DOI: 10.5061/dryad.dncjsxm06
title: Experimental data for Pseudomonas aeruginosa from experimental evolution under different bottleneck sizes and antibiotic selection pressures

description: We here combined evolution experiments with genomic and genetic analyses
 to assess whether bottleneck size and antibiotic-induced selection
 influences the evolutionary path to resistance in pathogenic Pseudomonas
 aeruginosa, one of the most problematic opportunistic human pathogens. Two
 sets of evolution experiments were performed across 16 transfers, in which
 either the aminoglycoside gentamicin or the fluoroquinolone ciprofloxacin
 were used as antibiotic. The evolutionary response was studied using
 counts of bacterial cells at the end of each transfer period (i.e., yield)
 or by calculating the growth rate from regular optical density measurement
 during the respective transfer periods. For the populations at the end of
 the evolution experiments, we also determined their antibiotic resistance
 with the help of standardized dose response curves. Moreover, we performed
 whole genome sequencing to assess the frequency of variants, which emerged
 and spread during the evolution experiments. We further focused on
 variants in two specific genes, which were selectively favoured in the
 gentamicin evolution experiments, and assessed their relative fitness
 using competition experiments. We found that antibiotic resistance is
 favoured under high antibiotic selection and weak bottlenecks, but also
 under low antibiotic selection and severe bottlenecks. We found that the
 absence of high resistance under low selection and weak bottlenecks is
 caused by the spread of low-resistance variants with high competitive
 fitness under these conditions. We conclude that bottlenecks in
 combination with drug-induced selection are currently neglected key
 determinants of pathogen evolution and antibiotic treatment outcome.
description: <strong>Material:</strong><br> All experiments
 were performed with Pseudomonas aeruginosa strain PA14 and mutants
 thereof, which arose during the evolution experiments. Bacteria were grown
 in M9 minimal medium, consisting of 7 g/l K2HPO4, 2 g/l KH2PO4, 0.588 g/l
 Na3C6H5O7, 1 g/l (NH4)2SO4, 0.1 g/l MgSO4, and supplemented with 2 g/l
 glucose and 1 g/l casamino acids. Different single colonies from M9 agar
 plates (M9 supplemented with 15 g/l agar) were picked to initiate the
 independent replicate populations of the evolution experiments.
 Exponential phase cultures with an optical density (OD) of 0.1 (equivalent
 to 104-105 CFU/ml) were used as inoculum for resistance assays.
 <br> <strong>Flow cytometry:</strong><br>
 A Guava easyCyte flow cytometer was used to assess cell counts of
 bacterial cultures during the evolution and competition experiments. Cells
 were suspended at an appropriate concentration (&lt; 1500 cells/µl) in
 phosphate buffered saline (PBS) and subjected to flow cytometry using a
 flow rate of 0.236 µl/s for either 30 seconds or until a total cell count
 of 5000 cells per sample was reached. 1.9 mM propidium iodide was used to
 stain dead cells and thus to determine the number of viable cells during
 flow cytometry. For each culture, the total number of cells was calculated
 from the measured cell concentration, adjusted by the number of dead
 cells, sampling volume, and dilution factor. These calculations were used
 to determine the transfer volume during the evolution experiment and to
 infer final yield at the end of each season as a proxy for bacterial
 fitness. <br> <strong>Dose-response curves
 and IC determination for the ancestral
 populations:</strong><br> We used dose-response curves in
 broth cultures and OD measurements as a proxy for bacterial growth in
 consistency with standard diagnostic approaches for antibiotic resistance
 measurements (e.g., the Vitek 2 approach, bioMérieux Ltd). Bacterial
 growth was assessed in 100 µl volumes at ten different antibiotic
 concentrations in a 96-well plate using a fully randomized design,
 including eight technical replicates per concentration, eight no-drug
 controls and eight medium-only controls. Growth was measured as OD after
 12 hours at 37 °C under constant shaking (double-orbital, 900 rpm) in
 Tecan plate readers. The lowest antibiotic concentration for which no
 visible growth was optically measurable was taken as the drug’s
 MIC. <br> <strong>Design and general setup
 of evolution experiments:</strong><br> We developed a novel
 protocol for experimental evolution that includes cell counting by flow
 cytometry, to ensure that an exact number of cells are transferred across
 growth periods. The evolution experiment was run in 96-well plates over 16
 growth periods and included two distinct transfer bottleneck sizes (BN of
 50,000 cells and 5,000,000 cells) and three inhibitory antibiotic
 concentrations (IC0, IC20, IC80), combined in a full factorial design. The
 evolution treatments were randomized across the 96-well plates using a
 block design and each included eight fully independent replicates.
 Experimental evolution was performed independently with two distinct
 antibiotics, the aminoglycoside gentamicin and the fluoroquinolone
 ciprofloxacin.<br> In detail, after each growth period, a 4 µl
 subsample of each bacterial culture was diluted 1:1000 in PBS in two steps
 in a new 96-well plate and then used to determine the exact cell count by
 flow cytometry (see above protocol). In parallel, the remainder of the
 bacterial culture was centrifuged at 5000 rpm for 75 minutes to remove the
 old growth medium and resuspended in fresh M9 medium. The resuspension
 volumes were calculated individually, based on the flow cytometry results.
