Whether the spatial arrangement of a population influences adaptive evolution has been a long-standing question in population genetics. In contrast to standard population genetic models, evolutionary graph theory (EGT) predicts certain topologies amplify (increase) the probability that a beneficial mutation will spread in the population relative to a well-mixed population. Here, we test these predictions empirically by tracking the fixation dynamics of an antibiotic resistant mutant under positive selection as it spreads through networks of different topologies both in vitro and in silico. We show that star-like topologies involving bi-directional dispersal between a central hub and peripheral leaves can be amplifiers of selection relative to a well-mixed network, consistent with the predictions of EGT. We further show that the mechanism responsible for amplification is the reduced probability that a rare beneficial mutant will be lost due to drift when it encounters a new patch. Our results provide the first empirical support for the prediction of EGT that spatial structure can amplify the spread of a beneficial mutation and broadens the conditions under which this phenomenon is thought to occur. We also show the importance of considering the migration rate, which is not independently adjustable in most previous models. More generally, our work underscores the potential importance of spatial structure in governing adaptive evolution by showing how the interplay between spatial structure and evolutionary forces determine the fate of a beneficial mutation. It also points the way towards using network topology to amplify the effects of weakly favoured mutations under directed evolution in industrial applications.
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Chakraborty, P. P., Nemzer, L. R., & Kassen, R. (2021). Experimental evidence that metapopulation structure can accelerate adaptive evolution. bioRxiv, 1 - 28. https://doi.org/10.1101/2021.07.13.452242. Retrieved from https://nsuworks.nova.edu/cnso_chemphys_facarticles/299