Phage-antibiotic synergy: cell filamentation is a key driver of successful phage predation
Data files
Sep 01, 2023 version files 810.58 KB
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Datafile_01092023.xlsx
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README.md
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Abstract
Phages are promising tools to fight antibiotic-resistant bacteria, and as for now, phage therapy is essentially performed in combination with antibiotics. Interestingly, combined treatments including phages and a wide range of antibiotics lead to an increased bacterial killing, a phenomenon called phage-antibiotic synergy (PAS), suggesting that antibiotic-induced changes in bacterial physiology alter the dynamics of phage propagation. Using single-phage and single-cell techniques, each step of the lytic cycle of phage HK620 was studied in E. coli cultures treated with either ciprofloxacin or cephalexin, two filamentation-inducing antibiotics. In the presence of sublethal doses of antibiotics, multiple stress tolerance and DNA repair pathways are triggered following activation of the SOS response. One of the most notable effects is the inhibition of bacterial division. As a result, a significant fraction of cells forms filaments that stop dividing but have higher rates of mutagenesis. Antibiotic-induced filaments become easy targets for phages due to their enlarged surface areas, as demonstrated by fluorescence microscopy and flow cytometry techniques. Adsorption, infection and lysis occur more often in filamentous cells compared to regular-sized bacteria. In addition, the reduction in bacterial numbers caused by impaired cell division may account for the faster elimination of bacteria during PAS. We developed a mathematical model to capture the interaction between sublethal doses of antibiotics and exposition to phages. This model shows that the induction of filamentation by sublethal doses of antibiotics can amplify the replication of phages and therefore yield PAS. We also use this model to study the consequences of PAS on the emergence of antibiotic resistance. A significant percentage of hyper-mutagenic filamentous bacteria are effectively killed by phages due to their increased susceptibility to infection. As a result, the addition of even a very low number of bacteriophages produced a strong reduction of the mutagenesis rate of the entire bacterial population. We confirm this prediction experimentally using reporters for bacterial DNA repair. Our work highlights the multiple benefits associated with the combination of sublethal doses of antibiotics with bacteriophages.
README: Phage-antibiotic synergy: cell filamentation is a key driver of successful phage predation
PATHOGENS-D-22-02110R2 "Phage-antibiotic synergy: cell filamentation is a key driver of successful phage predation"
Using single-phage and single-cell techniques, each step of the lytic cycle of phage HK620 was studied in E. coli cultures treated with either ciprofloxacin or cephalexin, two filamentation-inducing antibiotics. In the presence of sublethal doses of antibiotics, multiple stress tolerance and DNA repair pathways are triggered following activation of the SOS response. One of the most notable effects is the inhibition of bacterial division. As a result, a significant fraction of cells forms filaments that stop dividing but have higher rates of mutagenesis.
Description of the Data and file structure
Data corresponding to the figures in the manuscript are arranged in individual tabs included in the same file Datafile_figures_2.xlsx
- Fig. 1b: Radii measurements of phage HK620 lysis plaques in the presence of subinhibitory antibiotics concentrations (indicated in the “Treatment” column).
- Fig. 1c: E. coli TD2158 PL4 growth/lysis dynamics in the presence/absence of antibiotics and phage HK620. Each row represents one of the four replicates carried out for each antibiotic/phage treatment. Individual values represent the OD600 measurement at the given timepoint (Time row).
- Fig. 2a: E. coli MG1655 growth/lysis dynamics in the presence/absence of antibiotics and phage T4. Each row represents one of the four replicates carried out for each antibiotic/phage treatment. Individual values represent the OD600 measurement at the given timepoint (Time row).
- Fig. 2b: E. coli MG1655 growth/lysis dynamics in the presence/absence of antibiotics and phage T5. Each row represents one of the four replicates carried out for each antibiotic/phage treatment. Individual values represent the OD600 measurement at the given timepoint (Time row).
- Fig. 2a: E. coli MG1655 growth/lysis dynamics in the presence/absence of antibiotics and phage T7. Each row represents one of the four replicates carried out for each antibiotic/phage treatment. Individual values represent the OD600 measurement at the given timepoint (Time row).
- Fig. 3b, 3c: Measurements of HK620 adsorption on individual E. coli TD2158 PL4 bacterium. Cells are numbered in the “Cell” column, antibiotic treatment is indicated in the “Treatment” column, measured bacterial length is indicated in the “Cell length (µm)” column, and the number of adsorbed HK620 is marked in “Number of adsorbed phages” column.
