We standardised a way of counting cell colonies from CFU experiments with the ImageJ software. It is important to have the colonies well stained with crystal violet and photograph the plates with a camera from a fixed height.
Photos should be then, treated as follows:
- Adjust the color threshold of the image on Image > Adjust > Threshold
- Hue: 163-255
- Saturation: 46-255
- Brightness: 0-255
- Thresholding method: Default
- Threshold color: B&W
- Color space: HSB
- Then convert the image to binary on Process > Binary > Make binary
- Fill holes on Process > Binary > Fill holes
- Separate colonies on Process > Binary > Watershed
- Save it as binary
- Count colonies on Analyze > Particles; Parameters here may vary with the cell line
- For G361 colonies we usually count colonies with a size (pixel2) of 100 – Infinite; a cicularity of 0 – 1
- For A375 colonies we usually count colonies with a size (pixel2) of 200 – Infinite; a cicularity of 0 – 1
- To optimize the counts one can:
- Identify a few colonies with the minimum number of 50 cells and adjust the size value
- Count manually the colonies using the multi-point selection tool and then analyse particles until get similar colony numbers
- Save the Summary as a txt file and open it as a spreadsheet to get the results
- Transform the counts dividing them by the number of seeded cells to get the plating efficiency
- Transform the plating efficiency dividing all values by the average of the controls’ triplicates to get the relative plating efficency
- Perform an ANOVA with a Bofferoni multiple comparison as a post-test on the relative plating efficiency to find out if differences between treatments are significant
- Paste data on a “Column” type spreadsheet, each column being a treatment/experimental condition and each line being a replicate
- Perform the ANOVA clicking on “Analyze” icon
- Choose on “Column analyses” “One-way ANOVA”
- Choose then “Repeated measures ANOVA” as a test and “Bofferoni: compare all pairs of columns” as a post-test, select the column of descriptive statistics for means and averages
- If there are significant differences, reflect them on the graph.