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Data from: Antibiotics shift the temperature response curve of Escherichia coli growth

Citation

Cruz-Loya, Mauricio et al. (2021), Data from: Antibiotics shift the temperature response curve of Escherichia coli growth, Dryad, Dataset, https://doi.org/10.5068/D14T2B

Abstract

This publication consists of measurements of the temperature response of Escherichia coli growth in the presence of various antibiotic backgrounds. Growth is measured as the optical density of the corresponding bacterial culture 24 hours after inoculation. Two datasets are included in this submission. The first dataset consists of growth measurements of E. coli cultures at varying temperatures in the presence of a fixed concentration of twelve antibiotics (see table below for full list), and all possible pairs of these antibiotics present simultaneously. The second dataset consists of growth measurements at varying temperatures for two antibiotics (erythromycin and trimethoprim) at ten different concentrations.

Methods

Organism: Escherichia coli

Strain: BW25113

Dataset 1

The data consist of optical density measurements of E. coli cultures exposed to various antibiotic backgrounds.

Bacterial cultures were grown in LB broth (10 g/L tryptone, 5 g/L yeast extract, and 10 g/L NaCl) and maintained in 25% glycerol at -80°C. Fresh cultures were started by adding 20μL of thawed bacterial glycerol stock into 2 mL of LB followed by incubation at 37°C. Cultures were grown to exponential growth phase and diluted to maintain 104 cells per experimental condition (antibiotic background and temperature).

Antibiotics used in all experiments inhibited bacterial growth at sub-lethal concentrations (50% to 90% growth). The desired concentrations were first determined by a twelve-step concentration series of 2-fold at each step in 96-well plates (Costar). Antibiotic stock solutions were prepared in a total volume of 5 mL at 10-fold of their respective concentrations. Experiments of pairwise drug combinations were prepared by adding 10μL of each component drug followed by the addition of 80μL cell inoculum. 10μL of LB medium was added in replacement of a second drug for single drug experiments. Each experimental condition was conducted in 4 replicates from the same antibiotic stock solution. The 96-well plates were incubated at various temperatures (22°C, 25°C, 30°C, 37°C, 41°C, 44°C, 46°C) with aeration at 300 rpm.

The antibiotics and doses used are in the table below:

Antibiotic

Abbreviation

Mechanism of Action

Dose (mg/mL)

Ampicillin

AMP

cell wall synthesis inhibitor

1.2

Cefoxitin

FOX

cell wall synthesis inhibitor

1.2

Levofloxacin

LVX

fluoroquinolone, DNA gyrase inhibitor

0.01

Ciprofloxacin

CPR

fluoroquinolone, DNA gyrase inhibitor

0.005

Nitrofurantoin

NTR

DNA damaging, multiple mechanisms

2

Trimethoprim

TMP

folic acid synthesis inhibitor

0.1

Tobramycin

TOB

aminoglycoside

1.5

Gentamycin

GEN

aminoglycoside

1

Streptomycin

STR

aminoglycoside

2

Clindamycin

CLI

protein synthesis inhibitor, 50S

40

Erythromycin

ERY

protein synthesis inhibitor, 50S

50

Tetracycline

TET

protein synthesis inhibitor, 30S

0.25

Dataset 2

The second dataset was collected in order to explore the effects of varying the concentration of two antibiotics (ERY and TMP) in the temperature response of E. coli growth.

Ten antibiotic concentrations were chosen as a linear gradient ranging from the absence of drug to a near-inhibitory drug concentration (ERY:1000 µg/µl, TMP: 0.14 µg/µl) in order to clearly see changes in the shape of the temperature response. Four replicates of each antibiotic concentration were incubated at each of fourteen temperatures, ranging from 18ºC to 50ºC.

Usage Notes

This submission contains the following files:

  • data.csv    First dataset (temperature response of growth under fixed concentration of twelve antibiotics and all pairwise combinations).

  • conc_data_ERY_TMP.csv    Second dataset (temperature response of growth varying concentration of two antibiotics).
  • get_fr_advi_params.py    Python code to fit the modified Briere model to the first dataset.
  • README.txt    Description of data columns in datasets and requirements for running the code.