- Fig. 3d: Mean and s.e.m. values of HK620 adsorption obtained from the dataset indicated in “Fig. 3b, 3c” for each antibiotic condition.
- Fig. 3e: Mean and s.e.m. values of HK620 adsorption obtained from the dataset indicated in “Fig. 3b, 3c” separating each antibiotic-treated culture in filaments (cell length > 5.2 µm) and regular-sized cells (cell length < 5.2 µm). The morphological category is indicated in the “Morphology” column.
- Fig. 3f: Mean and s.e.m. values of HK620 adsorption per unit of surface separating each antibiotic-treated culture in filaments (cell length > 5.2 µm) and regular-sized cells (cell length < 5.2 µm). The morphological category is indicated in the “Morphology” column.
- Fig. 4b, 4c: Measurements of T5 adsorption on individual E. coli MG1655 bacterium. Cells are numbered in the “Cell” column, antibiotic treatment is indicated in the “Treatment” column, measured bacterial length is indicated in the “Cell length (µm)” column, and the number of adsorbed T5 is marked in “Number of adsorbed phages” column.
- Fig. 3d: Mean and s.e.m. values of T5 adsorption obtained from the dataset indicated in “Fig. 4b, 4c” for each antibiotic condition.
- Fig. 3e: Mean and s.e.m. values of T5 adsorption obtained from the dataset indicated in “Fig. 4b, 4c” separating each antibiotic-treated culture in filaments (cell length > 5.2 µm) and regular-sized cells (cell length < 5.2 µm). The morphological category is indicated in the “Morphology” column.
- Fig. 3f: Mean and s.e.m. values of T5 adsorption per unit of surface separating each antibiotic-treated culture in filaments (cell length > 5.2 µm) and regular-sized cells (cell length < 5.2 µm). The morphological category is indicated in the “Morphology” column.
- Fig. 5b: Percentages of infected cells using HK620 hkcEF::PrrnB-gfp in the presence of ciprofloxacin at different multiplicities of infection (MOIs). The morphological category is indicated in the “Subpopulation” column, and the multiplicity of infection in the “MOI” column.
- Fig. 5b: Percentages of infected cells using HK620 hkcEF::PrrnB-gfp in the presence of cephalexin at different MOIs. The morphological category is indicated in the “Subpopulation” column, and the multiplicity of infection in the “MOI” column.
- Fig. 6b: Number of T7 foci detected in individual ciprofloxacin-treated E. coli MG1655 at two timepoints (10 and 30 minutes). Cell length and foci number are indicated in their respective column.
- Fig. 7: One-step growth curve data of phage HK620 in the presence of subinhibitory concentrations of antibiotics. Antibiotics are indicated in the “Treatment" column. Plaque-forming units observed for each timepoint are indicated in three columns under the "PFU/cell" header, each column belongs to one of the three replicates performed for each antibiotic treatment. Resulting mean and s.e.m are also indicated.
- Fig. 10a: Fluctuation test data of E. coli TD2158PL4 in the presence/absence of ciprofloxacin and HK620. The presence/absence of ciprofloxacin is indicated in the “Antibiotic” column, the presence/absence of phage HK620 is indicated in the “Phage” column. The mutagenesis rate for each replicate is indicated in its own column and the mean and s.e.m. values are also indicated.
- Fig. 10b: Fraction of SOS-triggered cells in the presence of ciprofloxacin at increasing concentrations (“[Ciprofloxacin]” column). The replicate number for each condition is indicated in the "Replicate" column. The morphological categories are indicated in the “population” column. The mean percentages of SOS-triggered cells and their respective s.e.m. are also indicated.
- Fig. 10c: Simultaneous measurements of phage HK620 hkcEF::PrrnB-gfp infection and SOS-induction in individual E. coli TD2158 PL4 bacteria in the presence of subinhibitory ciprofloxacin. Cells are numbered in the “Cell” column. GFP intensity due to phage infection is indicated on the “GFP intensity” column. Fold-change of mCherry intensity (reporter of SOS activation) is indicated on “SOS fold-change” column. Measured bacterial length is indicated in the “Cell length (µm)” column. The status of infected/non-infected for each bacteria is determined from the GFP intensity levels and is indicated in the last column.
