1. Cell culture, stress-induction, and sampling procedure
NOTE: Use sterile culture glassware, pipette tips, and growth medium filtered at 0.22 µm to avoid background particles. Here, cell cultures are grown in low autofluorescence rich defined medium (see Table of Materials)7,8.
2. Plating assay
NOTE: The plating assay allows for measuring the concentration of cells able to generate a CFU in the culture samples. This procedure reveals the rate at which one cell divides into two viable cells and allows to detect cell division arrests (e.g., increase of the bacterial generation time of cell lysis).
3. Flow cytometry
NOTE: The following section describes the preparation of cell samples for flow cytometry analysis. This analysis technique reveals the distribution of cell size and DNA content for a large number of cells. When possible, it is recommended to process the flow cytometry samples immediately. Alternatively, samples can be kept on ice (for up to 6 h) and analyzed simultaneously at the end of the day, once plating and microscopy imaging have been performed.
4. Snapshot microscopy imaging
NOTE: The following part describes the preparation of microscopy slides and image acquisition for population snapshot analysis. This procedure will provide information regarding the morphology of the cells (cell length, width, shape) and the intracellular organization of the nucleoid DNA.
5. Microfluidics time-lapse microscopy imaging
NOTE: The following part explains the preparation of the microfluidic plates (see Table of Materials), cell loading, microfluidics program, and time-lapse image acquisition. This imaging procedure reveals the behavior of individual cells in real-time.
6. Image analysis
NOTE: This section briefly describes the key steps of processing and analyzing snapshot and time-lapse microscopy images. Opening and visualization of microscopy images is done with the open source ImageJ/Fiji (https://fiji.sc/)11. Quantitative image analysis is performed using the open source ImageJ/Fiji software together with the free MicrobeJ plugin12 (https://microbej.com). This protocol uses the MicrobeJ 5.13I version.
The procedure described was used to analyze the behavior of Escherichia coli K12 cells during transient exposure to cephalexin, an antibiotic that specifically inhibits cell division (Figure 1A)13. The hupA-mCherry E. coli strain that produces the fluorescently labeled HU protein associated with the chromosomal DNA was used to investigate the dynamics of the chromosome throughout this treatment8,9. The exponentially growing hupA-mCherry E. coli cells were analyzed before (t0) and 60 min after incubation with cephalexin (t60). Then, the antibiotic was washed away and the recovery of the cell population after 1 h (t120) and 2 h (t180) was analyzed (Figure 1B).
Figure 1: Procedure for the analysis of bacterial response to stress treatments. (A) Schematic of the method. (B) Cartoon illustrating the cell morphology during normal growth in rich medium and during transient exposure to cephalexin (Ceph.), from addition at (t0) and after cephalexin washing from (t60) to (t180). Please click here to view a larger version of this figure.
The parallel evolution of OD and CFU/mL is a first indicator that helps to understand the effect of the stress treatments. These two parameters are strictly correlated during unperturbed growth but are often uncoupled and evolve independently under stress. Cell cultures growing in the presence of cephalexin exhibited similar OD600nm increases as the unstressed cultures (Figure 2A), showing that the drug did not affect cell mass synthesis. However, the concentration of viable cells did not increase when cephalexin was present due to strict inhibition of cell division (Figure 2B). Cells started dividing again when cephalexin was removed and eventually reached a concentration equivalent to the unstressed culture at (t180). These results reflect the bacteriostatic effect of cephalexin, which induces a fully reversible inhibition of cell division. Different stresses will result in different uncoupling of the OD and CFU/mL curves, depending of the effect induced (e.g., modification of the cell morphology such as filamentation or bulging, cell death with or without lysis). A non-exhaustive list of possible outcome results indicative of different stress-induced effects is presented in Figure 2C.
Figure 2: Bacterial growth monitoring of untreated and cephalexin-treated cells at the population level. (A) Optical density monitoring (OD600nm/mL). (B) Concentration of viable cell (CFU/mL) within untreated and cephalexin-60min-treated cultures. Error bars indicate the standard deviation for an experimental triplicate. (C) Schematics of possible results and associated stress effects. Please click here to view a larger version of this figure.
