This study investigates the effects of colistin, an antimicrobial peptide, on Pseudomonas aeruginosa aggregates. By utilizing fluorescence microscopy and flow cytometry, the research aims to understand bacterial growth dynamics and antibiotic tolerance mechanisms.
To study the impact of antimicrobials on bacterial aggregates, take Pseudomonas aeruginosa culture in a growth medium that promotes aggregate formation — simulating growth during infection.
The engineered bacteria express a fluorescent protein for aggregate detection under a fluorescence microscope. Image in three dimensions to compute the volume of the aggregates, or the bacterial biomass, and visualize the increase in biomass over time, indicating bacterial growth.
Add colistin — a cationic antimicrobial peptide — at a sublethal concentration that kills susceptible bacteria while selecting the antibiotic-tolerant ones.
Colistin binds to negatively-charged lipopolysaccharides, or LPS, on the bacterial outer membrane, displacing cationic bridges that stabilize the LPS monolayer — damaging membrane integrity.
Colistin enters periplasm and binds to LPS on the cell membrane, disrupting the membrane and resulting in cell lysis. As a counter mechanism, specific genetic mutations in a subset of bacteria neutralize the negative charge of LPS. This modification inhibits the electrostatic interaction of cationic colistin with less anionic LPS — preventing cell death.
Image to visualize decreased biomass with time, indicating the impact of the antimicrobial. Add propidium iodide or PI — a fluorescent dye — that enters through the damaged membrane to bind DNA, labeling only the dead cells.
Perform fluorescence-activated cell sorting, or FACS, separating PI-labeled susceptible cells and fluorescently-labeled antibiotic-tolerant cells. The cells are ready for downstream assays.
To image the Pseudomonas aeruginosa aggregates by confocal laser-scanning microscope, at the end of the incubation, designate three wells of the culture plate as antibiotic treatment replicates in one well as the "no treatment control," and place the plate on the heated stage of the microscope.
Select a 63 times oil immersion objective, and open the Locate tab to identify the bacterial aggregates in the bright field. Define an area for imaging within each well, and use the Positions module to store the area position. Set the excitation wavelength to 488 nanometers and the emission wavelength to 509 nanometers.
In the Acquisition module, select the Z-Stack option to acquire the images, and use the Line Averaging module to reduce the background fluorescence in the GFP channel within the total volume of the Z-stack images. Set the Time Series option to capture 60 slices in each well at 15-minute intervals for 18 hours, and use the definite focus strategy to store a focal plane for each position that will be re-imaged at each time point throughout the experiment.
4.5 hours after setting up the imaging experiment, image each position to determine the aggregate biomass within each of the four wells before the addition of the antibiotic. After six hours, gently add antibiotic at two times below the minimum inhibitory concentration to the middle of each well, just below the air-liquid interface, and click Start Experiment to begin the post-antibiotic treatment imaging.
To isolate the live cells, at the end of the 18-hour imaging period, label the bacteria in each well with the appropriate volume of propidium iodide, according to the manufacturer's recommendations. At the end of the incubation, use an insulated container to transfer the plate to the flow cytometer, and set the cytometer to detect GFP and propidium iodide using a 70-micron nozzle. Then, run 1-milliliter aliquots of each culture supernatant at the lowest flow rate to sort the viable GFP-positive and nonviable propidium iodide-negative Pseudomonas aeruginosa aggregates.