Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

Summary

This paper describes the quantification of hemocytometer and migration/invasion micrographs through two new open-source ImageJ plugins Cell Concentration Calculator and migration assay Counter. Furthermore, it describes image acquisition and calibration protocols as well as discusses in detail the input requirements of the plugins.

Abstract

The National Institute of Health's ImageJ is a powerful, freely available image processing software suite. ImageJ has comprehensive particle analysis algorithms which can be used effectively to count various biological particles. When counting large numbers of cell samples, the hemocytometer presents a bottleneck with regards to time. Likewise, counting membranes from migration/invasion assays with the ImageJ plugin Cell Counter, although accurate, is exceptionally labor intensive, subjective, and infamous for causing wrist pain. To address this need, we developed two plugins within ImageJ for the sole task of automated hemocytometer (or known volume) and migration/invasion cell counting. Both plugins rely on the ability to acquire high quality micrographs with minimal background. They are easy to use and optimized for quick counting and analysis of large sample sizes with built-in analysis tools to help calibration of counts. By combining the core principles of Cell Counter with an automated counting algorithm and post-counting analysis, this greatly increases the ease with which migration assays can be processed without any loss of accuracy.

Introduction

In vitro cell counting is an important basic technique in a wide range of tissue culture experiments. Accurately determining the number of cells in a culture is essential for experimental reproducibility and standardization^1,2. Cell counting can be performed manually using a hemocytometer as well as using a variety of automated methods, each with their own advantages and disadvantages^3,4,5. Most of the automated methods for cell counting belong to one of two classes, those that use the Coulter principle or flow cytometry. Coulter counters take advantage of cells electrical resistance to determine cell number and size. They are fast, accurate and cheaper than flow cytometers. However, they are rarely used for only cell counting due to their considerable cost compared to manual counting³. Flow cytometers, on the other hand, are expensive but they have many applications such as cell counting, analysis of the cells shape, structure and measuring internal cell markers^4,5. Machines that use either of these two principles are available from many manufacturers. Manual counting is affordable but time-consuming and subject to bias while the automated methods come with a fraction of the time required for the manual counting but using expensive machines⁶.

Other common cell culture procedures are in vitro cell motility assays, namely, cell migration and invasion⁷. Migration and invasion assays are commonly used to investigate cell motility and invasiveness in response to a chemotactic response. In addition, they are widely used to study embryonic development, differentiation, inflammatory response, and metastasis of multiple cell types^7-11. Cells that have migrated or invaded through the porous membrane of a migration assay can be quantified in two different ways. Firstly, by staining the cells with a fluorescent dye, dissociation from the membrane, and quantification using a fluorescent reader¹². A limitation of this method of quantification is that no record can be retained of the membranes and there is no possibility for further analysis¹³. The second quantification method is for migrated/invaded cells to be fixed and stained with fluorescent dye or more commonly, with cytological dyes such as crystal violet, toluidine blue dye or hematoxylin; then cells are quantified manually using inverted microscopic images of these membranes which is a very time-consuming task^12,13.

To overcome the drawbacks of manual cell counting, two reliable and accurate automated cell counters for cell concentration and for the migration assay were developed. These automated cell counter algorithms were developed for ImageJ as a plugin using Oracle's Java computer language. ImageJ is a public and widely-used image processing tool developed by the National Institute of Health (NIH)^14,15; thus, writing these plugins for ImageJ facilitates easy integration into the biological community.

Automation of cell counting ensures high throughput and reproducibility compared to manual counting. Although other available software and plugins can be used to calculate cell concentration through image analysis^5,16,17, Cell Concentration Calculator plugin is fast and can also handle dilutions of cells and treatments. Moreover, all results and calculations from these two counters can be saved and exported. The two plugins described in this paper are optimized for the use of a phase contrast microscope for live cell imaging and large field of view (entire membrane capture) imaging for migration assay membranes through the use of a dissecting scope. The plugins are freely available for download with installation instructions from: http://peng.lab.yorku.ca/imagej-plugins.

Protocol

1. Compound Microscope and Camera Setup (Cell Concentration Calculator)

1. Increase bulb brightness to full with the light adjustment knob, switch to the 4X objective lens, and ensure phase contrast filters are selected.
   NOTE: Any inverted phase contrast microscope for tissue culture with a dark background, e.g., PhP phase contrast, can be used following standard microscope and camera procedures.
2. Within the microscope's software, set image capture settings to default values.
   NOTE: Refer to the microscope's user manual to find the location of these settings.
   1. Set 'brightness', 'contrast', and 'saturation' to 100% and 'gamma' and 'gain' to 1.0.
      NOTE: Depending on the software, 'brightness' and 'contrast' may default to a value of 0% instead of 100%.
   2. Set images to be captured in black and white using the highest resolution available (1,600 x 1,200 pixels (px) or greater).
      NOTE: A 'saturation' of 0% is sufficient if a black and white setting is unavailable.
3. Place a standard hemocytometer onto the microscope stage and capture an image as depicted in (Figure 1A); this is the 'Volume Calibration image'. Adjust exposure timing as required.

