  In nature, most microbial populations have complex spatial structures that
can affect their evolution. Evolutionary graph theory predicts that some
spatial structures modelled by placing individuals on the nodes of a graph
affect the probability that a mutant will fix. Evolution experiments are
beginning to explicitly address the impact of graph structures on mutant
fixation. However, the assumptions of evolutionary graph theory differ from the
conditions of modern evolution experiments, making the comparison between
theory and experiment challenging. Here, we aim to bridge this gap. We use our
new model of spatially structured populations with well-mixed demes at the
nodes of a graph, which allows asymmetric migrations, can handle large
populations, and explicitly models serial passage events with migrations, thus
closely mimicking experimental conditions. We analyze recent experiments in
this light. We suggest useful parameter regimes for future experiments, and we
make quantitative predictions for these experiments. In particular, we propose
experiments to directly test our recent prediction that the star graph with
asymmetric migrations suppresses natural selection and can accelerate mutant
fixation or extinction, compared to a well-mixed population.
