Selection in a growing colony biases results of mutation accumulation experiments

Abstract

Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments can be performed with different effective population sizes. In MA experiments with bacteria, a single founder is grown to a size of a colony (~ 108). It is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth. In this work, we simulate colony growth via a mathematical model, and use our model to mimic an MA experiment. We demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over-represented by a factor of almost two, and that the distribution of fitness effects of beneficial and deleterious mutations are inaccurately captured in an MA experiment. Given this, the estimate of mutation rates from MA experiments is non-trivial. We then perform an MA experiment with 160 lines of E. coli, and show that due to the effect of selection in a growing colony, the size and sector of a colony from which the experiment is propagated impacts the results. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.

A fitness trade-off explains the early fate of yeast aneuploids with chromosome gains

“…In particular, our quantitative expression for the fitness cost of aneuploid individuals (see Fig. 3 and and Eq.4) could be use to account for fitness effects in MA setups and correct the estimate of the missegregation rate [64,65].…”

“…Moreover, our modeling framework could be deployed to design and investigate Mutation Accumulation (MA) experiments aimed at measuring the mis-segragation rate. In particular, our quantitative expression for the fitness cost of aneuploid individuals (see Fig.3 and and Eq.4) could be use to account for fitness effects in MA setups and correct the estimate of the missegregation rate [64, 65].…”

The mutational landscape ofBacillus subtilisconditional hypermutators shows how proofreading skews DNA polymerase error rates

“…This finding echoes previous studies reporting changes in mutation rates in mutation-accumulation experiments (Perfeito et al 2014; Singh et al 2017). Indeed, recent studies have concluded that positive selection is possible in mutation-accumulation experiments despite the extreme bottlenecks imposed on the population (Mahilkar et al 2022; Wahl and Agashe 2022). Here, the over-representation of mutations in the genetic elements that confer the strongest hypermutator phenotypes indicates adaptive evolution through positive selection to reduce the mutation rate.…”

Consideration of a Liquid mutation-accumulation Experiment to Measure Mutation Rates by Successive Serial Dilution

“…Depending on how a researcher picks and spreads their colonies, edge effects may skew cell division estimates, as some parts of a colony experience more divisions than others [26]. Though single-cell bottlenecks are expected to overwhelm any but the most stringent selection (lethality), the harmonic mean effective population size is closer to 14 than 1 [25,16]; Several authors propose selection is a significant factor in a generic MA experiment, either throughout or in at least the first two weeks [2]. Colony choice instigated by researchers during serial bottlenecking is also at risk of researcher bias, in that humans tend to pick the colonies they can see, rather than just any colony.…”