2. Image Volume Calibration

1. Open ImageJ and from the Plugins menu, start the Cell Concentration Calculator (CCC) plugin, e.g., Plugins > Analyzer > 'Cell Concentration Calculator'.
   1. If the right-side 'Image Volume Calibration' panel is not visible, click on 'Calibrate' to show it.
2. In ImageJ, open the 'Volume Calibration image' from step 1.3 ('File' > 'Open') and in CCC click on the 'Get Image Dimension' button.
   NOTE: This will fill in both Image Width and Height text boxes with the image resolution in pixels automatically.
3. In ImageJ, select the 'Straight Line Tool' next to the selection tools and draw a straight line across the entire length of the hemocytometer primary (P)-square demonstrated in (Figure 1B) by clicking and dragging the cursor.
   1. Push the 'M' key to display the Results window containing the straight line measurements. Type the value from the Length column into the 'P-square Length' textbox in CCC (Figure 1B).
   2. Click on the 'Calculate Image Volume' button to output the image volume into the Image Volume textbox. Alternately, if the volume of the image is already known, type the volume in nL into the Image Volume textbox.
4. Click the 'Save' button.
   NOTE: The plugin is now calibrated.

3. Camera Exposure Calibration

1. Following cell harvesting for counting via hemocytometer, load 10 μL of cells into a chamber of the hemocytometer and place it onto the microscope stage.
2. Using the same settings from step 1.2, adjust the exposure time so that the background lines of the hemocytometer disappear.
   1. Adjust the focus so that the interior of the cells is darker than the cell membrane, indicating focus within the central cross section of the cell and not the poles.
   2. Further adjust the exposure so that the cells are not overexposed and resemble those depicted in (Figure 1C).
      NOTE: Slightly visible hemocytometer lines are acceptable. It is recommended to save or record these settings to maintain accuracy and reproducibility.

4. Image Acquisition

1. For each cell sample, load 10 μL into both chambers of the hemocytometer to increase statistical inference power². Place the hemocytometer on the microscope stage for imaging.
   NOTE: The resolution and magnification of each image must be the same as the 'Volume Calibration image'. The plugin counts all images of any selected folder; keep images to be counted together in the same folder.
   1. If a filename auto increment function is available, turn it on and make sure each image is not shown after capturing to increase throughput.
      NOTE: Manually saving and closing each image will drastically slow down the process. Refer to the microscope's user manual for information on the availability of an auto-increment function.
   2. Capture at least three non-overlapping images of the central region of the hemocytometer although more (5-10) is recommended to increase accuracy.
      NOTE: Avoid both the top and bottom areas of the chambers as cells tend to increase in density at both locations. Take the same number of images for every chamber. This is required for proper functioning of the plugin during counting.

5. Image Counting and Dilutions

1. In CCC, click on 'Count Cells' and observe the Choose Directory dialog box. Select a folder to be counted.
2. Observe the sample number input box after selecting a folder. Enter the number of images taken per chamber, i.e., 4.1.2, and click 'Ok'. The plugin will now count all the jpg, tiff, and png images in the selected folder in alphabetical order.
   NOTE: Clicking the 'Sample Viewer' button will bring up the Sample Viewer window displaying information about the counted samples. Sample concentration is the average concentration of all images taken per chamber. Samples with unitless concentrations can be added to this list, such as the addition of a drug or small molecule treatment.
   1. Recount the cell samples if the concentrations vary significantly within counts of the same samples (section 4).
      NOTE: To calculate dilutions for all the counted-samples, CCC automatically uses the formula C₁V₁ = C₂V₂.
3. Use the scenario of seeding 15,000 cells per 200 μL into 30 wells of a 96-well plate + 1 extra:
   1. Set the textbox to the right of the C2 label to 15,000 and the concentration volume textbox to 200, changing the adjacent combo box unit to 'μL'.
      NOTE: The plugin will ultimately calculate the concentration in cells/mL.
   2. Make sure the volume combo box has V2 selected (final volume) and in the textbox to the right enter 6200 (200 μL x (30 + 1)), selecting 'μL' in the volume unit combo box.
4. Click 'Calculate Dilution' to add the currently entered dilution to the bottom left list box.
   NOTE: For each dilution added, will be solved for each sample and displayed in the tree diagram to the right. Double click on each entry to expand.
5. Clicking the 'Save' button below the 'Sample Viewer' button to write to file all sample data and dilutions.
6. NOTE: These data can be recovered at any time by clicking 'Load' and selecting the saved file.

