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Destabilizing mutations encode nongenetic variation that drives evolutionary innovation

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Science  30 Mar 2018:
Vol. 359, Issue 6383, pp. 1542-1545
DOI: 10.1126/science.aar1954
  • Fig. 1 Evolutionary innovation through functional bistability.

    (A) Schematic overview of λ evolution. Mutations to improve ancestral receptor binding reduce stability until a critical mutation produces a multifunctional genotype. Further evolution can restabilize the protein. (B) Temperature sensitivity of genotypes with indicated numbers of mutations relative to the ancestor. Some have more than four mutations because λ often evolves additional mutations before achieving OmpF use. The y axis shows the fraction of infectious particles remaining after incubation. Curves are logistic models fit to data from multiple trials; fig. S1 shows all data (12). OmpF+ phages are shown in teal, and LamB-reliant genotypes are shown in black. (C) Temperature sensitivity of the ancestor, an OmpF+ generalist, and the generalist’s specialist descendants. Bars indicate the data range; fig. S2 shows all data.

  • Fig. 2 Decay rate heterogeneity.

    Decay of ancestor (black) or OmpF+ generalist (teal) phage over (A) 18 days or (B) 2 days. Four replicates (pale) and the average (bold) are shown in (A). Individual replicates are shown in (B). (C) Number of phage particles able to form plaques on LamB-only (solid) or OmpF-only (dashed) bacterial lawns after 2 days. Individual replicates are shown. pfu, plaque forming units.

  • Fig. 3 Isolation and properties of λ subpopulations.

    A phage pull-down assay shows the number of phage particles capable of infecting LamB-only (solid) or OmpF-only (dashed) hosts before and after incubation (A) in the presence of OmpF-only cells or (B) alone (in the absence of cells). (C) Adsorption rate to LamB-only cells before or after OmpF innovation; genotypes differ by one mutation. (D) LamB adsorption rate of the entire OmpF+ culture compared with that of the LamB-faithful subpopulation. P values are from paired t tests [(A) and (B)] or standard t tests [(C) and (D)]. h, hours.

  • Fig. 4 The fitness of ensembles of phenotypes.

    (A) Population fitness as a function of phenotypic variance. (B) Example of bivariate normal distribution of phenotypes constrained by a convex Pareto front (19). The variance of the colored points in (A) is the parameter used to calculate corresponding colored outlines in (B). The outlines represent the largest variance at which 50% of the population is contained. Error bars in (A) represent numerical error in estimating the integrals.

  • Destabilizing mutations encode nongenetic variation that drives evolutionary innovation

    Katherine L. Petrie, Nathan D. Palmer, Daniel T. Johnson, Sarah J. Medina, Stephanie J. Yan, Victor Li, Alita R. Burmeister, Justin R. Meyer

    Materials/Methods, Supplementary Text, Tables, Figures, and/or References

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    • Materials and Methods
    • Supplementary Text
    • Figs. S1 to S6
    • Tables S1 to S6
    • References

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