Data from: Costs of antibiotic resistance genes depend on host strain and environment and can influence community composition
Data files
May 14, 2024 version files 519.51 KB
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ARG_cost_data.csv
254.85 KB
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bla_plasmid_CPN.csv
1.55 KB
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df.full.csv
241.39 KB
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pmFP_cost.csv
13.91 KB
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README.md
7.81 KB
Abstract
Antibiotic resistance genes (ARGs) benefit host bacteria in environments containing corresponding antibiotics, but it is less clear how they are maintained in environments where antibiotic selection is weak or sporadic. In particular, few studies have measured the effect of ARGs on host fitness in the absence of direct selection or determined if any costs are fixed or depend on the host strain, perhaps marking some ARG-host combinations as reservoirs that can maintain ARGs in the absence of antibiotic selection. We quantified the fitness effects of six ARGs in 11 diverse Escherichia spp. strains. Three ARGs (blaTEM-116, cat, and dfrA5, encoding resistance to β-lactams, chloramphenicol, and trimethoprim, respectively) imposed an overall cost but all ARGs had an effect in at least one host strain, reflecting a significant strain interaction effect. A simulation predicts these interactions cause the success of ARGs to depend on available host strains, and, to a lesser extent, for successful host strains to depend on the ARGs present in a community. These results indicate the importance of considering ARG effects over different host strains, especially the potential of reservoir strains that allow resistance to persist in the absence of direct selection, in efforts to understand resistance dynamics.
https://doi.org/10.5061/dryad.6wwpzgn5d
GENERAL INFORMATION
- Title of Dataset: Costs of antibiotic resistance genes depend on host strain and environment and can influence community composition.
- Author Information
Corresponding Investigator 1
Name: Dr Tim F. Cooper
Institution: University of Auckland, Auckland, New Zealand
Email: Tim.cooper@auckland.ac.nz
Co-investigator 1
Name: Dr Huei-Yi Lai
Institution: Massey University, Auckland, New Zealand
3. Date of data collection: 2022-2023
DATA & FILE OVERVIEW
1. Description of dataset
Data was collected to determine: (i) the fitness effect of each of six antibiotic resistance genes (ARG) in each of eleven host strains, (ii) the fitness cost of the ARG empty vector in each host strain, and (iii) the copy number of a blaTEM116* vector.
2. File List:
File 1 Name: ARG_cost_data.csv
File 1 Description: Fitness estimate dataset used for analysis and plotting
File 2 Name: ARG_cost.Rmd
File 2 Description: R Markdown script to process, analyse, and plot fitness data
File 3 Name: pmFP_cost.csv
File 3 Description: Fitness estimates of pmFP empty vector in each tested host strain
File 4 Name: bla_plasmid_CPN.csv
File 4 Name: copy number estimate of the blaTEM116* plasmid
File 5 Name: community_competition.Rmd
File 5 Description: R markdown script to simulate communities consisting of various host strain - ARG combinations
File 6 Name: df.full.csv
File 6 Description: fitness estimates of host strain - ARG combinations used as simulation input
METHODOLOGICAL INFORMATION
To measure the fitness effect of each ARG, we performed a series of competition assays. The fitness effect of an ARG was estimated as the fitness difference between cells carrying an ARG plasmid (WARG) and cells carrying the control pmFP plasmid vector (WVec). The fitness of ARG and vector plasmid-carrying cells was estimated indirectly by competing each against reference cells carrying a GFP expressing plasmid (pUA66-PrpsLGFP).
Cells carrying an ARG plasmid, pmFP, or pUA66-PrpsLGFP, were inoculated in 200 μL of Davis-Mignioli broth supplemented with 250 μg/ml glucose (DM250) and 50 μg/ml kanamycin from frozen stocks and cultured at 37ºC overnight. The overnight cultures were diluted 1:100 in 200 μL of fresh DM250 and incubated for a 24-hour growth cycle. Cultures were grown over two additional daily growth cycles with 1:100 dilution between each cycle to condition them to the antibiotic-free medium, then used to set up competition assays. Five microliters of culture of each competitor – reference cells with pUA66-PrpsLGFP and either cells with an ARG plasmid or with the control plasmid – were mixed in 40 μL of fresh DM250. Forty microliters of the mix was added to phosphate buffered saline (PBS) and placed on ice or fixed with formaldehyde before being assayed by flow cytometry to determine the proportion of reference (GFP+) and ARG or control plasmid-containing cells (Day 0). The remaining 10 μL of the mix was added to 190 μL of fresh DM250 and incubated for 24 hours to allow strains to compete. Following this competition, cultures were diluted 20-fold in PBS and assayed by flow cytometry (Day 1). This protocol was repeated to obtain ARG effect estimates in a competition environment supplemented with kanamycin.
The fitness effect of an ARG was estimated as WARG / WVec, where WARG = ln(ARGDay1 × 100 / ARGDay0) / ln(GFPDay1 × 100 / GFPDay0) and WVec = ln(VecDay1 / VecDay0) / ln(GFPDay1 / GFPDay0). ARGDay1, ARGDay0, VecDay1 and VecDay0 are the proportion of flow cytometry events without a GFP signal, and GFPDay1 and GFPDay0 are the proportion of events with a GFP signal. Day 1 proportions are multiplied by 100 to account for growth occurring during the competition.