Single-cell analysis is essential to accurately interpret the stress response observed at the population level. Flow cytometry allows the examination of cell size and DNA content of several thousands of cells14,15 (Figure 3). Exposure to cephalexin provoked the parallel increase of cell size and DNA content (t60). When cephalexin was removed, the population cell size and DNA content gradually decreased to become similar to the unstressed population at t180. These results show that cephalexin did not inhibit DNA replication and provoked the formation of filamentous cells that contained several chromosome equivalents. These filaments divided into cells with normal cell size and DNA content when the drug was washed away. Flow cytometry results would be very different for stresses that inhibit DNA synthesis, which lead to the formation of filamentous cells containing only one non-replicating chromosome. In that case, cell size would increase similarly but would not be associated with increase in DNA content.
Figure 3: Representative flow cytometry analysis of untreated and cephalexin-60min-treated cells. (A) Cell size distribution histograms (FSC-H). (B) DNA content histograms (FL1-SYTO9). n = 120,000 cells analyzed. Please click here to view a larger version of this figure.
Snapshot microscopy imaging was used to examine the cell morphology and the intracellular organization of the DNA shown by HU-mCherry localization (Figure 4A). Cephalexin provoked the formation of long cells with normal cell width and no division septa. These smooth filaments contained regularly spaced DNA structures called nucleoids, confirming that cephalexin did not affect chromosome replication and segregation. Quantitative image analysis largely confirmed the cell size and DNA content increase previously observed with flow cytometry (Figure 4B,C). Results would be very different for stresses that induce DNA-damage, which lead to the formation of filamentous cells in which replication continues but segregation is impaired. In that case, cell size and DNA content would increase similarly, but cells would harbor a single unstructured mass of DNA. Snapshot images could also reveal other kind of aberrant cell shapes or the presence of mini, anucleate, or lysed cells (ghost cells).
Figure 4: Microscopy snapshot analysis of untreated and cephalexin-60min-treated cells. (A) Representative microscopy images showing phase contrast (grey) and HU-mCherry signal (red). (B) Cell length distribution histograms. Scale Bar = 5 µm. (C) Histograms of the number of nucleoid per cell. Between 800 and 2,000 cells were analyzed for each sample. Please click here to view a larger version of this figure.
Time-lapse microscopy associated with the microfluidic apparatus16 helped to determine the phenotypes previously observed and provides additional insights regarding the development and causality of the growth deficiency. Time-lapse images (Figure 5A and Movie 1) confirmed that cell elongation (cell mass synthesis), and chromosome replication and segregation were not inhibited by exposure to cephalexin. In addition, it revealed the process of recovery when cephalexin was removed. Analysis of the filamentous cell lineage showed that cell division restarts ~20 min after washing away the drug (Figure 5B). The resulting divided cells were viable, because they in turn divided, eventually leading to the formation of 33 cells exhibiting normal size and DNA content. This allowed calculation of an overall generation time of ~31 min over the 180 min of the experiment, which is similar to the generation time calculated for the unstressed population from CFU/mL measurements (~33 min).
Figure 5: Microscopy time-lapse analysis of cephalexin-60min-treated cells. (A) Representative microscopy images showing phase contrast (grey) and HU-mCherry signal (red). The monitored filamentous cell is indicated by the white outline, and divided cells by different colors. Scale Bar = 5 µm. (B) Schematic representation of the filamentous cell lineage corresponding to panel (A) and to Movie 1. Please click here to view a larger version of this figure.
Movie 1: Microfluidic movie of E. coli HU-mCherry treated with cephalexin. Cephalexin was injected after 60 min, followed by injection of fresh RDM medium for 3 h. Time indicated in yellow (1 frame every 10 min). Scale Bar = 5 µm. Please click here to view this video (Right click to download).
