An Assay for Real-Time Monitoring of Extracellular pH in Dental Biofilms

Take a multi-well plate containing a neutral pH salivary solution supplemented with glucose.

Add a dual-emission ratiometric, pH-sensitive dye.

Place the plate on a confocal microscope stage.

Introduce a glass slab with an adhered dental biofilm into the well facing down.

Bacteria in the biofilm ferment glucose, generating organic acids and lowering pH in the vicinity.

The acidic pH protonates the dye, causing its internalization and up-concentration within bacteria, staining them, while the deprotonated dye remains extracellular.

Over time, the pH becomes acidic in other areas of the biofilm.

Upon laser excitation, the protonated dye exhibits a shift in fluorescence emission compared to its deprotonated form.

Capture fluorescent images at specified intervals.

Using appropriate software, eliminate bacterial-derived fluorescence signals.

Calculate the ratio of fluorescent emission intensities from the extracellular matrix at two specific wavelengths, correlating to pH values.

Determine the decrease in extracellular biofilm pH following glucose metabolism by bacteria.

Within a few hours after biofilm collection, after preparing a salivary solution according to the text protocol, titrate the solution to pH 7.0, and add glucose to a concentration of 0.4%. Pipette 100 microliters of solution per biofilm to be analyzed into a glass bottom 96-well plate for microscopy.

Add 5 microliters of the ratiometric dye per well. Place the 96-well plate on the microscope stage. Then, turn on the microscope, and the 543 laser line. Warm up the incubator to 37 degrees Celsius. Use the same microscope settings as for the calibration of the dye.

Next, with a slim pair of tweezers, pick up one or more glass slabs and place them in the saliva-filled wells -- one slab per well with the biofilms facing downward. Under "Scan Control" → "Single" acquire single images, or to acquire Z-stacks under "Scan Control", "Z Settings", "Num Slices", choose the number of slices to be imaged and use "Mark First," "Mark Last" to mark the first and last slice.

To follow pH changes in a microscopic field of view over time, under "Stage and Focus Control," "Mark Pos" to mark the XY position, and take repeated images at consecutive time points.

To export the images as .tiff files, use "Macro" → "File Batch Export" from the microscope software. Mark the files to be exported and save red and green channel images in separate folders as .tiff files. Then, rename the files in both folders to give them sequential numbers.

After importing the red and green image series into software such as daime, under "Segment" → "Automatic segmentation" → "Custom Threshold," segment the green channel images with individually chosen brightness thresholds. Choose the brightness threshold with care so that all bacteria, but not the matrix will be recognized as objects during segmentation. Verify visually that the areas recognized as objects correspond well to the bacterial biomass.

It is crucial to select brightness thresholds that differentiate accurately between cells and extracellular matrix, and to verify visually that all bacterial cells have been removed from the images during image processing.

Under "Segment" → "Transfer Object Layer," transfer the object layer of the segmented green channel images to the corresponding red channel images. Use the "Object Editor" function to reject and delete all objects in the red and green channel images, so that only the extracellular matrix is left in the biofilm images.

Next, import the background images into ImageJ and use "Analyze" → "Histogram" to determine the average fluorescence intensity in the background images taken with the laser turned off. Now, import the biofilm images into ImageJ. Under "Process" → "Math" → "Subtract" subtract the appropriate background from the red and green images. Then, use "Process" → "Image Calculator" to divide the green image series G1 by itself.

Now, multiply the resulting image series G2 with the green image series G1. This will yield an image series G3 where NaN is assigned to all pixels belonging to areas that were recognized as objects in daime. Proceed in the same way with the red image series.

Under "Process" → "Filters" → "Mean"; radius: one pixel, apply the 'Mean' filter to compensate for detector noise. Then, divide the green image series by the red image series. This results in a green-to-red ratio for every remaining pixel in the extracellular space of the images.

From "Image" → "Lookup tables" use false coloring for graphic representation of the ratios in the images. Then use "Analyze" → "Histogram" to calculate the mean ratio for each image.

Finally, convert the green-to-red ratios to pH values according to the text protocol.