of mutations throughout the genome. Most wiu be harmful to the organism and threaten its chances of survival. But, by chance, a new mutation might appear whose benefits outweigh the total cost of all the deleterious changes. Or, in one or a few offspring bacteria, just the right combination may occur to produce a bacterium adapted to the new environment. Of course, there is no guarantee that the drastic measure of employing an 'inefficient caretaker" will have the desired effect-the changes could be entirely deleterious. But it does at least make rapid change a possibility. More importantly, it allows the process to be switched on or off with a single mutation. Evidence from outside the lab suggests that most bacteria have low genome-wide mutation rates. But where high mutation rates are found, they tend to be in highly pathogenic species like Salmonella. "I think mutator genes can themselves be thought of as contingency genes," says Moxon. For an organism facing a wildly fluctuating envirorunent, high mutability of mutator genes could be an adaptation in itself. Moxon refers to the genome's mutational machinery as the organism's "tool box" a metaphor which accurately describes its problem-solving role. What's more, he believes that natural selec ' tion is constantly refining the contents of an organism's tool box. "I think this fine tuning is going on all the time," he says, "with contingency genes constantly being recruited and dismissed." A lethal bacterial infection is clearly bad news for the host, but it is not an ideal situation for the bacteria either. The death of a host wifl end any prospect of the bacteria establishing further infections. A fatal outbreak of meningitis is an example where the bacteria responsible have let success go to their head. In these circumstances, natural selection is likely to remove some of the tools from the tool box to reduce the bacterial potency. Conversely, if bacterial survival is suddenly threatened by a barrage of new environmental problems or opportunities, additional tools may be incorporated.
Not so blind watchmaker
It is almost ten years now since John Calms, from the Harvard School of Public Health, wrote, in a highly publicised article in Nature (volume 335, 1988, pp 142-145) that "cells may have mechanisms for choosing which mutations occur'. Cairns believed that organisms might somehow be able to perceive changes in their envirorunent and direct mutations to the most appropriate genes. In other words, Cairns was suggesting that Richard Dawkins's blind watdimaker had suddenly regained his sight. The jury is still out on the so-called directed mutation controversy. Caims's idea did not go down too well with the disciples of Dawkins and Darwin. But more importantly, a feedback mechanism to explain directed mutation has so far proved elusive. Nevertheless, at the time, there was something intuitively attractive about Caims's concept. On the face of it, directed mutation seemed like a much more efficient problem-solving system than random change, and offered a possible explanation for the rapid evolutionary diange obsexved in pathogenic species of bacteria. Moxon's contingency theory is not a million miles away from Cairns's original notion of directed mutation, yet it neither invokes unknown mechanisms or commits Darwinian blasphemy. What's more, Moxon believes that "biased randomness", as he cans it, is a more effident system of evolutionary problem solving than directed mutation. Directed change would restrict navigational flexibility on the adaptive landscape. Populations would always be evolving towards the nearest local pea k, leaving more prominent peaks out of reach. Random change, on the other hand, allows populations to explore genetic solutions over the entire adaptive surface. 'Random genetic variation and natural selection is a far more powerful system of problem solving," says Moxon. Bacteria may be the organisms of choice for Moxon, Sniegowski and others who are fascinated by evolutionary problem solving, but they are by no means the sole proprietors of an evolving tool box. "Contingency genes are characteristic of all organisms," says Moxon. Furthermore, the study of evolutionary problem solving may have important implications for understanding other cases of rapid evolution, such as in HIV and cancer. Many cancers are initiated by a mutation in a mutator gene of a normal cen. The subsequent growth and spread of the cancer is exactly analogous to the growth and spread of pathogenic bacteria inside the host. Says Sniegowski, "We're just at the early stages of this subject, and some pretty exciting things lie ahead."
Contingency genes accelerate an organism's mutational wandering over its adaptive landscape. Imagine a simple case in which an organism has 1000 genes, including five contingency genes. 'A binary switch is a realistic way of describing mutations in these contingency genes,' says Moxon. So each of the contingency genes can exist in one of two alternative states, A or a, B or b, C or c, and so on, with mutations transforming a gene from one state to another. With 5 contingency genes and two alternative states there are 2^5 = 32 possible genetic combinations.
Inside a host, a bacterium with the genetic combination ABcDe gets lucky, finding itself more than capable of counter ing the host's repertoire of immune responses. ABcDe is the Mount Everest of this particular adaptive landscape. Within hours, this single individual has given rise to millions of identical clones, leaving the host in some discomfort. For the host, drastic measures are needed, so it decides to self-administer some antibiotics. The antibiotics induce radical changes in the bacterial population's adaptive landscape. The high est peak collapses to a valley and fresh new peaks rise up around it. Population ABcDe must rapidly evolve to a new peak if it is to survive the antibiotic onslaught. If this new peak corresponds to the genotype AbCDE, for example, then three mutational changes would be required.
Let's assume initially that the mutation rate in the contingency genes is the same as that in the rest of genome-10^-3 per gene per generation. Then, the chance of the three mutational changes occurring in a single individual is 10^-9. This equates to a probability of one in a billion cells. Even for rapidly reproducing bacteria, this remains a pretty remote possibility. But in real life, contingency genes have much 'higher mutation rates. With a mutation rate of 10^-2, the chance of an individual reaching the new adaptive peak in one generation is reduced to only one in a million cells. Although the descendants of any one bacterium are still almost surely doomed, in a population of millions, there is a good chance of a survivor being created.