Rutgers Biomedical Engineering
125:315
Laboratory # 9:
2004
Cellular Property Measurements via Biomedical Imaging
and Microscopy
Developers:
Becky Hughey (rhughey@eden.rutgers.edu)
Eric Wallenstein (ejw42@eden.rutgers.edu)
Faculty Instructors:
Prof. P. Moghe (moghe@rci.rutgers.edu)
Introduction:
Lab Subsection 1: Cell Imaging: Viability Study Using Calcein and Ethidium Homodimer
Many methods exist to visualize and quantify characteristics of cells. In this lab section cell
viability will be studied.
In every living cell there are general and unique enzymatic activities that define cell viability
and function. Within viable cells, cytoplasmic esterases can cleave calcein-AM, resulting in
the emission of a green wavelength signal when excited by a UV light source. However, if
these enzymatic reactions are inhibited, i.e. following the introduction of toxins into the cell
cytoplasm or through the permeation or degradation of internal membranes, necrosis (a type
of cell death) will ensue. Furthermore, following cell membrane disruption or compromised
cell integrity, another compound, ethidium homodimer-1, will have access to nucleic acids
within the nuclei of these dead cells to produce a vibrant red fluorescent color.
Lab Subsection 2-1: Image Quantification: Monitoring Cell Differentiation
Depending on their overall health, activity, and environmental conditions, cells in
culture/experimental regimes can display wide morphological ranges. For example, by
applying sequential addition of growth factors, embryonic cells can be induced to express
various differentiated cell types, each with unique cell shape characteristics. Differentiation
can then be followed in such systems, through the classification of differentiated states based
on measurable morphological characteristics.
I. Purpose:
Lab Subsection 1: Cell Imaging:
In this lab, cell population viability will be assayed through the use of a calcein/ethidium
homodimer stain. Live cells will stain green due to calcein binding, and dead cells will stain
red due to ethidium homodimer binding to nucleic acids. Total cell population and percentage
dead cells will be obtained using the Microsuite software package, quantifying on the
parameter basis of color and cell diameter.
Total cell population  # cells expressing both ethidium homodimer and calcein
Percentage dead cells 
# ethidium homodimer stained cells
Total cell population
Lab Subsection 2: Image Quantification:
During this subsection, different morphological cell configurations will be quantified,
compared, and related to function. In one system, differentiated embryonic stem cells will be
quantitatively characterized based on major and minor cell axes measurements. The
characterization scheme obtained from these measurements will then be used to classify cell
populations as differentiated, or undifferentiated.
II.
Materials:
Lab Subsection 1: Cell Imaging:
The viability assay will be performed using previously acquired images of calcein/ethidium
homodimer staining.
Quantification for the viability assay will be performed using the Microsuite software package.
Cell counts will be performed on the basis of color as well as cell size.
Lab Subsection 2: Image Quantification:
Quantification of cell phenotype and morphology will be performed with the Microsuite
software package.
III. Methods and Data Collection:
Lab Subsection 1: You will be using cell imaging software to quantify
the viability of a certain population of cells.
The following procedure is used for counting the dead cells in the entire picture. The first
image you will bring up and analyze contains cells previously stained with calcien and
ethidium homodimer-1. These cells were imaged on the epifluorescence microscope in A209.
Open Olympus MicroSuite software from the desktop.
1. From File toolbar, open <My Documents/lab6_microscopy/Images/live_dead> and
open the DEAD image.
This will open the image on the screen and place it in the image manager on the left side
of the screen. The image manager allows you to keep many images at the ready and
toggle between images. (i.e. you don’t have to open and work on one image at a time).
Next, in step 2, you will create a new toolbar that will contain items we will refer you to in
the course of the lab.
2. Open Special menu and select Edit Button Bars; Put a check next to Analysis and
click OK.
You will set color thresholds so that the program can select cells from the background
3. Go to the Measure menu and select Pixel Value
4. Click on two different cells and once on the black background
5. Right click and end the quantification process; Click Yes to stop measurements
This will give you the red, green, and blue values of the pixel in chart form. These values
will be used as starting points for color thresholding
6. On the analysis toolbar click the Set Color Threshold icon
7. Click the Window button in the Preview; move the box around and enclose a region
with a good number of cells
8. Right click to lock the box in place
9. Select All in the Preview box
10. Put the representative minimum and maximum pixel values for each color obtained
from the Pixel Values Sheet into the slider bar boxes for the representative color;
Click OK
11. Adjust the values in the boxes so that the cells in the window become completely
colored
12. Save the Pixel Value data sheet that you generated to the desktop to later e-mail to
yourself
The color thresholds are now set up and you can identify the cells from the background
You will now set up a filter to sort the cells by diameter
13. Go to the Measure menu again and select Arbitrary Distance
14. Use this tool to measure the diameter of a cell
15. Repeat for two more cells
16. Right click and end the quantification process; Click Yes to stop imaging
This will give you an idea of the range of diameters you will incorporate into your filter
Next you will create a classification scheme to detect dead cells in the picture
17. On the analysis toolbar click on the Define Classification icon
18. Put the name DeadClass into the New Classification box and click New
19. Click on the Units button and select Pixel as Basic Unit. Pick Normal so that your
units are pixels – a measure of distance. Click OK.
Note: if you wanted to use area as your selection criterion, you would use pixels2 since
these are units of area, not distance.
20. Click on the Compute button
21. Set min at the lowest value from the sheet obtained using Arbitrary Distance
calculations
22. Set max at the highest value from the sheet obtained using Arbitrary Distance
calculations
23. Set bins at 5 (this creates 5 categories of cell sizes from the values you entered)
24. Click OK to close the window and accept the scheme; Click OK on the Define
Classification box.
