What is compensation and when should you do it?
In this first of 3 blog articles, we will discuss the principles of compensation, as well as why it is important, and how to perform compensation. Subsequent articles will discuss the rules that must be followed for proper compensation and some of the common compensation myths that permeate the field. It all begins with an understanding of the process of fluorescence.
After excitation, a fluorescent molecule emits a photon. This photon has an emission maximum — that is, the most probable photon wavelength that will be emitted. However, this emission is not so specific, and there are a range of photons that can be released from the molecule. This can be modeled with a variety of software. A typical emission profile for a common fluorochrome, fluorescein, is shown in Figure 1.
Figure 1: Fluorescein emission profile.
As can be seen from this spectra, Fluorescein has a maximal emission of about 524 nm. However, it has a very long tail, and there is a chance (albeit small) that a photon of over 600 nm can be emitted by this molecule. Fluorescence happens in the nanosecond range, so while the cell traverses the excitation source in microseconds, each fluorescent molecule has the chance to go through the excitation/emission cycle multiple times. Thus, with each cycle, the independent emission of a photon occurs.
If one is looking at cells labeled with a single particle, this is nothing to consider. It only becomes important when cells are labeled with multiple fluorochromes with overlapping emission spectra. This can be visualized using the ImageStream®, as observed in Figure 2. This data is courtesy of Dr. David Basiji.
A. Uncompensated Cells
B. Compensated Cells
Figure 2: Demonstration of the results of compensation using the ImageStream®.
Cells were labeled with 4 different fluorochromes, and run on the ImageStream®. The uncompensated data is shown on the top. After compensation is properly calculated and applied, the spillover from one fluorochrome is corrected for, and measured only in the proper channel.
This is why compensation is so important. Otherwise, it is impossible to make an accurate measurement of the single fluorochrome in the presence of multiple fluorochromes.
There are several different methods to compensate. In 2011, the New England Cytometry users group hosted a one-day meeting to discuss these concepts. You can still download the talks from this meeting at the link above. For the purposes of this article, we will consider 3 methods: Non-pensation, manual compensation, and automated compensation. The idea of spectral unmixing (spectral compensation) is gaining traction with the proliferation of spectral cytometers, but will be subject to a separate blog.
Non-pensation is the concept of not compensating the data. Instead, non-pensation takes advantage of 3 factors: a wide dynamic range of a detector, a fixed voltage PMT, and a visualization tool that allows the very accurate drawing of gates.
This process was demonstrated on the Accuri™ flow cytometer (now part of BD Bioscience), a fixed voltage flow cytometer with 4 fluorescent detectors, and a wide dynamic range. Additionally, the software has a magnifying tool, allowing very precise positioning of gates.
Data was collected from multiple different sample types, from multiple cytometers, all of which were set up and locked down the same way. The results are shown in Figure 3.
Figure 3: Uncompensated FITC and PE data from multiple samples and multiple machines showing the location of the single and double stained gates for this system. Data courtesy of Claire Rodgers.
As can be seen from this data, the location of single stained fluorochromes is consistent and predictable for instruments with the characteristics of these systems. This data is from the early 2010s, so the specifics of the newer instruments may have changed, but the principle is the same.
This method is limited in implementation, and ultimately not recommended.
2. Manual Compensation
During the early years of multicolor flow cytometry, where most researchers were using 2-4 fluorochromes, manual compensation was the vogue method to correct for the spillover of a fluorochrome into secondary detectors.
The process started by placing the unstained cells in a box in the lower left corner of the plot (the first decade) and placing a quadrant on this plot. Single color controls were run, and a slider bar (or equivalent) was used to adjust the compensation. This is shown in Figure 4, which was taken from the FACSCalibur Users Manual.
Figure 4: Manual compensation. By adjusting the percentages, the positive sample was adjusted to below the quadrants.
