4 Critical Components In Cellular Proliferation Measurement

Written by Tim Bushnell, PhD

Cell proliferation is a critical component in biological systems.

While normal cell proliferation keeps the body functioning, abnormal proliferation (such as in cancer) can be a target for therapy.  

Measuring how cells proliferate in response to a stimulus is a time-honored assay in science. This can be as simple as a cell count between untreated and treated cells. More sophisticated assays can include the use of ³H-thymidine or colorimetric assays (MTT assays).

While these all can measure proliferation, they lack the finesse that flow cytometry can bring to the assay – which allows the phenotypic identification of which cells are actually dividing, as well as allowing for calculations of values such as the precursor frequency, the percentage of cells that have divided, a proliferation index, and more.

Proliferation calls for cells to make a trip around the cell cycle, and there are many ways to measure cell division.

The focus here is on the long-term measure of cell division-the 'temporal' dimension for measuring such biological processes as:

• Proliferation of immune cells in response to stimulation


• Self-renewal of stem cells


• Biological homeostasis


• Tumor cell proliferation

To this end, there are several critical components in developing, validating and optimizing an assay to make these measures using flow cytometry. These 4 components are…

1. Pick the right cellular proliferation dye.

Determine which dye you want to use for proliferation. The qualities of a good dye for proliferation include:

• It is taken up by live cells


• It stains brightly


• It is well retained by the cells


• It segregates equally between daughter cells

There are two major classes of these dyes, based on where the dye is retained by the cells.  

The first class is the intracellular dyes that enter the cell, are acted upon by cellular esterases which cleave the compound into a fluorescent form that can also interact with intracellular molecules, thus binding inside the cell.

The most common of these dyes is carboxyfluorescein diacetate succinimidyl ester (or CFDA-SE).  When this enters the cell, it is cleaved to the active form CFSE, which is amine reactive, binding to intracellular proteins, and has been used extensively for cell tracking and proliferation.

The second class of dyes for proliferation are lipophilic dyes that bind to the cell membrane.  

These dyes are typically not fluorescent until they are incorporated into the cellular membrane, and over time distribute over the whole cell. There are a host of these dyes, one of the most popular is PKH26. Table 1 below lists some of the most common cell proliferation dyes available.

There are many more dyes available, and a quick search of your favorite vendor's catalog will reveal one that will work for your needs. The Molecular Probes Handbook is especially useful in selecting a dye for your experiment needs and instrument capabilities.

Table 1:  Some Common Cell Proliferation Dyes

2.  Validate your proliferation dye-make sure your cells like it!

After you have selected your dye, it is critical to optimize the labeling reaction for the dye.

This will include optimizing the labeling solution (typically between 0.1 to 10 μM), the cell concentration (between 1-20 million cells per ml), the incubation time and temperature, and the quenching step.

In the case of succinimidyl dyes, this would involve adding protein (BSA) and letting the cells rest for 5-10 minutes before washing. As part of this assay development, it is important to make sure that the dye does not kill the cells.

After labeling, a viability check is critical.  

Shown below are data from Dr. Andy Filby (head of flow cytometry at Newcastle University): cells were labeled with increasing amounts of CellTrace Violet (CTV), CFSE and eFluor670 (EPD) and the viability measure.  At 1 μM, the cells have about the same viability, but this rapidly changes, especially for CFSE, where increasing amounts of the dye increased cell death.

More dye is better, in so much as the brighter the signal, the more generations can be measured in the experiment, but not at the expense of increased dead cells.

Dead cells tell no tales.

3.  Optimize your flow cytometry instrument.

In an ideal world, as the cells divide, the fluorescence signal would decrease precisely by ½ and calculating the proliferation metrics would be easy.

As shown in this figure, modified from a lecture Dr. Andy Filby presented for Expert Cytometry (and available to Mastery Class members here), the reality is not that pretty.

Several factors influence the spread of the data, including:

• The true biological variance inherent in the cell systems


• The intrinsic spread because of fluorochrome labeling and speed of the cells through the system


• The extrinsic spread because of the instrument (such as optics, laser power, alignment)

The consequences of these factors can be reduced in several ways:

• Careful planning of the experiments


• Run the cells at low differential pressure


• Monitor the laser alignment


• Keep the instrument (flow cell) clean

Before running samples, run a standard bead set to validate the instrument. Checking linearity, sensitivity, and alignment before the actual samples are run is a good way to help minimize the causes that can be controlled.

4.  Analyze your proliferation data correctly.

In designing a proliferation experiment, as with any flow cytometry experiment, it's important to develop a data analysis plan before beginning the experiments.

There are three informative parameters that can be measured from a properly constructed experiment. These values are:

• The Percent Divided – the measure of the percent of the input cells that entered division.


• The Division Index – a measure of the average number of divisions which includes the undivided cells.


• The Proliferation Index – the average number of divisions that exclude the undivided cells.

There is a clear temptation to manually gate on the populations and calculate these values, because of the overlap between peaks. It is impossible to easily set the gates to avoid the overlap. This is where modeling of the data comes into play.

