DOI: 10.5061/dryad.c867b
title: Data from: Temporal variation in antibiotic environments slows down resistance evolution in pathogenic Pseudomonas aeruginosa

description: Antibiotic resistance is a growing concern to public health. New treatment
 strategies may alleviate the situation by slowing down the evolution of
 resistance. Here, we evaluated sequential treatment protocols using two
 fully independent laboratory-controlled evolution experiments with the
 human pathogen Pseudomonas aeruginosa PA14 and two pairs of clinically
 relevant antibiotics (doripenem/ciprofloxacin and cefsulodin/gentamicin).
 Our results consistently show that the sequential application of two
 antibiotics decelerates resistance evolution relative to monotherapy.
 Sequential treatment enhanced population extinction although we applied
 antibiotics at sub-lethal dosage. In both experiments, we identified an
 order-effect of the antibiotics used in the sequential protocol, leading
 to significant variation in the long-term efficacy of the tested
 protocols. These variations appear to be caused by asymmetric evolutionary
 constraints, whereby adaptation to one drug slowed down adaptation to the
 other drug, but not vice versa. An understanding of such asymmetric
 constraints may help future development of evolutionary robust treatments
 against infectious disease.
description: Data for dose response
 curvesThis file contains the
 data for the dose-response curves as shown in supplementary Fig. S2 of the
 paper. The columns indicate the following: $date: the data was collected
 on two days; $treatment: specifies antibiotic treatment; $ID: a number
 from "0" to "10" that serves as ID for the ascending
 antibiotic concentrations; $conc_ng_ml: concentration of antibiotic in
 ng/ml; $replicate: name of technical replicate; $od_600: optical density
 at 600 nm read after 12h of incubation at 37°C.Data_Roemhild_2015a.csvData for both evolution experimentsThis file contains the data from the two evolution experiments, as summarized in Figs. 1,2,3,5,S3,S5, and S6 of the paper. The columns show the following: $well: position of population in 96-well plate; $season: number of transfers within the evolution experiment; $time: time point of od measurement in hours; od was measured in 15 min intervals; $od_600: optical density at 600 nm; $ID: a number from "1" to "10" that serves as ID for treatment groups as specified in the paper plus "11" for the evolving nodrug references; $treatment: treatment type, including monotherapy (mono), regular changes of antibiotics (regular), and random changes of antibiotics (random); $drug: antibiotic used; $exp: number of evolution experiment.Data2_Roemhild_2015a.csvData for cross-resistance testThis file contains the data for the cross-resistance test (Fig. 4). $evoexp: number of evolution experiment or the ancestral population $evoexp_season: season of the evolution experiment after which populations were streaked on agar plates for characterization $evoexp_drug: antibiotic present in $evoexp_season and on the agar plates $evoexp_well: position of population in 96-well plate during evolution experiment $clone_id: name of the five cfus that were isolated from each $evoexp_well $test_drug: antibiotic present in the cross-resistance test $ic: the inhibitory concentration aimed for with the applied concentration; if the value is "E" these are wells with antibiotic but without the bacteria $concentration_ng_ml: concentration of the antibiotic in the cross-resistance test in ng/ml $od_600: optical density at 600 nm after 12h of incubation at 37°CDatafile3_Roemhild_2015_Corrigendum.txt