Experimental evidence that network topology can accelerate the spread of beneficial mutations.

Whether and how the spatial arrangement of a population influences adaptive evolution has puzzled evolutionary biologists. Theoretical models make conflicting predictions about the probability that a beneficial mutation will become fixed in a population for certain topologies like stars, in which "leaf" populations are connected through a central "hub." To date, these predictions have not been evaluated under realistic experimental conditions. Here, we test the prediction that topology can change the dynamics of fixation both in vitro and in silico by tracking the frequency of a beneficial mutant under positive selection as it spreads through networks of different topologies. Our results provide empirical support that meta-population topology can increase the likelihood that a beneficial mutation spreads, broaden the conditions under which this phenomenon is thought to occur, and points the way toward using network topology to amplify the effects of weakly favored mutations under directed evolution in industrial applications. Lay Summary: Most natural populations are spatially structured, meaning that they are geographically subdivided and connected by migration. Whether spatial structure impacts adaptive evolution has been less clear as different theoretical approaches to modeling the spread of beneficial mutations through spatially structured populations make contrasting predictions. Our work uses evolution experiments and numerical simulations to show that spatial structure can impact the pace of adaptive evolution. Certain topologies, specifically a four-patch star with bidirectional migration through a central hub to each of three "leaf" populations, can accelerate the rate at which a beneficial mutation spreads through a population relative to an unstructured, well-mixed population. The cause of this acceleration is a reduced probability that beneficial mutations are stochastically lost when rare because they get concentrated in the central hub and then disperse outwards to the leaves. Our results offer the first experimental support for models of adaptive evolution in space based on evolutionary graph theory, may help understand the spread of invasive species or pathogens, and could be used in industrial settings to selectively enrich desired traits or biomolecules of interest. [ABSTRACT FROM AUTHOR]