Skip to content

3 Guidelines For Setting Compensation Controls In Flow Cytometry Experiments

Written by Tim Bushnell, PhD

Fluorescence compensation is not possible without proper controls, so it is critical to spend the time and effort to generate high-quality controls in the preparation of an experiment.

First, recall that compensation is a consequence of spectral overlap, which occurs because the fluorescence emission spectra of essentially all fluorophores are wider in wavelength range than the optical filters that we use to measure those fluorophores.

Because of this, fluorophore emission will often overlap with more than one filterset on the cytometer, leading to the detection of the signal from one fluorophore by multiple detectors (i.e. spillover). The more colors measured within a single experiment, the more crowded the spectrum becomes and the more severe this kind of crosstalk is.

Compensation is a mathematical process that deals with this problem by removing a percentage of the total signal from each detector.

This percentage corresponds to the amount of signal spillover signal that is contributed to this detector by all the other fluorophores being used in the experiment. The compensation calculation relies on the fundamental concept that the amount of spillover of a fluorophore (e.g. fluorophore A) into a detector (e.g. fluorophore B) is defined by the ratio of A’s signal in B’s detector to A’s signal in its own detector.

This relationship between two detectors, the spillover coefficient, defines the spillover regardless of the amount of dye, so it can be used correctly for the spectral overlap in a typical experimental setting in which amounts of dye can vary widely between and within samples.

Given all of these points, the most important aspect of setting up a relevant, proper, and functional compensation matrix is to ensure that the spillover coefficient is accurate, is wholly reliant on good controls.

What Is A High Quality Compensation Control?

What does it mean for a compensation control to be “proper” or “good”?

The Daily Dongle, contains a much-cited and useful post, Three Rules For Compensation Controls and answers this question with three guidelines:

  • Each compensation control must be as bright as, or brighter, than the experimental stain.
  • Autofluorescence should be the same for the positive and negative populations used for the compensation calculation in each channel.
  • The fluorophore used must be the exact fluorophore (i.e. same molecular structure) that is used in the experimental sample.

Let’s look at each of these in detail.

Keep in mind that properly compensating a channel requires both a fluorescent, or stained population (for every fluorescent channel), and a nonfluorescent, or very dim, population.

These populations can either be present:

  • in a single tube (e.g. a lysed whole blood stained with a marker which will be present on only a portion of the total number of cells)
  • or, in separate tubes.

In the latter case, the controls would consist of (1) a single universal negative tube, used to designate the negative population in all channels and (2) a tube containing stained cells or beads for each channel.

Note that the single-stained controls may or may not contain negative cells. Regardless, when using a universal negative, the operator instructs the cytometry software to utilize the nonfluorescent population in the universal negative control and to ignore any nonfluorescent cells or beads in the single-stain controls.

3 Keys To Creating High Quality Compensation Controls

Dimly fluorescent populations tend to spread out (have higher coefficients of variation) when measured with flow cytometry

1. Account for brightness.

You may be wondering whether the compensation matrix may be irrelevant and inaccurate if compensation controls signal intensities are not exactly matched to the experiment’s samples.

The answer is a firm no: they don’t need to be matched. This is the beauty of compensation…

The spillover coefficient defines a ratio of interaction between two channels that is independent of the amount of fluorophore.

Another way of thinking about the spillover coefficient is that it defines the slope of a line that can be drawn between the nonfluorescent and fluorescent populations, connecting their medians, in an uncompensated plot of data from a single-color control.

The slope, or angle, of this line defines the amount of compensation required to correct the spillover between the two channels on the plots (see Figure 1 below).

Cytometer compensation required to correct spillover

The accuracy of the slope of the line described above is only as robust as the quality of the compensation controls used to generate it.

This accuracy can be compromised when the signal in the experimental sample is brighter than the signal from the compensation control for a given channel.

By nature, dimly fluorescent populations tend to spread out (have higher coefficients of variation). This is because fewer photons are measured from a dimly fluorescent population than they are from a brightly fluorescent population.

When a population is spread out in this way, there is uncertainty in the determination of the median, which will introduce uncertainty into the determination of the spillover coefficient (see Figure 2 below).

Spillover coefficient in cytometer

2. Account for autofluorescence.

Autofluorescence is an inevitable component of the total fluorescent signal in any channel.

This contribution has no effect on compensation as long as its extent is identical between the fluorescent and nonfluorescent populations used to calculate compensation.

However, the story is quite different if the autofluorescence intensity is unequal between these fluorescent and nonfluorescent populations (see Figure 3 below).

Autofluorescence intensity is unequal between fluorescent and nonfluorescent populations in a flow cytometry experiment

If the autofluorescence intensity of the bright and negative populations in a compensation control is augmented identically, both populations will shift on the scale of the channel to be compensated.

Nevertheless, the slope of the line that can be drawn between their medians is unaffected; therefore, the spillover coefficient and the compensation matrix will also be unaffected.

However, a change in the slope of this line will occur if the autofluorescence of only one of the populations is modulated, and this will impact the compensation matrix.

The bottom line here is to make sure that whichever cells or particles being used for a negative control or population have the same autofluorescence intensity in every channel as the cells or particles being used for the stained controls.

