How mutation spectra reversals increase the odds of evolutionary success
The evolutionary gamble for mutations is rife with biased roulette wheels. Different types of mutations occur at random but at different rates. While no specific type is inherently ‘good’ or ‘bad’ for the organism, recent evidence shows that reversals of the prevalent bias might have evolutionary benefits.
The frequency with which different types of mutations occur, or the mutation spectrum, is characteristic of all life forms. It can look vastly different depending on the physical and chemical conditions inside the cell, as well as the activities of the molecular machinery meant for DNA repair. For example, some strains of bacteria witness more transitions – mutations where one nucleotide is replaced by another of a similar ring structure. Others have more transversions – when the exchange is between nucleotides of dissimilar ring structures. On their own, such biases should have nothing to do with how often an organism encounters a ‘good’ or beneficial mutation that helps it adapt to its environment.
But an unexpected discovery was made in Dr Deepa Agashe’s lab (Adaptation Lab) at the National Centre for Biological Sciences, India. Her graduate student, Dr. Mrudula Sane, was assessing the impact of different mutations in lab-grown strains of the gut bacterium E. coli, and found that beneficial mutations occurred much more frequently in a strain that was genetically engineered to change its mutation spectrum.
“We didn't expect to see such a big difference,” says Agashe. The difference persisted even after correcting for an experimental artifact that leads to an overestimation of the number of beneficial mutations (https://news.ncbs.res.in/research/peek-boo-i-saw-you). “It didn't make sense.”
Agashe’s collaborator, Dr. Lindi Wahl from Western University, Canada, conjectured that this phenomenon might not be specific to the engineered strain of bacteria or its mutation spectrum, but could be a result of the change in the spectrum. She conducted simulations that confirmed her hunch – a reduction or reversal of the starting mutation spectrum bias always led to an increased fraction of beneficial mutations.
“When you've had the same kinds of mutations for a while, you've used up the good ones and everything that you're looking at is the bad ones. If you mix it up, the ratio of the good ones to the bad ones changes,” explains Dr. Joanna Masel from the University of Arizona, USA, who was not involved in the study. “That's just a compelling idea.”
Here's an analogy to elucidate the concept. Like a kid putting their favorite candies in their pocket and others back in the store racks, populations evolve by retaining good mutations and discarding the bad ones. A population evolving with a certain preference for specific mutation types faces a gradually declining pool of good mutations that haven’t already been retained. The kid’s predicament of having fewer favorite candies to choose from can be solved by taking them to a different store with a new candy collection. Changing the mutation spectrum can achieve something similar by increasing the chances of occurrence of previously under-represented mutation types.
A prediction following the above hypothesis is that reversals in mutation spectra biases are frequent events. To see if that is indeed the case, Agashe’s team zoomed into a part of the tree of life that reflects the evolutionary history of more than a thousand bacterial species. They looked for changes in the genes for DNA repair enzymes – key regulators of mutation biases – and discovered that bacterial species have undergone gains and losses of these genes at rates higher than what would be expected by chance. As guessed, in 80% of these cases, the prevalent spectrum bias was found to have changed in the opposite direction.
For Masel, it had always been a puzzle as to why different species vary so much in their nucleotide usage and why it changes so rapidly over time. She now has an explanation. “It may not be the final word, but it's no longer a mystery.”
Agashe is most excited about how far-reaching the implications can be. Though the experiments were done with bacteria, the simulations tested diverse enough conditions to suggest that this idea is applicable to other systems as well. Further experiments and analyses of natural populations would confirm this.
The implications need not even be confined to mutations. “We expect it to apply in all kinds of scenarios and not just sampling of mutational space but say, for sampling of ideas,” says Agashe. Advice to think ‘outside the box’ might be more than motivational trickery afterall.