Full- versus Sub-Regional Quantification of Amyloid-Beta Load on Mouse Brain Sections

This protocol compares amyloid-beta plaque load in full sections of interest and sub-regions of interest in brain sections from APP/PS1 transgenic mice. The method and results presented in this particular protocol will enable the readers or researchers to choose either between the full region of interest or sub region of interest analysis to determine a beta load in mouse brain sections. To begin, download the image analysis software.

Upon installation, start the software and click on the file, then open and choose the image to be analyzed. From the software tool bar, select the straight tool and draw a straight line along the length of the scale bar. Click on the analyze, then click on the set scale tabs.

Again, click on the analyze, then measure tabs to note the length or distance of the scale bar in pixels. In the popup window, enter the distance in pixels, the known distance of the scale bar, and enter the unit of length as a micrometer. Then, check the global box to apply the new scale setting to all following images, if multiple images are processed.

Click OK to apply the settings. To set the desired measurement to the area of the section, go to analyze, then set measurements, and select the area and display label boxes. Ensure that the image being analyzed is selected under the Redirect To tab.

For ease of hippocampus or cortex visualization, go to the image and adjust brightness or contrast. Drag the maximum slide bar gradually to the left to increase tissue clarity until the brain regions of interest or ROI are identifiable. Use the polygon or freehand selection tool to outline the hippocampus region.

Once the region is outlined, click on the reset option of the brightness or contrast settings to revert to the original brightness. To measure the total tissue area of the selected region, click on the edit and clear outside. Once the selected region is the only image on screen, click the analyze, then measure tabs to obtain the total tissue area analyzed in a popup window.

Then, save the data in an Excel file. To measure the 6-E10 stained positive area, go to the image, adjust, and color threshold tabs in order. A pre-made filter under the thresholding method provides desired results highlighting the strongest signals in red.

After selecting the appropriate threshold, check the dark background to highlight the amyloid beta spots on a black background. Click on the select, then original, and again select, giving the dark signals of amyloid beta deposits on a white background. When the popup window generates, click on the analyze and analyze particles tab, and hit OK.Copy the summary output generated by the software by clicking on the edit and copy buttons.

Then, paste into the previously started Excel file with respective labels. Calculate the percent 6E-10 positive area by using the formula After downloading the image analysis software, perform the steps until the brain ROI are identifiable, as demonstrated earlier. Then, using the rectangle tool, select the ROI in the cortex or the hippocampus.

In the toolbar, click on edit, then selection and specify tab changing the height and width to a predefined value. Adjust the box so that it is entirely covered by the tissue. Reset the brightness or contrast to the original brightness.

Duplicate the selected ROI by right clicking the box and clicking on the duplicate. A new window with the selected region will open. Rename the duplicated image to display the region it is located in.

Adjust the duplicated image type by using the toolbar and clicking on the image, then type in 8-bit keys to convert the duplicated RGB image to 8-bit, to best analyze the plaques. Invert the image by clicking on edit, then invert. To measure the 6E-10 positive area, go to the image, then adjust and threshold.

A predefined filter under the thresholding method will provide desired results, highlighting the strongest signals in red. After selecting the appropriate threshold, press apply. To analyze the 6E-10 positive area, use the toolbar and click on the analyze and analyze particles tabs, ensuring the summarize results is checked.

Copy the summary output with the percent area by clicking on the edit and copy tabs. Then, paste the summary output into the previously started Excel file with respective labels. Repeat the procedure for the different regions in the tissue, ensuring the placement of each box to outline the ROI is consistent between each image.

In this representative assessment, full and sub ROI analyses methods are compared to quantify the 6E-10 positive area in the cortex and the hippocampus brain tissues. The full ROI analysis involves outlining the entire ROI. In contrast, sub ROI analysis involves selecting a predefined region within the ROI.

The stepwise procedure for full and sub ROI 6E-10 positive area quantification, with ROI rotation for sub ROI quantification, are shown here. The correlation between the full and sub ROI analyses is demonstrated here. A significant positive correlation was observed between the 6E-10 positive area reported by the two readers performing the sub ROI analysis for the cortex and the hippocampus.

Further, the averaged sub ROI 6E-10 positive area shared a strong, significant positive correlation with the area obtained using the full ROI. For the mean 6E-10 positive area by the full in the sub ROI analyses, no significant difference was observed in the cortex and the hippocampus. A significant correlation was observed between whole brain homogenate and soluble amyloid beta 1-42 measurements, by Eliza, and full ROI analysis from the study Threshold selection is key in getting accurate data quantification.

User intervention is required to ensure the positive stains are accurately selected for with the selected filter. Apart from amyloid beta quantification, this method can be used for other fluorescent immuno-stains. For example, Iba-1, from microglial positive area quantification.