6. Migration and Invasion (Counter)

1. Perform the migration and invasion assays using the standard Boyden chamber method^7-9.
2. After cells have migrated/invaded, carefully remove the media within the insert by inverting and gently tapping. Wick away any excess media adhered to the bottom of the membrane by touching the edge to a paper towel.
   NOTE: Do not touch the membrane itself to the towel, this may dislodge adhered cells.
3. Fix and stain the cells as reported^7-9 in a 24-well plate set up with each row containing ~500 µl of a different solution, e.g., Fixative, Stain 1, Stain 2, and double distilled water (ddH₂O). Fill a second plate with 1x PBS to place the inserts in before cutting.
4. Wash the inserts by placing them into wells filled with ddH₂O and fill the insert with ddH₂O. Drain the water before swabbing away cells by inversion.
5. Use a clean cotton applicator to remove un-migrated/un-invaded cells from the top of the membrane taking care not to damage the membrane. Be thorough around the edges of the membrane.
6. Cut the membrane using a razor or a scalpel and carefully transfer the membrane (bottom-side up) onto a clean glass slide.
7. Add a small drop of mounting solution beneath and on top of the membrane and cover with a thin cover slip.
   NOTE: Avoid trapping bubbles within the mounting solution to preserve accuracy of the counts.

7. Dissecting Scope and Camera Setup

1. Turn on the microscope's light source and camera.
   NOTE: Refer to the microscope's user manual for detailed instructions.
2. Within the microscope's software, set image capture settings to default values.
   NOTE: If an averaging function exists, a value of four is recommended. This is a good compromise between the degree of averaging and image acquisition time. Likewise, a small degree of sharpening may increase image fidelity.
   1. Set 'brightness', 'contrast', and 'saturation' to 100% and 'gamma' and 'gain' to 1.0.
      NOTE: Depending on the software, 'brightness' and 'contrast' may default to a value of 0% instead of 100%.
   2. Set display (real-time) and capture resolution to their maximum settings (1,600 x 1,200 px and 2,592 x 1,944 px, respectively).
      NOTE: Display resolution can be adjusted as required if the refresh rate is too slow. Lower resolutions will make it more difficult to focus accurately but increase the refresh rate.
3. For the stage of the dissecting scope, use a solid white background; a black or glass background is insufficient.
4. Use the above-stage light source, preferably from two flexible LED lights to the right and left of the stage.
   NOTE: A below-stage light source will illuminate the pores within the migration assay membrane which may negatively influence the accuracy of subsequent counts.
5. Place a completed migration assay membrane slide onto the stage. Looking at the real-time image displayed by the software, adjust the magnification with the zoom adjustment knob so that the edges of a single membrane are just within the camera's field of view.
   NOTE: Placing the slide on a glass plate overtop the white background stage makes it easier to maneuver the slide for imaging.
6. Adjust the light source positions (7.6.1) and exposure times to reproduce as closely as possible the ideal image depicted in Figure 2A. Depending on the brightness, exposure times of 5-60 ms should be sufficient.
   NOTE: The goal is to produce an image with as little background color as possible and a uniformly illuminated membrane without reducing image fidelity, i.e., overexposure leading to a loss of visible cells.
   1. Position the left and right light sources at a low angle relative to the slide. This will help remove background stain and chromatic aberrations. Try to keep each light source directly opposite to the other.
      NOTE: While maneuvering each light source into position, turn the other off. This helps to center the area of illumination onto the membrane itself more easily and accurately.
7. Remove the slide and white balance the image using a single button click in the microscope software.
   NOTE: The microscope is now calibrated. Save as many settings as possible for future use and take note of the light source positions and intensity.

