Measuring Cell Fluorescence using ImageJ
Image J can be downloaded for free from here .
This guide can also be downloaded as a complete PDF here: Measuring Cell Fluorescence using ImageJ
Here is a very simple guide for determining the level of fluorescence in a given region (e.g nucleus)
- Select the cell of interest using any of the drawing/selection tools (i.e. rectangle, circle, polygon or freeform)
- From the Analyze menu select “set measurements”. Make sure you have AREA, INTEGRATED DENSITY and MEAN GRAY VALUE selected (the rest can be ignored).
- Now select “Measure” from the analyze menu or hit cmd+m (apple). You should now see a popup box with a stack of values for that first cell.
- Now go and select a region next to your cell that has no fluroence, this will be your background.
NB: the size is not important. If you want to be super accurate here take 3+ selections from around the cell. - Repeat this step for the other cells in the field of view that you want to measure.
- Once you have finished, select all the data in the Results window, and copy (cmd+c) and paste (cmd+v) into a new excel worksheet (or similar program)
- Use this formula to calculate the corrected total cell fluorescence (CTCF).
NB: You can use excel to perform this calculation for you.CTCF = Integrated Density – (Area of selected cell X Mean fluorescence of background readings)
- Make a graph and your done. Notice that in this example that the rounded up mitotic cell appears to have a much higher level of staining, but this is actually due to its smaller size, which concentrates the staining in a smaller space. So if you just used the raw integrated density you would have data suggesting that the flattened cell has less staining then the rounded up one, when in reality they have a similar level of fluorescence.
How to Cite this if you wold like to:
I used this method in this paper here:
Burgess A, Vigneron S, Brioudes E, Labbé J-C, Lorca T & Castro A (2010) Loss of human Greatwall results in G2 arrest and multiple mitotic defects due to deregulation of the cyclin B-Cdc2/PP2A balance. Proc Natl Acad Sci USA 107: 12564–12569
But you can also find a similar method published here:
Gavet O & Pines J (2010) Progressive activation of CyclinB1-Cdk1 coordinates entry to mitosis. Dev Cell 18: 533-543
And here:
Potapova TA, Sivakumar S, Flynn JN, Li R & Gorbsky GJ (2011) Mitotic progression becomes irreversible in prometaphase and collapses when Wee1 and Cdc25 are inhibited. Mol Biol Cell 22: 1191–1206
And my apologies to any others that I have not mentioned.
Hi, I find your post very relevant for my project. However, my cell nuclei were stained by DAPI, and my protein-of-interest was stained with Alexa Fluor 488. I am trying to quantify the amount of this protein within the nucleus. Could you give me some advice on this? Thanks!
Hi, this method works with any flurophore, be that DAPI, 488, 555, FITC, Texas Red etc etc. If you want to only measure the nucleus of a cell, then when you draw your region, just limit it to the nucleus. This method is good for gathering data on individual cells, and I normally find that a minimum of 25 is needed to get any meaningful stats (but more cells is always better). If your more interested in the whole population, then you might be better off using a threshold method which could give you the average intensity across the whole field very quickly. Just make sure what ever you do you use identical acquisition settings for every sample. Overall, quantifying IF images is perhaps a little subjective and open to user input, but it can still be a useful tool. I hope that this is of some help. If you still need further clarification let me know.
But in my case, should I separate the RGB stack into individual fields, and then measure the green and blue channel staining intensity separately? With blue channel of DAPI alone staining as background, and then use the formula as shown by you?
Thanks for the help, I am a complete beginner in this!
Hi, you need to measure each channel separately. The background measurement should be taken from an empty region on the same channel, just adjacent to the sample of interest, in your case the nucleus. You can, then also measure the DAPI staining (in the same way) if you like as well, but I’m not sure if this is really necessary. If your only interested in determining if your protein (488 channel) increases/decreases�then you only need to measure that channel. So in summary yes you need to separate the channels, and measure them independently! Good luck
Is there a way to use ImageJ to calculate the mean fluorescence in a given field? Or will it only work for single cells?
You could use this same method but instead of selecting a single cell, you could select the whole field using for e.g. the rectangle tool.
how doyou change your RGB picture to 16bit pixels only picture?
This is so useful! Thank you very much!
Hi I am a complete beginner at using imageJ. Would I be able to use this method for comparing the intensity of alexa flurophore 488 inside the nucleus with the intensity at the periphery of the cell in order to see if the protein had moved to a different location in the cell? If so how would I go about doing this?