The copy number of plasmids encoding the blaTEM-116** ARG was measured by quantitative PCR (qPCR) using the comparative Ct (ΔΔCt) method. Plasmid carrying cells were cultured overnight in DM250 supplemented with 50 μg/ml kanamycin and DNA isolated using a Wizard Genomic DNA Purification Kit (Promega). Amplification of target genes was carried out using a SYBR Green based qPCR mix consisting of Q5® High-Fidelity 2× Master Mix (NEB), SYBR Green, and relevant primers (at a final concentration of 0.25 μM). Between one and two ng of template DNA was used per 10 μl reaction. Reactions were performed using a Thermo Scientific PikoReal Real-Time PCR System with default settings. Primers were designed using PrimerQuest (Integrated DNA Technologies, Inc.) to amplify the chromosomal *dxs gene, in order to determine the absolute Ct value of the bacterial chromosome (Ctch; xs_qpcr_F1:cgagaaactggcgatcctta; dxs_qpcr_R1: cttcatcaagcggtttcaca),* and the pUA66 plasmid encoded aph(3’)-IIagene, to determine the Ct value of the plasmid (Ctp; pUA_Kan_qpcr_F1: ctcgtcaagaaggcgatagaag; pUA_Kan_qpcr_R1:cgttggctacccgtgatatt). The relative copy number of the blaTEM-116 plasmid to the chromosome (ΔCt) was calculated as . The ΔCt of different bacterial strains was then normalized to the lab strain, REL606, to obtain the ΔΔCt value.
DATA-SPECIFIC INFORMATION FOR: dARG_cost_data.csv
1. Number of variables: 7
2. Number of cases/rows: 4562
3. Variable List:
GFP_neg_percent: Starting percentage of GFP- strain in fitness competition. Used as a flag for excessive experiemntal varition in setting up the fitness competition -- target is 50%.
ARG: ARG present in competition; 'vector' indicates plasmid backbone with no ARG
Date: Assay date
Strain: Host strain used in competition
Kan: competition environment -- 'Kan50' with kanamycin; 'DM' without kanamycin
Fitness: estimated fitness of test strain
4. Missing data codes:
None
DATA-SPECIFIC INFORMATION FOR: pmFP_cost.csv
1. Number of variables: 6
2. Number of cases/rows: 346
3. Variable List:
ARG: ARG present in competition. 'cell' indicates host strain with no vector; 'vector' indicates plasmid backbone with no ARG
replicate: replicate experimental block
Strain: Host strain used in competition
Kan: competition environment -- 'Kan50' with kanamycin; 'DM' without kanamycin
fitness: estimated fitness of test strain
Date: Assay date
4. Missing data codes:
None
DATA-SPECIFIC INFORMATION FOR: bla_plasmid_CPN.csv
1. Number of variables: 6
2. Number of cases/rows: 33
3. Variable List:
Sample name: Host strain used in assay
Ct.ch: Ct value for chromosomal dxs gene
Ct.p: Ct value for plasmid aph3 gene
delta.Ct: difference in Ct values for each strain-replicate combination (2^-(Ct.p - Ct.ch))
delta.delta.Ct: delta.Ct normalised to reference REL606 strain
mean.delta.delta.Ct: mean estimate of delta.delta.Ct: for each strain
4. Missing data codes:
None
DATA-SPECIFIC INFORMATION FOR: df.full.csv
1. Number of variables: 5
2. Number of cases/rows: 3351
3. Variable List:
ARG: ARG present in competition; 'vector' indicates plasmid backbone with no ARG
Date: Assay date
Strain: Host strain used in competition
Kan: competition environment -- 'Kan50' with kanamycin; 'DM' without kanamycin
Fitness: estimated fitness of test strain
4. Missing data codes:
None
Code
The R markdown file ARG_cost.Rmd contains code used to process data and perform all empirical data analyses and plotting reported in the manuscript associated with this submission.
The R markdown file community_competition.Rmd contains code used to simulate competition of communities containing combinations of host strain - ARGs.
To measure the fitness effect of each ARG, we performed a series of competition assays. The fitness effect of an ARG was estimated as the fitness difference between cells carrying an ARG plasmid (WARG) and cells carrying the control pmFP plasmid vector (WVec). The fitness of ARG and vector plasmid-carrying cells was estimated indirectly by competing each against reference cells carrying a GFP expressing plasmid (pUA66-PrpsLGFP).
To measure the copy number of the pmFP::blaTEM116* plasmid we used qPCR. Primers were designed to amplify the chromosomal dxs gene, in order to determine the absolute Ct value of the bacterial chromosome (Ct_ch) and the pUA66 plasmid encoded aph(3’)-IIa gene, to determine the Ct value of the pmFP::blaTEM116* plasmid (Ct_p). The relative copy number of the plasmid to the chromosome (ΔCt) was calculated as 2^-(Ct_p - Ct-ch). The ΔCt of different bacterial strains was then normalized to the lab strain, REL606, to obtain the ΔΔCt value.