Publications

Selected Publications

Beneficial Synonymous Mutations

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Conventional wisdom holds that synonymous mutations, nucleotide changes that do not alter the encoded amino acid, have no detectable effect on phenotype or fitness. However, a growing body of evidence from both comparative and experimental studies suggests otherwise. Synonymous mutations have been shown to impact gene expression, protein folding and fitness, however, direct evidence that they can be positively selected, and so contribute to adaptation, is lacking. Here we report the recovery of two beneficial synonymous single base pair changes that arose spontaneously and independently in an experimentally evolved population of Pseudomonas fluorescens. We show experimentally that these mutations increase fitness by an amount comparable to non-synonymous mutations and that the fitness increases stem from increased gene expression. These results provide unequivocal evidence that synonymous mutations can drive adaptive evolution and suggest that this class of mutation may be underappreciated as a cause of adaptation and evolutionary dynamics.

Network Topology

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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.

De Novo Evolution of Interactions

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Ecological interactions are crucial to the structure and function of biological communities, but we lack a causal understanding of the forces shaping their emergence during evolutionary diversification. Here we provide a conceptual framework linking different modes of diversification (e.g., ecological diversification), which depend on environmental characteristics, to the evolution of different forms of ecological interactions (e.g., resource partitioning) in asexual lineages. We tested the framework by examining the net interactions in communities of Pseudomonas aeruginosa produced via experimental evolution in nutritionally simple (SIM) or complex (COM) environments by contrasting the productivity and competitive fitness of whole evolved communities relative to their component isolates. As expected, we found that nutritional complexity drove the evolution of communities with net positive interactions whereas SIM communities had similar performance as their component isolates. A follow-up experiment revealed that high fitness in two COM communities was driven by rare variants (frequency <0.1%) that antagonized PA14, the ancestral strain and common competitor used in fitness assays. Our study suggests that the evolution of de novo ecological interactions in asexual lineages is predictable at a broad scale from environmental conditions. Further, our work demonstrates that rare variants can disproportionately impact the function of relatively simple microbial communities.