One common instance where this can be problematic is when generating a control for CD14 staining. CD14 is expressed on monocytes, which can be significantly more autofluorescent than other blood cells.

Therefore, if cells are used for compensation controls (e.g. lysed whole blood), then the autofluorescence intensity of the CD14-positive population will be more intense than the CD14- negative population.

This is a good situation for antibody capture beads, which are manufactured to have very consistent autofluorescence levels among particle types.

3. Match your fluorophores.

Finally, be sure that the fluorophore used to generate a compensation control is exactly the same fluorophore that is used in the experimental sample.

For example, avoid using an Alexa FluorⓇ 488-conjugated antibody to compensate for GFP. Even though similar, Alexa FluorⓇ 488 and GFP are different fluorophores and contain different emission spectra, so a compensation control prepared using Alexa 488 will generate a different compensation matrix than one prepared using GFP. Figure 4 below illustrates this difference in emission spectra between Alexa FluorⓇ 488 and GFP (spectra were generated using the BioLegendⓇ Fluorescence Spectra Analyzer)

Figure 4 illustrates the difference in emission spectra between Alexa FluorⓇ 488 and GFP (spectra were generated using the BioLegendⓇ Fluorescence Spectra Analyzer)

This extends further to tandem dyes like PE-Cy5, APC-Cy7, and the Brilliant Violet™ dyes, some of which can be tandem dyes.

Due to differences in conjugation efficiency between the donor and acceptor dyes, different lots of a particular tandem may differ in emission spectra and intensity, so make sure that compensation controls are generated using the same antibody conjugate that is used in the experimental sample. This is another situation in which antibody capture beads can be extremely useful.

Fluorescence compensation is not possible without proper controls, so it is critical to spend the time and effort to generate high-quality controls in the preparation of an experiment.

For a compensation control to be considered “good” or “proper”, each compensation control must be as bright as or brighter than the experimental stain, autofluorescence should be the same for the positive and negative populations used for the compensation calculation in each channel, and the fluorophore used must be the exact fluorophore (i.e. same molecular structure) that is used in the experimental sample.

To learn more about 3 guidelines for setting compensation controls in flow cytometry experiments, and to get access to all of our advanced materials including 20 training videos, presentations, workbooks, and private group membership, get on the Flow Cytometry Mastery Class wait list.

Tim Bushnell, PhD

BOOKS

Advanced Microscopy

Learn the best practices and advanced techniques across the diverse fields of microscopy, including instrumentation, experimental setup, image analysis, figure preparation, and more.
flow cytometry tablet eBook cover

Modern Flow Cytometry

Learn the best practices of flow cytometry experimentation, data analysis, figure preparation, antibody panel design, instrumentation and more. 

Advanced 4-10 Color Compensation

Advanced 4-10 Color Compensation, Learn strategies for designing advanced antibody compensation panels and how to use your compensation matrix to analyze your experimental data.

Top 40 Networking Scripts For PhDs

If you want to get replies from top employers and recruiters, this ebook is for you. These networking scripts will show you the exact words ...

Informational Interviews For PhDs

If you want to learn how to set up and execute informational interviews with PhDs working in industry, this ebook is for you. Here, you ...

Industry Resume Guide For PhDs

If you have a PhD and want to create the perfect industry resume to attract employers, this ebook is for you. Here, you will get ...

Top 20 Industry Jobs For PhDs

If you want to learn about the top 20 industry careers for PhDs regardless of your PhD background, this ebook is for you. Here, you ...

Salary Negotiation For PhDs

If you have a PhD and want to learn advanced salary negotiation strategies, this ebook is for you. Here, you will learn how to set ...

Top 20 Transferable Skills For PhDs

If you want to learn the top 20 transferable skills the industry employers ranked as most important for PhDs to include on their resumes and ...

Related Posts You Might Like

scientist sorting cells on paper

4 Factors To Improve Flow Cytometry Cell Sorting Speed

Written By: Tim Bushnell, PhD Cell sorting owes a lot to Mack Fuwyler  - when he developed the first cell sorter, he started a revolution. ...
Read More

5 Techniques For Dramatic Improvements In Reproducibility

Written By: Heather Brown-Harding, PhD It's not easy to improve reproducibility in your experiments. Image manipulation has become a major problem in science, whether intentional ...
Read More

3 Compensation Mistakes That Will Ruin Your Flow Cytometry Experiments

Written By: Tim Bushnell, PhD Putting it basically, compensation is the mathematical process of correcting spectral spillover from a fluorochrome into a secondary detector. Yet ...
Read More

We Tested 5 Major Flow Cytometry SPADE Programs for Speed – Here Are The Results

Written By: Tim Bushnell, PhD As a follow-up to our post on tSNE where we compared the speed of calculation in leading software packages, let’s ...
Read More

Understanding Reproducibility in Flow Cytometry – It’s the Antibodies!

Written By: Tim Bushnell, PhD Reproducibility is key to the scientific method. After the results of a study are published, the community validates the findings ...
Read More

3 Components Of Every Flow Cytometer You Don’t Know Enough About

Written By: Tim Bushnell, PhD All flow cytometer instruments have a certain 3 components you likely don’t know enough about. The way they are put ...
Read More