Any help would be appreciated. Thanks
Hi Dani, yes you should be able to use this method to do what you want… just include an extra step for the cell periphery. my suggestion is to try drawing around the total cell and then the nuclear fraction, take reading for both, correct each for background as per formulae and then divide one by the other to create a nuclear:cytoplasmic ratio, which over say 20+ samples you hopefully will be able to get some statistical relevance.
Good luck
Andrew
Hi Andrew, I wanted to ask if you have ever used size exclusion when doing your analysis in ImageJ. If you have, how do you set the scale for your maximum size?
Hi Kelly, sorry I have not done any size exclusion with image J so I’m afraid I can’t offer any advice. Good luck
Andrew
Hi Andrew,
I was using Imaris before to quantify my confocal images and beside the value of the fluorescence of a defined area, it was giving me also the size of the area, is it possible to evaluate that in Image J? (by giving him a scale in um before of course).
Thanks in advance
Cedric
Yes you should be able to do this in imageJ. First set the scale of the image by going to the menu item Image>Properties.
Then go set the type of things you want measured by going to the menu Analyze>Set Measurements. Here you can select a whole heap of different parameters to measure area being one of them !
Good luck
Andrew
this is what I searching for, thanks for sharing!
Greeting from Taiwan
Cathy
Hi Andrew. Thank you so much for your helpful post. I am a beginner with ImageJ, so I was hoping you could answer a question for me. My cells are stained with Bodipy (specific to lipids) and DAPI for the nucleus. I’m trying to measure the average fluorescence of the lipid droplets in the cytoplasm. How do I subtract the fluorescence emitted by the DAPI? Thanks!
You should do the quantification on the image before you compile all the channels together. Most microscopes should acquire each channel as a separate image. If you have a good microscope then it should cut out most of the bleed thru, also I find acquiring the Dapi last helpful, as the blue light can often bleach the other channels a bit.
Hope this helps
Andrew
Thanks! That does help a lot! I have the green fluorescence images, so I should be able to do that. Do I need to convert the image to an 8-bit black and white prior to starting the measurements? Also, if all the cells are different sizes, do I have to subtract the area of the nucleus since I’m only interested in what’s in the cytoplasm?
Not sure it has been along time since I came across a camera that took colour pics, most are greyscale. It should be fairly simple to test if conversion makes a difference to the reading but my guess is that it won’t. As for the nucleus subtraction that is really up to what it is exactly that you want to measure. I would start with the simplest setup and see if the data corresponds to what you see visually. Then add complexity if needed to improve the readout quality if needed.
Hi Andrew,
I found your article very useful, thanks a lot for posting on this topic! I’m also a beginner in ImageJ.. I would like to calculate nulcear/cytoplasmic fluorescence intensity ratios on my cells. I suppose, I’ll use a simple circle tool, and put down circles in the cytoplasm and in the nucleus in case of many cells and than calculate the average. This might be very simple, but I don’t see how I could set the size of the circle tool to be constant. Otherwise I need to create circles by hand all the time, and if the size is not the same, then the whole thing will get far away from being representative..
Thank you so much for the answer!
I have not yet figured out how to set a constant size, but there are two work arounds. First you can move the circle that you set up on the first image around the first image and take all your readings. Next copy and paste that circle onto the next image, then hit the delete (backspace) and it should just delete the pasted image but leave the circle, so you can then repeat the same process.
This is ok for a few images but its easy to accidentally delete or loss the circle tool.
Thus I think you maybe better off, making the readings independent of size by using the formulae in the guide to correct for both background and size of the area that you select. This way can draw any size circle, or even perhaps select the whole cell, and then then subtract the nucleus. I suggest having a bit of play to see which method/s give you the best/most accurate looking data.
Good luck
Andrew
Hey, great article. Just had a quick question, I am comparing fluorescence between different samples and using the entire field. So the area fr each sample is the same. When I go to calculate my corrected total cell fluorescence, i get some negative values. Is there a way I can adjust for this?
Hi, this method is specifically designed for single cell analysis, so applying it to a whole field probably won’t work and thus the negative values. If you just want a whole field then you are better off using a threshold over the whole field as this will be faster and probably more accurate… but won’t give you individual cell info.
Good luck
a
I am a beginner in imageJ and i have a question. Am I able to use this to quantify the fluorescence in a given field? I am not interested in individual cell data. Will this method be accurate and if not do you have any suggestions on what I could do?
Hi,
This method is specifically targeted at single cell analysis, and is probably not the best method for whole field quantification. I would look into the use of thresholds to do what you want to do.
Unfortunately I am not able to help you out with that method as I don’t know how to do it…sorry but good luck
a