 Resuspension volumes were set to achieve a concentration of 5 x 105
 cells/?l per culture. The plate for the next growth period was prepared
 accordingly (100 ?l per well minus the calculated transfer volume) and the
 respective volumes were then transferred to the new plate: 0.1 ?l for
 50,000 cells and 10 ?l for 5,000,000 cells. The freshly inoculated plate
 was sealed with transparent foil and incubated for 9.5 h in a Tecan plate
 reader at 37 °C under constant shaking (double-orbital, 900 rpm). OD
 measurements were taken in 15-minutes intervals throughout each growth
 period of the evolution experiments and later used for inference of growth
 rates. <br> <strong>Assessment of bacterial
 fitness:</strong><br> We calculated two proxies of bacterial
 fitness during the evolution experiment. On the one hand, we used the
 absolute cell counts, determined with flow cytometry at the end of each
 growth period, to infer final yield for each growth period and replicate
 population, followed by calculation of relative yield by dividing the cell
 counts for each replicate population with that for the corresponding
 no-drug control (either IC0-k50 for strong bottleneck treatments or IC0-M5
 for weak bottleneck treatments). This data is provided in
 Mahrt_etal_Data_1.csv.<br> On the other hand, we also used the
 continuous OD measurements to calculate growth rate for each growth period
 and each replicate population. This data is provided in
 Mahrt_etal_Data_2.csv. <br>
 <strong>Antibiotic resistance of evolved
 populations:</strong><br> Populations of the last transfer
 period were challenged against different antibiotic concentrations of the
 treatment drug, to obtain dose-response curves for the evolved populations
 (see above protocol). For this assessment, all cultures were standardized
 to the same population size of 500,000 cells. All bacterial populations
 were consistently subjected to eight distinct antibiotic concentrations:
 two below (IC50, IC80) and six above the MIC (2xMIC, 4xMIC, 8xMIC and
 16xMIC) of the ancestral population. We specifically chose this design to
 ensure comparability of the experimental procedures for the evolved
 populations. Control measurements were done in the absence of antibiotics.
 After 12 h growth, endpoint ODs were obtained for all concentrations. This
 data is provided in the file Mahrt_etal_Data_3.csv.
 <br> <strong>Variant frequencies during the evolution
 experiment:</strong><br> We performed whole genome sequencing
 of entire populations. DNA was isolated from experimentally evolved
 populations and the original starting cultures. WGS of DNA samples of the
 last transfer period was performed at the Competence Centre for Genomic
 Analysis (CCGA) Kiel, Germany. Sequencing libraries were generated with
 the Nextera DNA Flex library preparation kit and sequencing was performed
 on the Illumina HiSeq 4000 platform using the Illumina paired-end
 technology with read lengths of 150 bp and an average base coverage of
 &gt;100. In addition, DNA extracted from transfers 3, 5, 7, 9, 11 and
 13 were sequenced on the Illumina NextSeq platform at the Max Planck
 Institute for Evolutionary Biology (MPI-EB) in Plön, Germany, with read
 lengths of 150 bp and an average base coverage of &gt;40. Sequence
 reads were provided in the fastq format. We excluded populations IC20-M5
 H2 and IC80-M5 G7 from the GEN experiment, because material from some
 transfers could not be recovered. Quality and quantity of reads were
 checked with FastQC. Trimmomatic was used to remove sequencing adapters
 from the Nextera library and to filter out low quality reads. High quality
 reads were mapped to the UCBPP_PA14 reference genome with the software
 bwa. The generated .bam files were scanned for SNPs, insertions and
 deletions using the variant calling programs FreeBayes, PinDel and
 VarScan. The resulting output files were filtered for duplicates,
 ancestral variants, and variants found in the evolved controls using R and
 additionally checked by visually inspecting the called genome positions
 provided by the .bam file in the IGV genome browser. The detected variants
 were annotated with the help of SnpEff and the Pseudomonas database
 (available at http://pseudomonas.com). The variant frequencies for
 transfer periods 3 and 16 is provided in the file Mahrt_etal_Data_4.csv
 and the variant frequencies from across the evolution experiments in the
 file Mahrt_etal_Data_5.csv. <br>
 <strong>Antibiotic resistance of selected
 variants:</strong><br> We used the antibiotic resistance data
 obtained above for selected populations, which had a high abundance of
 variants in either the gene pmrB or the gene ptsP, in order to compare
 variation in resistance associated with the two genes. The antibiotic
 resistance data for this comparison is provided in the file
 Mahrt_etal_Data_6.csv. <br>
 <strong>Competition assays and clone frequency analysis using
 amplicon sequencing:</strong><br> In total, three pairs of
 different pmrB and ptsP mutants were competed against one another and
 against the PA14 reference in 96-well plates. As a control, each single
 strain was incubated in individual wells under the same conditions on a
 separate 96-well plate. The used clones were picked as a single CFU from
 M9 agar plates, which had been inoculated with a cryo-preserved culture of
 an evolved bacterial population, which should contain only a single
 variant according to the performed WGS of bacterial populations. The
 picked clones were cultivated in 5 ml M9-medium at 37 °C. Cultures of
 competing strains were set to an OD of 0.1 mixed at a 1:1 ratio before
 inoculation of the competition cultures. The cultures were then
 transferred to 96-well plates. Competitions ran with culture volumes of
 100 µl at different gentamicin concentrations for 12 hours at 37 °C in a
 Tecan plate reader. The relative frequency of the competing strains was
 determined using amplification of diagnostic genome regions and their
 subsequent sequencing. Bacterial pellets from the end of the competition
 experiments were resuspended in 50 ?l nuclease-free water and boiled for
 15 minutes. A two-step PCR was subsequently performed to amplify the
 region of interest and to ligate barcodes to the amplicons, followed by
 sequencing on the Illumina NextSeq platform of the MPI-EB. The mean
 frequencies of every replicate were calculated and is provided in the file
 Mahrt_etal_Data_7.csv.