Avoid Flow Cytometry Faux Pas: How To Set Voltage The Right Way

The Shift from Analog To Digital Cytometer Age

Analog instruments processed data differently than the current generation of digital instruments. With analog systems, if the populations were “off-scale,” especially at the low end of the scale, the data accumulated in the first channel. When setting voltage, highly autofluorescent cells would drive the voltage, and it was not uncommon for less autofluorescent cells on the axis to get compressed. Unfortunately, due to the way the data were plotted, this side effect was not always clear to observers.

With these older systems, the data were log-transformed and compensated in the hardware preventing much manipulation post-acquisition. Fortunately, with the advent of the digital cytometer age, data could finally be processed post-acquisition. This monumental shift meant it was time to review traditional voltage-setting methods, and new methods would need to be developed.

Methods To Set Voltage

There are a few different ways to set voltage. There is the historical method of putting the negatives in the first decade; you can calculate the standard deviation of electronic noise, set your negatives at 2.5-to-10x that value. You can use the OEM method to set voltages. You can use the Peak 2 method. Or you can use the “2x brighter” method. Last but not least, you can measure Q and B to help you define your values. We generally do not recommend the “SWG” method (scientific wild guess). 

Of course, at the end of the day, the important thing about setting voltages is that you identify a method and stick with it. So what makes a good voltage? That’s the question I’m going to address in this article. For one, the ideal voltage will give the best signal-to-noise ratio for a given fluorochrome. It’s going to make sure that the fluorochrome is within the linear range of the detector, and it will ensure that the fluorochrome is not off-scale.

Voltage Optimization: The Peak 2 Method

My preferred method for setting voltages involves a two-fold process. First, you need to characterize the PMTs. To do this, use the Peak 2 method from Maecker and Trotter’s paper. For this method, you run a dimly fluorescent particle (such as RCP-30-5A-2 from Spherotech) over a voltage range. Next, you calculate the rCV at each point, then plot and identify the inflection point – that’s your minimum starting value.

Figure 1 shows the results of the Peak 2 method. Beginning at a point of low voltage and high CV, it progressed to an inflection, marking the starting point of the optimal voltage range. Notice that there is a change in the slope of the curve. Above this point, you’ll also notice that the signal doesn’t improve – you don’t see a change. What you have to do is use the inflection point as your minimal operating voltage.

Figure 1: Determining voltage settings using the Peak 2 method.

These voltages can be refined by determining experimental specific voltages, which reflect the actual fluorochromes and cells that are being used in the experiment. To replicate this process, run the cells using the titer antibody concentration. Then run the voltage series, starting from this minimal starting voltage, and calculate the staining index. Basically, you’re looking at the ratio between the negative and the positive. You can do this using a foldover background, a staining index, or a separation index. I have never actually noticed a difference between any of the 3 methods, so I stick to using the staining index.

The next step is to plot the staining index vs. the voltage and identify your optimal voltage, as shown in figure 2. As you will notice, not every channel will be improved. 

Figure 2: Voltage optimization of two different fluorochromes. 

Cells are stained at the optimal titration concentration and run across a voltage range. Next, plot the staining index against the voltages. In figure 2, the peak 2 value is marked with a blue arrow. The optimal voltage is circled in green. On the left figure, as the voltage is increased, the signal first goes out of the linear range of the detector, which means we can’t use the data as we cannot properly compensate, thus, the peak 2 voltage is optimal. The figure on the right, on the other hand, increasing the voltage identifies a voltage where we get a 20% increase in the SI. To the right, the SI decreases because of an increase in the background signal. 

Tracking Voltages Over Time

Finally, you need to develop a way to consistently set target voltages over time (without having to go through a long, tedious process). After the optimal voltages are identified, run a bright, fluorescent bead such as the Spherotech 6th peak of the 8 peak headset. This will give you a “target value”, which is used when you set up a template with the appropriate plots and target values. The next time you use the instrument, open your template, and run that bright bead, adjusting the voltages to achieve the target values in each channel. Once that is done, you will be ready to start acquiring your samples. An example template is shown below.

Figure 3: Example template for instrument setup and tracking voltages over time. 

This method has another advantage: you can become cross-platform compatible. The best way to simplify the voltage-setting process (and eliminate accompanying dread) is to use some optimization methods. 

For those using the CytoFLEX™, a variation of this method has been recently published to aid in optimizing this platform. 

Concluding Remarks

The Peak 2 method—described earlier—is a useful and robust method by which you can identify optimal PMT voltage ranges. You can even further improve sensitivity by refining that to the voltage walk with the actual cells and fluorochromes of interest. This is especially critical for rare cell populations—or emergent antigens like activation markers. And to conclude, make sure you set up a way to monitor and maintain your voltage settings.

To learn more about important control measures for your flow cytometry lab, 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.

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Tim Bushnell, PhD
Tim Bushnell, PhD

Tim Bushnell holds a PhD in Biology from the Rensselaer Polytechnic Institute. He is a co-founder of—and didactic mind behind—ExCyte, the world’s leading flow cytometry training company, which organization boasts a veritable library of in-the-lab resources on sequencing, microscopy, and related topics in the life sciences.

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