title: A tortoise-hare pattern seen in adapting structured and unstructured populations suggests a rugged fitness landscape in bacteria.
abstract: In the context of Wright's adaptive landscape, genetic epistasis can yield a multipeaked or "rugged" topography. In an unstructured population, a lineage with selective access to multiple peaks is expected to fix rapidly on one, which may not be the highest peak. In a spatially structured population, on the other hand, beneficial mutations take longer to spread. This slowdown allows distant parts of the population to explore the landscape semiindependently. Such a population can simultaneously discover multiple peaks, and the genotype at the highest discovered peak is expected to dominate eventually. Thus, structured populations sacrifice initial speed of adaptation for breadth of search. As in the fable of the tortoise and the hare, the structured population (tortoise) starts relatively slow but eventually surpasses the unstructured population (hare) in average fitness. In contrast, on single-peak landscapes that lack epistasis, all uphill paths converge. Given such "smooth" topography, breadth of search is devalued and a structured population only lags behind an unstructured population in average fitness (ultimately converging). Thus, the tortoise-hare pattern is an indicator of ruggedness. After verifying these predictions in simulated populations where ruggedness is manipulable, we explore average fitness in metapopulations of Escherichia coli. Consistent with a rugged landscape topography, we find a tortoise-hare pattern. Further, we find that structured populations accumulate more mutations, suggesting that distant peaks are higher. This approach can be used to unveil landscape topography in other systems, and we discuss its application for antibiotic resistance, engineering problems, and elements of Wright's shifting balance process.
authors.affiliation: BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824; nahumjos@msu.edu kerrb@uw.edu.
authors.forename: Joshua R
authors.initials: JR
authors.lastname: Nahum
authors.affiliation: Philosophy Program, The Graduate Center, City University of New York, NY 10016; History and Philosophy of Science Unit, University of Sydney, Sydney, NSW 2006, Australia;
authors.forename: Peter
authors.initials: P
authors.lastname: Godfrey-Smith
authors.affiliation: BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824; Department of Biology, University of Washington, Seattle, WA 98195;
authors.forename: Brittany N
authors.initials: BN
authors.lastname: Harding
authors.affiliation: Department of Human Genetics, University of Chicago, Chicago, IL 60637; and.
authors.forename: Joseph H
authors.initials: JH
authors.lastname: Marcus
authors.affiliation: Department of Biomedical Engineering and Wisconsin Institute for Discovery, University of Wisconsin, Madison, WI 53706.
authors.forename: Jared
authors.initials: J
authors.lastname: Carlson-Stevermer
authors.affiliation: BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824; Department of Biology, University of Washington, Seattle, WA 98195; nahumjos@msu.edu kerrb@uw.edu.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Kerr
mesh_terms: D000220:Adaptation, Biological; D019020:Directed Molecular Evolution; D024881:Drug Resistance, Bacterial / Q000235:genetics; D004843:Epistasis, Genetic; D004926:Escherichia coli / Q000235:genetics* / Q000502:physiology*; D019143:Evolution, Molecular; D014644:Genetic Variation; D016680:Genome, Bacterial; D008954:Models, Biological; D009154:Mutation
keywords: NK model; adaptive landscape; experimental evolution; landscape topography; spatial structure