Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness.
The effect of a mutation depends on its interaction with the genetic background in which it is assessed. Studies in experimental systems have demonstrated that such interactions are common among beneficial mutations and often follow a pattern consistent with declining evolvability of more fit genotypes. However, these studies generally examine the consequences of interactions between a small number of focal mutations. It is not clear, therefore, that findings can be extrapolated to natural populations, where new mutations may be transferred between genetically divergent backgrounds. We build on work that examined interactions between four beneficial mutations selected in a laboratory-evolved population of Escherichia coli to test how they interact with the genomes of diverse natural isolates of the same species. We find that the fitness effect of transferred mutations depends weakly on the genetic and ecological similarity of recipient strains relative to the donor strain in which the mutations were selected. By contrast, mutation effects were strongly inversely correlated to the initial fitness of the recipient strain. That is, there was a pattern of diminishing returns whereby fit strains benefited proportionally less from an added mutation. Our results strengthen the view that the fitness of a strain can be a major determinant of its ability to adapt. They also support a role for barriers of transmission, rather than differential selection of transferred DNA, as an explanation of observed phylogenetically determined patterns of restricted recombination among E. coli strains.
Department of Biology and Biochemistry, University of Houston, Houston, TX 77204;
Yinhua
Y
Wang
Department of Biology and Biochemistry, University of Houston, Houston, TX 77204;
Carolina
C
Diaz Arenas
Department of Biology and Biochemistry, University of Houston, Houston, TX 77204;
Daniel M
DM
Stoebel
Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH 03824;
Kenneth
K
Flynn
Department of Biology, University of Akron, Akron, OH 44325;
Ethan
E
Knapp
Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH 03824;
Marcus M
MM
Dillon
Department of Biology and Biochemistry, University of Houston, Houston, TX 77204;
Andrea
A
Wünsche
Department of Computer Science, University of New Hampshire, Durham, NH 03824;
Philip J
PJ
Hatcher
Department of Biology, University of Akron, Akron, OH 44325;
Francisco B-G
FB
Moore
Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH 03824; Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, PA 15219.
Vaughn S
VS
Cooper
Department of Biology and Biochemistry, University of Houston, Houston, TX 77204; tfcooper@uh.edu.
Tim F
TF
Cooper
D003198:Computer Simulation; D017753:Ecosystem; D004843:Epistasis, Genetic; D004926:Escherichia coli / Q000145:classification / Q000235:genetics*; D059647:Gene-Environment Interaction; D056084:Genetic Fitness / Q000235:genetics*; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics*; D018570:Risk Assessment / Q000379:methods; D012641:Selection, Genetic / Q000235:genetics*
beneficial mutations; epistasis; horizontal gene transfer; mutation-by-genetic background interactions