8. Image Acquisition and Flatfield

1. Within the software, set the capture folder location, and capture one image per membrane. Name the images following the general template of: Name - ###, e.g., Control - 001.tif, Control - 002.tif, Test drug - 001.tif, and so on.
   NOTE: For best image results, save the image file type as tiff over other lossy formats such as jpeg.
   NOTE: Images not following the general template will still be counted but will not be subject to automated grouping and flat fielding.
   1. If flatfield correction is desired, for each slide find an empty area and take a Blank image following the naming convention: Name - Blank.
      NOTE: A blank is an area on the slide that contains no membrane and represents the background illumination.
   2. Immediately before imaging, flatten each membrane by applying pressure over the coverslip and remove as many trapped bubbles as possible.
2. In ImageJ, go to Plugins and open the TC plugin; e.g., Plugins > Analyze > 'Transwell Counter'.
3. Within TC, click on the 'Flatfield' button and observe the Choose Directory dialog box. Select the folder where the membrane images were saved.
   NOTE: Only images saved with the general template above will be automatically flatfield corrected and saved in a new folder called Flatfield within the chosen folder. See Figure 2B for an example of a flatfield corrected image.

9. Configuration Settings

1. Open a migration assay membrane image in ImageJ ('File' > 'Open') and select Image > Adjust > 'Color Threshold…'. Observe the Color Threshold window to adjust what colors will be filtered out of the image.
   1. At the bottom of the window, set Thresholding method to 'Shanbhag', Threshold color to 'White', and Color space to 'RGB' (red green blue); uncheck Dark background if selected.
   2. Adjust the top sliders by clicking and dragging the markers to 0 and the bottom sliders to 255 (leave the bottom sliders at 255). Ensure that the image is fully white.
2. Adjust the green and red top sliders until only the nuclei are visible.
   NOTE: The settings selected will vary entirely upon the cell stain used. See Figure 2C.
3. In the TC plugin, input the values of the RGB top sliders into the associated Configuration Settings 'RGB Threshold' textboxes. Click the 'Add/Modify' button and overwrite the configuration.
   1. Leave the Size Range Lower and Upper values at 1 - Infinity.
4. Within the Configuration Settings panel, click 'Save' to write the settings to the hard drive.

10. Counting Images and Calibration

1. Open the TC plugin (8.2) and click on 'Count Folder' and observe the Choose Directory dialog box. Select the folder to be counted and wait for it to finish.
2. Each counted-sample is automatically added to the main table. Key columns are 'Count', 'Quality', and 'Calibrate?'.
   NOTE: The un-calibrated Count is the number of particles per membrane within the area displayed in the column 'Area range'.
   NOTE: Quality ranges from approximately -0.8 to 1.7; Q ≥ 0.5 is acceptable.
   1. Observe a checkmark in the 'Calibrate?' column if an image is flagged for calibration based on its resemblance to the ideal metrics.
      NOTE: Both Quality and Calibration may suggest that the current settings are possibly insufficient. If after proper 'Color Thresholding' and 'Size Ranges' have been selected and calibration is still suggested, inspection of the original and counted images should be the final determinant of a valid count.
3. Select All the Samples in the Table Flagged for Calibration.
   1. Right click in the table and select Recount > 'Suggested size'. This will recount the images with a suggested minimum particle area.
   2. Right click again and select 'Show Plot'. Observe the frequency scatter plot of particle areas. An ideal image will have a graph resembling a long right-tailed normal distribution, i.e., the bell curve. See Figure 3B.
   3. Adjust the lower Size Range, if required, by selecting the sample, right clicking, and selecting Recount > 'Manual settings'. Observe the manual settings dialog. Enter the desired settings and click Count to recount the image with the new settings.
4. To adjust the counts manually, select the samples, right clicking the table, and select 'Open image with counts'. Observe the original image with red markers representing each particle counted by the plugin.
   NOTE: Recount > 'Show counted binary image' can be useful to check how well individual cells are being resolved by the color thresholding.
   1. To add a count, hold 'Ctrl' and left click. Observe a marker at the cursor location that will be added to the samples total count. To remove a marker, right click the image. The plugin will remove the marker closest to the cursor.
   2. To remove a group of markers, use a selection tool in ImageJ to select a region of interest (ROI). While holding 'Ctrl', right click the image and all markers inside the ROI will be removed. Observe the cell number in the 'Count' column.

