DOI: 10.5061/dryad.g41hg96
title: Data from: Historical contingency in the evolution of antibiotic resistance after decades of relaxed selection

description: Populations often encounter changed environments that remove selection for
 the maintenance of particular phenotypic traits. The resulting genetic
 decay of those traits under relaxed selection reduces an organism’s
 fitness in its prior environment. However, whether and how such decay
 alters the subsequent evolvability of a population upon restoration of
 selection for a previously diminished trait is not well understood. We
 addressed this question using Escherichia coli strains from the long-term
 evolution experiment (LTEE) that independently evolved for multiple
 decades in the absence of antibiotics. We first confirmed that these
 derived strains are typically more sensitive to various antibiotics than
 their common ancestor. We then subjected the ancestral and derived strains
 to various concentrations of these drugs to examine their potential to
 evolve increased resistance. We found that evolvability was idiosyncratic
 with respect to initial genotype; that is, the derived strains did not
 generally compensate for their greater susceptibility by “catching up” to
 the resistance level of the ancestor. Instead, the capacity to evolve
 increased resistance was constrained in some backgrounds, implying that
 evolvability depended upon prior mutations in a historically contingent
 fashion. We further subjected a time-series of clones from one LTEE
 population to tetracycline and determined that an evolutionary constraint
 arose early in that population, corroborating the role of contingency. In
 summary, relaxed selection not only can drive populations to increased
 antibiotic susceptibility, but it can also affect the subsequent
 evolvability of antibiotic resistance in an unpredictable manner. This
 conclusion has potential implications for public health, and it
 underscores the need to consider the genetic context of pathogens when
 designing drug-treatment strategies.
description: <strong>The data package
 associated with the paper "Historical contingency in the evolution of
 antibiotic resistance after decades of relaxed selection" contains
 two zip folders:</strong><br> <br> <br>
 <strong>1.  Card et al. (2019) - Data and R
 notebook</strong><br> <br> <br>
 <b>File:  Historical contingency in the evolution of ABR.Rmd (and
 .html)</b> This R
 notebook contains code to analyze all data and generate all figures
 associated with the paper. A .html file is also included for convienence
 so one may examine the analysis outputs without running the
 code. <br>   <strong>Folder: 
 Figures</strong> This folder contains Figs 2, 3, and
 4 that output from the R Notebook.<br>   <b>File:  MICs of LTEE ancestral
 and derived strains.csv</b> This is the data file for the minimum
 inhibitory concentrations (MICs) of various antibiotics on the LTEE
 ancestor and derived clones isolated from generation 50,000 populations,
 and their resistant mutant derivatives. <br> <b>File:  MICs of
 strains from Ara+5 population.csv</b> This is the data file for the minimum
 inhibitory concentrations (MICs) of tetracycline on the LTEE ancestor and
 derived clones isolated from the Ara+5 population, and their resistant
 mutant derivatives.<br>   <b>File:  Cell
 counts.csv</b> This is the data file for the estimated
 cell yields among twelve replicate populations of the LTEE ancestor and a
 derived clone isolated from the Ara+5 population after 2,000
 generations.<br>   <b>File:  Mutant colony
 counts.csv</b> This is the data file for tetracycline
 resistant mutant colony counts of the LTEE ancestor and a derived
 clone isolated from the Ara+5 population after 2,000
 generations.  
 <strong>2.  Card et
 al. (2019) - Experimental plate photos</strong>
 This zip folder contains photos of
 all experimental plates for our evolvability assays.
description: The data were collected using plate-based evolvability and
 fluctuation assays that are described in detail in the associated
 publication. All of the statistical analyses of experimental data were
 performed using the R software environment (version 3.5.0). The details of
 our statistical analyses are provided in the associated R Notebook titled
 "Historical contingency in the evolution of ABR". This Notebook
 was written using RStudio (version 1.2.1181).