The significance of this protocol is that it offers a simple and reproducible framework for quantifying in vitro biofilm structures under varying antimicrobial conditions. The main advantage of this technique is that it helps eliminate subjective variations associated with the manual operation of COMSTAT, which ultimately facilitates the standardization and transparency of experiments across research centers. To image the Pseudomonas aeruginosa cultures, place the plate onto the stage of a confocal microscope, equipped with the appropriate laser excitation wavelengths and filter sets.
And use a 20 to 25x water immersion lens to capture at least six layered z-stack images from the substratum to the top of each biofilm segment in 0.3 micrometer increments. Then save the images as OME-TIFFs for COMSTAT analysis. When all the images have been acquired, open the COMSTAT2 package in ImageJ and create a source folder on the desktop.
Add a single OME-TIFF to the folder and open OME-TIFF from the source folder. Delete any empty layers containing no biomass. Select File, Import, and Image Sequence to import the file into ImageJ.
Locate and highlight the source folder without opening it and click Select. A sequence options window will appear, click OK.Select Image, Transform, and Flip Z to flip the orientation of the biofilm so that the substratum is at the top of the stack. To define the image properties, select Image and Properties, a source window will appear.
Specify the unit of length as micron, define the voxel depth as 0.3, and click OK.Select Image, Adjust, and Threshold. To adjust the image threshold in the threshold window, position the lower slider to the far right to manually set the maximum threshold value and use the upper slider to set the minimum threshold. Then use the slider in the image window to scroll through each layer to ensure that the background noise is sufficiently removed throughout the stack, and select Set to fix the lower threshold value.
In the set threshold levels window, select OK, and set and fix the maximum threshold value similarly. Select Apply, click OK in the convert stack to binary window that appears, and exit the threshold window. Select Plugins, Bio-Formats, and Bio-Formats Exporter to save the file with a new file name in the source folder.
A Bio-Formats Exporter multiple files window will appear, select OK.A Bio-Formats Exporter options window will appear, select OK again. To run COMSTAT, select plugins and COMSTAT2, an about window will appear, select OK.In the Observed Directories window, select Add, locate and highlight the source folder, highlight and click Choose. An Images in Directories window will appear that lists the OME-TIFFs to be analyzed.
On the COMSTAT2.1 window, deselect Automatic Thresholding Otsu's Method and Connected Volume Filtering to ensure that the software uses preset threshold values for individual OME-TIFFs. In the COMSTAT2.1 window, select Biomass, Thickness Distribution and Surface Area, and click Go to run the program. The output data will be shown in the log window.
The measurements will be automatically saved as TXT files in the source folder. In this representative analysis, a Pseudomonas aeruginosa isolate, cultured from an infected cystic fibrosis patient, was used to demonstrate the strengths of this approach, inaccurately quantifying antimicrobial induced changes in in vitro biofilm architecture. Live cell imaging can also visualize changes in Pseudomonas aeruginosa biofilm structure before and after biofilm specific monoclonal and tobramycin treatment.
COMSTAT data analysis revealed significant differences between treated biofilm structures compared to control cultures. In tobramycin-treated cultures, a clear reduction in the average thickness and biomass was observed. However, in the presence of antibodies, the P.aeruginosa biofilm was resistant to these tobramycin-induced structural changes.
When examining the surface to bio volume ratio, a significant reduction was observed in the presence of antibodies in both tobramycin-exposed and unexposed biofilms, indicating the formation of aggregates in antibody treated cultures. This procedure can be performed to quantitatively assess or compare the effects of different antimicrobials used to disrupt biofilm matrices. Using this technique as a general framework, researchers can explore different ways to refine the protocol to include new mathematical models and algorithmic plugins in ImageJ to better depict biofilm heterogenecy.
