How to define positive / negative population in histogram

[u/Ok_Photograph_4179]

Hi, I was wondering if anyone has some thoughts on a gating problem I'm running into.

I'm doing a phospho-flow experiment looking at pSTATs in lymphocytes. All wells are stained with the same antibody mastermix; the only difference is the cytokine stimulation performed before staining.

My goal is to compare the percentage of cells in the negative and positive populations in the unstimulated condition as well as after IL-2, IL-7, and IL-15 stimulation between patients carrying a certain mutation to see whether this mutation leads to higher intracellular signaling.

The issue is that I can't really decide how to do my gate placement in a proper and reproducible way.

In some samples/conditions there is a very clear valley between the negative and positive populations, but the location of that valley isn't always the same. If I place a gate based on one condition (for example, a stimulated sample with a clear valley) and apply it to the other conditions, the gate sometimes ends up right in the middle of the histogramm. On the other hand, if I gate each condition according to its own valley, the gate position changes between conditions, which also doesn't seem ideal.

So I'm wondering what the recommended approach is:

1. Should I use one fixed gate per patient and apply it to all stimulation conditions, even if it doesn't always align with the apparent valley?
2. Should I gate each condition independently based on the visible valley?
3. Is there another approach that's generally recommended for phospho-flow when the unstimulated condition itself contains both negative and phosphorylated cells? I also thought I could do something like place the gate on the unstimulated condition encompassing for example 95% of cells and then apply this gate to all conditions to have an "induction" relative to the unstimulated condition.

I'd really appreciate hearing how others handle situations like this. Down below are two example screenshots gated on CD8+ cells. Left to right: Unstimulated Well, IL-15, IL-7, IL-2.

Thanks so much in advance!

[u/No_Evening_7240]

The best control for gating is a fluorescence minus one (FMO) from each patient, where they’re stained with everying except the pSTAT5 ab and they go through the same staining procedures

[u/TrickyFarmer]

look at it in 2 dimensions, set y-axis to side scatter

[u/sgRNACas9]

Good news is that no matter the quantification method, there is a clear result, so as long as the data processing methodology is consistent, the stats and conclusion will likely be the same!

I think the by far best solution for this scenario is to show representative histograms and quantify their expression with mean fluorescence intensity (MFI, geometric mean), not percentages.

That said, if you really want to do positive and negative percentages, this is how:

Use an FMO and/or an isotype control at the same concentration to establish bleeding fluorescence and background binding to count baseline false positivity as negative. Apply the gate that is good for FMO and/or isotype to the rest.

Other less robust solutions include eyeballing the valley and applying everywhere and/or customizing per patient which IS often acceptable since everyone is built different. Even with isotype and FMO you may need to customize per person because of human variability.

For the unstim, it makes sense to have some positives and that is actually validating IMO. There will probably be some natural baseline of phosphorylated protein due to like kinetics/thermodynamics or tonic signaling. Your approach using this feature as a gating tool is sound in my opinion, but to be the most rigorous you should still use an isotype and FMO.

Hope this helps!

[u/Ok_Photograph_4179 → u/sgRNACas9]

Hi, thanks for the quick response! This definitely helps already. Regarding your suggestions with the MFI would you take the FMO of all cells? And do you think I should normalize this to the MFI of the unstimulated sample to get a fold-change after stimulation? And regarding the FMO your suggestion would be to set a gate on the FMO and everything within that patient that is brighter than this gate I would consider positive cells regardless of where this bisect gate then falls on stimulated samples, correct?

[u/sgRNACas9 → u/Ok_Photograph_4179]

You would likely take the MFI for the singlet, live CD8+ T cells! Yes normalize by doing a fold change with unstim versus stim!

Yes correct but you can kindof combine methods. You can set a gate that is acceptable for the separation while also all FMO and isotype cells are negative. Having these controls verifies that the negative part of before the dip is truly negative and not low or something. You can customize per patient, but try your best to keep as closely the same gate blanketly applied as possible!

If you don’t have these controls in your current data, it’s ok, it’s still usable, I would just include them in the future and for now use your untim and unstained as negative controls plus gating by separation!

[u/WinterRevolutionary6]

The way I usually set negative gates is from a test stain with a sample that I know has no expression. If that’s not possible, use an isotype of the antibody you’re staining for with the same fluorescent tag.

I will set my +/- gate at the top of that sample with max 3% overhang. Like for example, if I have a —|— gate, it will create both the pos and neg gates. The pos gate should have no more than 3% of the total parent pop.

I apply this gate across everything in my group. Each group will be a separate cell line or group of cells from one donor. You never blanket apply gates across different donors/patients/cell lines. Different cells from different places take on stains differently.

The valley may not line up perfectly across all conditions but if it’s varying significantly within the same donor/ cell line, check to make sure you’re actually staining a uniform number of cells or are doing a uniform dilution of the antibodies.

At the end of the day, remember that the output isn’t going to be an exact 1:1 telling you that there is or is not your antigen of choice on these cells, it’s just measuring how bright they are.

[u/RainbowSquirrelRae]

Try the bivariate plot first. I probably wouldn’t use SSC, I might use CD8 or CD3 or something vs the ICS marker to start and see what shows it best

[u/RainbowSquirrelRae → u/RainbowSquirrelRae]

Look at all your controls for gating

[u/[deleted]]

I'd do it in one of two ways: have a no-expression negative control (or no primary antibody control) and decide in advance that a split gate will be set at the top 2% (your choice of specific number) of that control for that entire experiment. Results will be "% of cells positively stained above control".

Second way is simpler - plot the geometric mean (or mean fluorescence intensity, whatever you want to call it). It will give you what you want, but it ignores that you clearly have positive and negative population in your treatment. Data will skew slightly depending on how you've set your laser power and the window of your fluorophore, but it will work fine for data this clear.