Agarose | BioRad | 1613100 | Certified molecular biology agarose |
Attune NxT Acoustic Focusing Cytometer | ThermoFisher scientific | A24858 | Cytometer |
CellASIC ONIX Microfluidic System | Merck Millipore | CAX2-S0000 | Microfluidic system |
CellASIC ONIX2 FG | Merck Millipore | ONIX2 1.0.1 | Microfluidic software |
CellASIC ONIX2 Manifold Basic | Merck Millipore | CAX2-MBC20 | Manifold system |
CytoOne 96-well plate with lid | Starlab | CC7672-7596 | Microplate with 0,2 mL well working volume and clear flat bottom, for automated plate reader |
E. coli strain carrying a chromosomal insertion for a hupA-mCherry fusion | Created by P1 transduction of hupA-mCherry in E. coli MG1655 | ||
Fiji | ImageJ | https://fiji.sc/ | Image software. Cite Schindelin et al. if used in publication |
Gene Frame | Thermo Scientific | AB-0578 | Blue frame (125 μL, 1,7 x 2,8 cm) |
Luria-Broth agarose medium | MP Biomedicals | 3002232 | Growth medium for plating assay |
MicrobeJ | Imagej/Fiji plugin | https://www.microbej.com/ | Microscopy image analysis plugin. Cite Ducret et al. If used in publication; Detection settings: For bacteria : Area (μm2): 0,1-max; Length (μm): 0,5-max; Width (μm): 0,6-max; Range (μm): 0,5-max; Angularity (rad): 0-0,3; 0-max for all other parameters. For nucleoid: Tolerance: 500; Threshold: Local; 0-max for all other parameters |
Microfluidic Plates CellASIC ONIX | Merck Millipore | B04A-03-5PK | Plate for Microfluidic system |
Microscope Nikon eclipse Ti | Nikon | Fluorescence microscope | |
MOPS EZ Rich Defined Medium (RDM) | Teknova | M2105 | Growth rich medium, 10x MOPS Mixture, 0,132 M K2HPO4, 10x AGCU, 5x Supplement EZ, 20% Glucose. Filtered at 0,22 μm |
SYTO9 Green Fluorescent Nucleic Acid Stain | ThermoFisher scientific | S34854 | DNA fluorescent dye |
TECAN Infinite M1000 | TECAN | 30034301 | Automated plate reader |
Analysis of the bacterial ability to grow and survive under stress conditions is essential for a wide range of microbiology studies. It is relevant to characterize the response of bacterial cells to stress-inducing treatments such as exposure to antibiotics or other antimicrobial compounds, irradiation, non-physiological pH, temperature, or salt concentration. Different stress treatments might disturb different cellular processes, including cell division, DNA replication, protein synthesis, membrane integrity, or cell cycle regulation. These effects are usually associated with specific phenotypes at the cellular scale. Therefore, understanding the extent and causality of stress-induced growth or viability deficiencies requires a careful analysis of several parameters, both at the single-cell and at the population levels. The experimental strategy presented here combines traditional optical density monitoring and plating assays with single-cell analysis techniques such as flow cytometry and real time microscopy imaging in live cells. This multiscale framework allows a time-resolved description of the impact of stress conditions on the fate of a bacterial population.
Analysis of the bacterial ability to grow and survive under stress conditions is essential for a wide range of microbiology studies. It is relevant to characterize the response of bacterial cells to stress-inducing treatments such as exposure to antibiotics or other antimicrobial compounds, irradiation, non-physiological pH, temperature, or salt concentration. Different stress treatments might disturb different cellular processes, including cell division, DNA replication, protein synthesis, membrane integrity, or cell cycle regulation. These effects are usually associated with specific phenotypes at the cellular scale. Therefore, understanding the extent and causality of stress-induced growth or viability deficiencies requires a careful analysis of several parameters, both at the single-cell and at the population levels. The experimental strategy presented here combines traditional optical density monitoring and plating assays with single-cell analysis techniques such as flow cytometry and real time microscopy imaging in live cells. This multiscale framework allows a time-resolved description of the impact of stress conditions on the fate of a bacterial population.
Analysis of the bacterial ability to grow and survive under stress conditions is essential for a wide range of microbiology studies. It is relevant to characterize the response of bacterial cells to stress-inducing treatments such as exposure to antibiotics or other antimicrobial compounds, irradiation, non-physiological pH, temperature, or salt concentration. Different stress treatments might disturb different cellular processes, including cell division, DNA replication, protein synthesis, membrane integrity, or cell cycle regulation. These effects are usually associated with specific phenotypes at the cellular scale. Therefore, understanding the extent and causality of stress-induced growth or viability deficiencies requires a careful analysis of several parameters, both at the single-cell and at the population levels. The experimental strategy presented here combines traditional optical density monitoring and plating assays with single-cell analysis techniques such as flow cytometry and real time microscopy imaging in live cells. This multiscale framework allows a time-resolved description of the impact of stress conditions on the fate of a bacterial population.