I was at a meeting talking about the principles of panel design.
At the end of my talk, I had an investigator approach me and ask why he was not making progress on his 15-color panel that he started developing. So, I asked how long he’d been working on it.
That was his response. This might shock some of you but a month is not very long when it comes to designing an accurate and effective antibody panel for a flow cytometry experiment. Multicolor panel design requires a delicate balance of biology and physics. Understanding the biology of the system and the physics of flow cytometry are critical to success.
Antibody panel design (and flow cytometry experimental design in general) is a complicated process that can take a very long time. There are, however, some things you can do to simplify the process and shave weeks if not months off of your design time, including:
1. Knowing your biological question.
The driver in this whole process is knowing what the question is. This question will help determine the target reagents that will be needed to identified. If you don’t know the question you’re trying to answer, you’ll never be able to design an effective antibody panel.
2. Knowing your instrument.
This is the second biggest factor (#1 is the first) in designing an accurate and effective antibody panel. First, you have to know the instrument configuration, which means you have to:
- Understand the excitation light sources: What lasers are available and are they co-linear or parallel. The laser sources and the pathways determine the fluorochrome choices that can be used. Especially with co-linear lasers, some fluorochrome choices may have to be eliminated.
- Understanding the emission options: The filters in front of the PMTs will dictate what flurochromes can be measured by the flow cytometer.
Second, you have to know the sensitivity and quality control specifications of the instrument.
3. Knowing the antigens.
In designing a polychromatic flow panel, knowing the approximate antigen density is important. This can be ‘high density’, ‘intermediate density’, ‘low density’ or ‘unknown density’. For some common antigens, these values are known. In fact, you can download an antigen density chart here. This and knowledge of the literature will help you make these general assessments.
4. Knowing the fluorochrome intensity (or brightness).
Brightness can be measured and different fluorochromes compared to each other. Fluorescence brightness has several factors – the fluorochrome, the laser power and the detector efficiency. Thus, for each instrument it can be different, and should be part of the development process of any panel. New fluorochromes are shaking up many brightness charts. The new brilliant violet dyes, for example, are spectacularly bright compared to traditional fluorochromes. If in doubt, here is an example staining index chart.
5. Knowing how to use automation.
The next biggest effort in panel design is to assemble a list of available antigens and fluorochrome choices. This can be done with brute force and google-fu, or can be done using automation. Tools like Fluorish or Chromocyte can help assemble the list of possible antigens and fluorochrome.
6. Knowing how to pull the initial panel(s) together.
Here is where things get pulled together. Begin by paring the high antigen expression with dimmer fluorochromes. Those targets of low or unknown antigen expression should be paired with brighter fluorochromes. An additional consideration is to minimize the spread of error, especially in channels where sensitive measurements are made. Methods for determining the spread of error into different detectors has been published here and here.
The data would look something like this.
The sum across the detectors reveals the amount of error that each detector receives. Summing down the fluorochromes reveals the amount of error that each fluorochrome contributes to the total panel.
This type of chart can help identify where it is best to make the most sensitive measurements in the context of where the greatest spillover is, which reduces the sensitivity.
7. Knowing how to optimize the reagents.
This is a multi-step process, first of which is titration of the antibodies. This ensures that that the optimal antibody concentration is used. Too much antibody, and sensitivity is reduced by increasing background (SI is decreased). Too little antibody, and sensitivity is also reduced by decreasing the positive signal.
The second step is optimizing the voltage on the instrument for each fluorochrome. Staining the cells with optimal antibody concentration (see titration above), then run a voltage series to determine if increasing the voltage will improve the Staining Index.
In the panel on the left, increasing the voltage doesn’t change the staining index significantly. In the right panel, increasing the voltage shows an improvement to the staining index.
8. Knowing how to validate the panel.
With optimized antibody concentrations and voltages, the work begins on validating the panel. During this part of the panel design, staining a series of control cells, and validating the panel is critical. At this point, it is also critical to review the controls that are necessary for proper analysis of the data. These controls will include:
Proper compensation controls
9. Knowing the OMIPs.
Consider reviewing the OMIPS or “Optimized Multicolor Immunofluorescent Panels”. This journal article type, published in the journal Cytometry A, reports the results of researchers who have developed multicolor panels. There are currently over 20 OMIPs published and can be used as the basis of developing and modifying fluorescent panels for an individuals.
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.
Latest posts by Tim Bushnell (see all)
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- 4 Steps To Implementing a QC Program For Your Flow Cytometry Experiments - August 1, 2019