11. Saving/Opening Results and Exporting to CSV

1. In TC, go to the menu bar and click on 'File' > 'Save results'. Observe the Save Results dialog box. Choose a name and destination and click 'Save'.
   1. Use 'File' > 'Open results' to load a file containing all the data displayed in the main table, including the plot.
      NOTE: The results file saves the directories the images are saved in. If the original images are moved after saving, the 'Open original image' and 'Open image with counts' functions will fail.
   2. To reset the image directory, select the samples, right click the table, and select 'Reset image directory'. Observe the Choose Directory dialog box. Select the new folder and if the images exist, the directories will be reset. Re-save the results file.
2. To save a Comma Separated Values (CSV) file, in the menu bar go to 'File' > 'Export to .csv'. This produces a file with samples organized into statistical groups with the mean count and standard error of the mean; its layout is designed for quick graphing in common graphing programs.
   NOTE: The statistical groups are based on the groups created within TC.
   1. If the samples follow the general naming template, select the samples to be grouped, right click and select 'Auto grouping'. This adds samples with the same 'Name' to the same group. Using the example Control - 1, Control - 2, Treatment - 1, Treatment - 2: both controls would be added to the group 'Control' and treatments to 'Treatment'.
   2. Add samples manually to groups by double clicking the sample's 'Group' cell and typing in the group name. Select the samples to be added to this group, right click and select 'Add to group'.

Results

Cell Concentration Calculator

Figure 1 presents the overall process of CCC calibration and countable image acquisition. Figure 1A and 1B depict the P-square calibration image and calculation of P-square length in pixels. CCC determines cell concentration in a given volume using the formula:

Discussion

Critical Steps, Troubleshooting, and Limitations

The very nature of automated computational methods, specifically those of particle analysis, necessitates the mathematical ability to define these particles. Consequently, the accuracy of both Cell Concentration Calculator and migration assay counter is majorly dependent on image fidelity, that is, how closely the captured image resembles the cell sample or migration assay membrane. It is therefore of the upmost importance to follow microscope and ...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
HyClone Classical Liquid Media: RPMI 1640 - With L-Glutamine	Fisher Scientific	SH3002702	Cell culturing media
Fetal bovian serum (FBS)	GIBCO BRL	P00015	Media suppliment
HTR8/SVneo trophoblast cell line	Cells were obtained from Dr. Charles Graham (Queen’s University, Kingston, Canada)		Software is designed to work with any cell line.
Trypsin	GIBCO BRL	27250-018	Prepared as 0.20% (w/v) in 10 µM EDTA 1x PBS
Accutase	Innovative Cell Technologies	AT104
10 cm cell culture plates	SARSTEDT	833902	Any tissue culture treated plates will be suitable
Transwell Polyester Membrane Inserts - 8.0 µm Pore size	Costar 3422 ordered from Fisher Scientific	7200150	For 24-well plates; Pore size: 8.0 µm; 6.5 mm diameter; 0.33 cm2 growth area
HARLECO Hematology Stains and Reagents, EMD Millipore - Soluntions 1, 2 & 3	EMD Millipore and ordered from VWR	65044A, B, & C	Hemacolor stain set consists of three 500 ml (16.9 oz.) poly bottles & includes a methanol fixative (Solution 1), an eosin or acid stain (Solution 2), and a methylene blue or basic stain (Solution 3)
Cotton Tipped Applicator	Puritan Medical	806-WC
Single-edge industrial razor blades	VWR	55411 - 055	Thickness: 0.30 mm (0.012")
Microscope Slides - Precleaned/Plain	Fisher Scientific	12550A3	Dimentions: 25 mm x 75 mm x 1.0 mm
Fisherbrand Cover Glasses - Rectangles no. 1	Fisher Scientific	12-545E	Thickness: 0.13 to 0.17 mm; Size: 50 mm x 22 mm
Fisher Chemical Permount Mounting Medium	Fisher Scientific	SP15-500
Leica Stereo dissecting microscope	Leica Microsystems		The microsope is equipped with Leica microscope camera Model MC170 HD & camera software is Leica App. Suite (LAS E2) Version 3.1.1 [Build: 490]. Microscope parts:  LED3000 Spot Light Illumination Model: MEB126, Leica M80 Optic Carrier Model M80, Objective achromat 1.0X, WD=90 mm Model: MOB306 & Objective achromat 0.32X, WD=303 mm Model: MOB315, Video Objective 0.5X Model: MTU-293
Hemacytometer	Assistant Germany		0.100 mm Depth - 0.0025 mm2
Olympus inverted light microscope	Olympus Corporation	CKX41SF	The microsope is equipped with Lumenera Infinity 1-2 2.0 Megapixel CMOS Color Camera & camera software is Infinity analyze Version 6.5.2
Laminar flow cabinet 1300 Series A2	Thermo Scientific	Model: 1375	Any laminar flow cabinet for cell culture work will be suitable
Cell culture incubator	Thermo Scientific	Model: 370	Any cell culture incubator will be suitable - Cells were cultured under humidefied environment, 5% CO2, 37 °C
ImageJ	NIH	Version 1.50e	Minimum version required
Java Runtime Environment	Oracle	Version 1.8.0_66	Minimum version required