You will now specify which measurements we want computed for the items that are
detected by your classification scheme.
25. On the analysis toolbar click on the Define Measurements icon
26. Select the particles tab. ID Class and ID Particle will already be selected
27. Select Area and Diameter Mean as measurements
This will show you the mean diameter as well as the area of the cells you detect.
28. Click OK
You will now specify the criterion you want to sort by (in this case you will pick diameter
since you specified pixel and not pixel2 in the Define classification section) and using the
subdivisions you set up (DeadClass as specified in the Define Classification menu).
29. On the analysis toolbar click on the Define Detection icon
30. Click on Detection Tab and make sure the ROI box is not checked. Instead select
Frame
This will allow you to analyze the entire picture.
31. Click on Classification tab
32. Select Diameter Mean as Criterion
33. Select DeadClass as Classification
34. Select Outline as the style
35. Select ID Particle as the Measurement label type
36. Click OK
37. On the analysis toolbar click on the Detect icon
38. On the analysis toolbar click on the Particle Results icon
This will put all your results on a spreadsheet. Notice how various groups are outlined
in different colors, corresponding to the values in DeadClass. You can also export to
excel and remove data with no ID Class (not colored).
Review your spreadsheet.
How many particles that fit into your classifications where found.
39. Save the image of the measured picture, as well as the sheet of results obtained for
Particle Results, not from ROI Results, to the desktop to later e-mail.
40. Now repeat this procedure (steps 3-39) to image live cells.
Go to <My Documents/lab6_microscopy/Images/live_dead> and open the
LIVE image.
Lab Subsection 2: In the previous subsection, we quantified the
morphology of all cells that fell within a certain region. In the next subsection we will manually select a few individual cells and measure their
morphometric properties.
Go to <My Documents/lab6_microscopy/Images/differentiation> and open the
differentiated image
Because this is not a fluorescent image you will have to reset your color thresholds.
1. On the analysis toolbar click the Set Color Threshold icon
2. In threshold slider boxes set minimum to 0 and maximum to 255 for all three colors.
This will allow the program to analyze all cells
You will now create regions of interest (ROI) around individual cells to analyze.
3.
4.
5.
6.
7.
On the analysis toolbar click the Define ROI’s icon
Select the Pencil Tool (freehand polygon).
Left click and hold down to encircle a cell.
Right click to close the outline
Repeat this process (4-6) two more times
This will define three ROI’s
8. Make sure the regions you created are selected and click close.
This does not mean that your regions have been lost. They are still being stored
somewhere in the program.
You will now select the parameters to quantify.
9. On the analysis toolbar click on the Define Measurements icon
10. Click on the ROIs tab.
11. Select Area ROI, and Diameter Mean ROI.
12. Click OK.
13. On the analysis toolbar click on the Define Detection icon
14. On the Detection tab, select ROIs as the Search Area.
15. On the Classification tab, set Criterion to No Classification.
16. Click OK.
17. On the analysis toolbar click on the Detect icon
18. On the analysis toolbar click on the Frame ROI Results icon
The ROI data is presented for the specified parameters, with the ROI listed as the row
variable, and the parameter listed as the column variable.
Save the spreadsheet (that which is accessed using the button for ROI results) and
images of the selected cell populations on the desktop to later e-mail.
Having learned two ways to calculate parameters of cells, quantify the following properties
using a Classification method of your choice.
1. Maximum diameter
2. Elongation
3. Orientation
You will analyze the image entitled Undifferentiated, found at <My
Documents/lab6_microscopy/Images /differentiation>
Save the image of the measured picture as well as the data sheet of results obtained
using one of the above classification methods on the desktop to later e-mail.
Lab section 3: To view the staining of cytoskeletal components in the
cell we will make a composite image.
Open the images from <My Documents/lab6_microscopy/Images/composite/Phalloidin>
and <My Documents/lab6_microscopy/Images/composite/Phase>
Here the image manager allows you to open both images at one time and toggle between
them.
1.
2.
3.
4.
5.
Find the Define Fluorochromes icon (painters pallet) in the upper toolbar and click
Click deselect all
Select <Phase Contrast> and FITC
Click OK
Go to the Define Fluorescences icon (next to Define Fluorochromes icon)
6. Put a check in the box for both <Phase contrast> and FITC (You may need to add
FITC as a new target.)
7. Click OK
8. Highlight both images – click on one, then hold shift and click on the other
9. Go to Create Composite image icon (to the right of the Define Fluorescences icon)
10. Define the type of fluorescence for each image in the fluorescence drop down window;
Phalloidin = FITC, Phase = Phase contrast
11. Put a check in the box for both pictures that comprise the composite image
12. Highlight the phase contrast image
13. Check the blend with composite image box
14. Click on switch view drop down menu and select composite image view
15. Adjust weighting of each picture in the composite
16. Click OK when the desired picture is obtained
Save the image of the composite picture on the desktop to later e-mail.
IV. Questions and Discussion:
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How many live and dead cells were found in the live-dead assay section?
Differentiated cells typically decrease in size, and obtain a more spherical shape.
What is the trend in area and maximum diameter seen between differentiated
and undifferentiated cells?
Why did you choose pixel as the basic subunit of measurement? What defines
the specific size of an individual pixel?
How does creating a composite image help in your understanding of the
cytoskeletal system in a cell?
What is the principle behind fluorescence microscopy?
Turn in all printed sheets and pictures.
References:
Lecture Notes by Professor P. Moghe
Schloss, R.S., Vitolo, J.L., Moghe, P.V. (1999). Flow-mediated cell stress induction in adherent
leukocytes is accompanied by modulation of morphology and phagocytic function. Medical and
Biological Engineering and Computation; 37: 257-263.