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Quantifying the Determinants of Evolutionary Dynamics Leading to Drug Resistance

Fig 4

Resistance variability affects the dynamics of evolutionary adaptation to drugs.

(A) Simulation results from a theoretical model of resistance evolution in a morbidostat [11]: IC50 increase over time for a drug with narrow DEC and two available large-effect mutations (magenta) or none (gray); light lines are sample runs; dark lines are mean of 200 runs; inset: distribution of relative IC50 changes used in simulations (Materials and Methods). (B) Same as in panel A for wider DEC (Materials and Methods). (C, D) Results from morbidostat laboratory evolution experiments: IC50 increase over time for nitrofurantoin (C) and chloramphenicol (D); light lines are individual runs; dark lines are mean, error bars standard deviation; shaded region in C indicates early phase during which large-effect mutations fix (Materials and Methods). (E) Mutated loci in nitrofurantoin (left) and chloramphenicol (right)-resistant clones after 10 and 21 d, respectively. Filled pie segments show evolution replicates in which genes were mutated; (P) indicates promoter mutations. Bar chart shows diversity (entropy) of mutations under nitrofurantoin (magenta) and chloramphenicol (gray); p < 0.002 (**) and p < 0.0003 (***) from two-sample t test; error bars show jackknife standard error (Materials and Methods). Numerical data is in S1 Data. Whole genome sequencing results are in S2 Table and S3 Table.

Fig 4

doi: https://doi.org/10.1371/journal.pbio.1002299.g004