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Methods
Phage-Antibiotic Synergy measurements. PAS measurements in liquid cultures were carried out by OD600measurements in a 96-well microplate. Briefly, a log-phase E. coli TD2158 PL4 culture was diluted to a final OD600 = 0.025. Subinhibitory antibiotic concentrations were added at this time. Replicates of 200 μL of each condition were dispensed in each well. After two hours of incubation at 37ºC under 180 rpm agitation, the same number of phages (phage titer PF/mL) was added to each replicate and lysis was observed by the reduction in OD600. Conversely, PAS measurements in semi-solid cultures were performed using the double agar overlay assay. For this, 10 mL of a log-phase culture of E. coli TD2158 PL4 at OD600 = 1 were infected with a final titer of 103 PFU/mL of phage HK620 and incubated at 37°C under 180 rpm agitation. Twenty-five minutes post-infection, 100 μL of this culture was mixed with 3 mL of soft-LBA (0.75% agar) and plated over a 20 mL bottom layer of 1.5 % LBA on a petri dish. Antibiotics were added at sublethal concentrations in the bottom layer. Plates containing 100 PFU each were imaged using a digital camera (Nikon D5300). Plaque diameter was measured using a homemade software designed by Leon Espinosa (available upon request) and average plaque diameter was plotted for each condition.
Single-cell infection. An overnight culture of E. coli TD2158 PL4 was diluted to final OD600 = 0.025 in 10 mL of LB medium, and supplemented with the appropriate sublethal antibiotic concentrations when required. At OD600 ≈ 0.8, phages were added to reach a final MOI between 0.1 to 10. Thirty minutes post-infection aliquots were sampled and fixed by diluting 1:1 in PBS buffer PFA 4% solution to stop phage replication and prevent cell lysis. For adsorption analysis, unabsorbed phages were washed by centrifugation followed by resuspension of the pellet in PBS-PFA 2% solution. For all samples, the mix was put on a coverslip, gently squeezed under a 1 mm thick 1% agarose pad, and directly imaged on an inverted epifluorescence microscope (Nikon TiE) using an oil immersion 100X NA 1.45 objective. Images were acquired using a cooled camera (Hamamatsu Orca Fusion). Acquisition was carried out using Nikon’s NIS-Element software.
Image analysis. Cell image analysis was performed using MicrobeJ [1]. Cell shape parameters were directly measured from phase-contrast microscopy. For phage adsorption quantification, automated foci detection was carried out using the maxima foci function of MicrobeJ, after background subtraction and thresholding the GFP channel to isolate individual fluorescent phages. To quantify phage infection of HK620 hkcEF::PrrnB-gfp the integrated fluorescence of each cell was measured in the GFP. Statistical analysis was conducted in R [2] and figures were produced using the package ggplot2 [3]. To calculate average phage adsorption per unit of surface, E. coli shape was considered as a cylinder with two half spheres on each extremity. Bacterial length (L), measured from pole to pole, and average width (d) was determined for each bacterium using the image analysis software MicrobeJ. We then used these measurements to approximate bacterial cell surface through the following equation: π*d*(L-d) + 4*π*(d/2)2. The first term represents the surface of the cylinder of length (L-d), and the second, the surface of the two hemispheres of radius (d/2) at each pole.
Mutation rates measurements. The frequency of RifR CFU after 20 hours of growth was determined as follows. A log-phase, OD600 = 1 culture was diluted 1:106 (final concentration 200–500 CFU/mL) and 100 μL were dispensed in each well of a U-shaped bottom 96-well microplate (Nunclon Delta-Treated, U-Shaped-Bottom Microplate, Nunc). Antibiotics, if used, were added at ½ of the MIC at this point. The plate was covered with a sealing tape and incubated at 37 °C, 180 rpm, in a humidity cassette to minimise culture evaporation. After 20 h of incubation, the total volume (100 µL) of 84 wells was plated onto separate LBA plates supplemented with 75 μg/mL rifampicin. The remaining 12 wells were serially diluted and plated on non-selective plates to count the total number of CFU. Mutation rates were estimated by the MSS-MLE algorithm provided by the FALCOR calculator (https://lianglab.brocku.ca/FALCOR/). For the experiments in which we assessed phage effect in RifR mutant frequencies, HK620 phages were added in all wells at 11 h post-inoculation with a final titer of 4x103 PFU/well. Each condition was repeated at least three times.
References
1. Ducret A, Quardokus EM, Brun YV. MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis. Nat Microbiol. 2016;1: 16077. doi:10.1038/nmicrobiol.2016.77
2. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2021. Available: https://www.R-project.org/
3. Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. 2016.