This technique — “Cowboy Compensation”, coined by Joel Sederstrom (he’s the one I first heard using this term) — is illustrated with data generated in FCS3.0 in the figure below.
Figure 5: Cowboy Compensation of the signal in the primary detector (B530/30). The black line represents the ~median of the negative population.
Following this method, samples are often overcompensated. This is especially true of data from FCS 2.0 files, where the ability to visualize the full range of the spread was compromised by the hardware limitations. This is shown in Figure 6.
Figure 6: Comparison of uncompensated flow cytometry data in FCS2 or FCS3. The dotted box represents the approximate area that was magnified on the right.
As can be seen on the axis of the FCS2 data, there is a substantial amount of data piled in the first bin, which is showing up as red along the axes. This is not an issue with FCS 3 data, which allows for the visualization of the full range of the data.
One can use statistics to help improve the process, to an extent. In this case, a gate is placed around the positive and negative populations. As the compensation value is increased, the goal is to match the median (or geometric mean, depending on what is available in the software) of the positive gate in the secondary channel to the median of the negative gate in the secondary channel. This looks something like what is shown in Figure 7.
Figure 7: Using Statistics to optimize compensation. The median values of the positive and negative gate in the secondary channel (B-585/42) are shown in the table below.
The real compensation value is somewhere between 20 and 25% compensation. Plotting a graph with median on the Y axis and the compensation value on the X axis, as shown below, will allow the calculation of the 2 lines. The intercept point of these 2 lines is where the median value is equal. With a little bit of algebra, the equations can be set equal to each other, and the compensation value where MFIs are matched can be solved for. In this case, that value is 24.445%
Figure 8: Using matched medians and algebra to determine the compensation value of FITC into the PE channel.
That is a lot of work. Cowboy Compensation is not recommended at all. In fact, with more than 3 fluorochromes, manual compensation becomes difficult and should not be considered. While there are those who will swear by manual compensation, it is highly error prone, and should also be avoided. That leaves the last method of compensation, which is recommended.
3. Automated Compensation
Taking a step back, if one were to consider the process of signal detection, for a hypothetical 3-color experiment, it could be diagrammed as shown in Figure 9.
Figure 9: Origins of the fluorescent signal as measured by the detector system.
The left side of this box represents what we are trying to determine: the actual amount of fluorescence on the target. On the right side, is what is measured by the detector. The lines represent the photons of light from each fluorochrome. Taking the FITC signal to start, it is made up of the actual amount of FITC label on the cells, plus the actual amount of PE on the cells times a constant M21, that represents the detection “efficiency” of PE by the FITC detector and the amount of Cy5-PE fluorescent times a second constant M31, that is the amount of Cy5-PE captured by the FITC detector. Mathematically, this can be represented as:
FITCobs = FITCact+M21*Peact+M31*Cy5-PEact
By using the appropriate single stained controls and following the rules of compensation, these values can be determined. It boils down to a matrix algebra problem.
Figure 10: Matrix algebra representation of the compensation process.
Fortunately, the researcher doesn’t have to solve this problem, as automated compensation is available on most acquisition and analytical software. The rules of how to get the best controls will be discussed in the next blog in this series.
3 different theories on compensation have been discussed. The first, non-pensaton, is not recommended, and only possible under a narrowly defined instrument. The second, manual compensation, is also not recommended for anything more than 2 fluorochromes. It is error prone and subject to the researcher’s judgement, unless statistics are invoked. For polychromatic flow cytometry, best practices in flow cytometry is to use the automated compensation methodologies. This will ensure consistent and accurate compensation, if some rules are followed. The next article in this series will discuss what these rules are and how they apply to compensation.
To learn more about the Best Practices In Flow Cytometry Compensation Methodologies, 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.
My other passions include grilling, wine tasting, and real food. To be honest, my biggest passion is flow cytometry, which is something that Carol and I share. My personal mission is to make flow cytometry education accessible, relevant, and fun. I’ve had a long history in the field starting all the way back in graduate school.