Take, for example, the below data (courtesy of Dr. Andy Filby)…

On the left, the populations have been manually gated, while on the right, they have been fitted to a model using the FlowJo™ proliferation package.

Manually fitting the data gives a percent divided at 78%, while the model fitted data shows a percent divided of only 59%.

It's clear that the above difference has a major consequence on the interpretation of the data.  

It's also important to remember dyes like CFSE have a 24-48 hour proliferation-independent loss of signal that must be taken into account before measuring proliferation.

Another thing to remember is that as the cells divide, it will become over-represented in the data by 2^{division round}.  To determine the true percentage of dividing cells, you have to do some math. This starts by correcting the frequency of each generation by dividing by 2^{division round}.  

These values are then added together, and the data normalized by that value to determine the real frequency in each population. Furthermore, by subtracting the undivided fraction from 100, it is possible to get the precursor frequency.

Making sure that you know the data needed to answer the biological questions, and the power (and limitations) of the analysis of the data is critical.

Define the question, define the statistics needed and then, and only then, foray into the lab and begin the experiments.

Proliferation assays are a powerful tool for understanding and monitoring this important cell process. Understanding this process, how it can be dysregulated and what ways it can be controlled (chemically), is a critical process. The development of new treatments for cancer, for example, target the proliferation of the cancer cells. Failure to properly design and analyze the data will result in missed opportunities and false leads. Knowing the steps to optimize these assays and properly interpret the results, as discussed here, will help ensure the best data and best opportunities are pursued.

To learn more about getting your flow cytometry data published 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.

4 Spectral Viewers You Should Be Using For Your Flow Cytometry Experiments

Written by Tim Bushnell, PhD

At the heart of flow cytometry is the ability to make meaningful measurements of fluorescently tagged cells.

These fluorochromes can be bound to antibodies, a fluorescent protein, a reporter fluorochrome, and the like. Free online spectral viewers are useful in a variety of ways, all of which help improve experimental design and troubleshooting.

These spectral viewers have a special place on every scientist's browser toolbar. I refer to them regularly, at least weekly.

During the process of panel design, it is useful to have these open to check and compare different fluorochromes. In fact, with recent upgrades to FluoroFinder, there is an integrated spectral viewer based on the filter configuration.

There are a host of different spectral viewers available online. Each one has its strengths and provides specific information. This often necessitates having to use two or three of them to get the information you want. These are the spectral links I use (in alphabetical order):

1. AffymetrixFluorPlan Spectra Viewer


2. BD Bioscience Spectrum Viewer


3. Biolegend Spectra Analyzer


4. ThermoFisher Fluorescence SpectraViewer

All the spectral viewers listed have several common and important features. These all allow the investigator to specify the laser excitation lines, the filter configurations and the fluorochromes. The one caveat with fluorochrome choice revolves around proprietary spectra and some will only be available with specific vendors.

The spectral viewers also output similar information, as illustrated below. This information can include how much of a given excitation curve is found in a given filter, the percentage of maximal emission, and more.

What Is A Spectral Viewer And Why You Should Use It

One of the primary benefits of spectral viewers is that they are useful in learning more about fluorochromes. For example, the popular tandem dye PerCP-CY5.5.  

This shows the excitation at 488 nm, and the nice emission. The BD Bioscience Spectrum Viewer gives you a nice additional feature–the %Max excitation, in this case it's 98.4%. The excitation curve (shown in dashed blue) ends at about 450 nm. So, how can the spectral viewer help us explain the following data?

In this experiment, the beads were stained with either PerCP-Cy5.5 or Qdot705 and measured with either blue laser excitation (Blue B 710/50) or violet laser excitation (Violet B 710/50). As you can see from the graph, it's clear that there is significant PerCP-Cy5.5 signal in the Violet B channel (Blue line).

Where is this signal coming from?

Seeing that the PerCP-Cy5.5 excitation profile ends, the following figure shows the excitation profile from PerCP.  Our answer is revealed in the full excitation spectrum.

PerCP, it turns out, can be excited by a 405 nm laser, at about 27% efficiency. Coupled to an efficient transfer to the Cy5.5 acceptor on the tandem, it explains why we see this signal in the violet laser.

This is significant if you were going to be using those two dyes in a polychromatic panel.

How To Evaluate New Fluorochromes On The Market

The Brilliant Violet™ dyes, produced by Sirigen, have been a boon to users of the violet laser. These dyes are extremely bright and have become very popular. The Brilliant Violet™ series of dyes include both polymer dyes (BV421™ and BV510™), and tandem dyes with the polymer core (BV570, BV605™, BV650™, BV711™, BV785™). While they may not be named as tandems, they may have some issues that the spectral viewer can reveal.

Here is the spectrum of BV605™…

Notice that there is a second excitation (here shown in the green 561 nm line). This excitation means that this tandem may have issues affecting the spillover of this dye into a PE and PE-Texas Red®-like channel.

Anytime a new fluorochrome comes out, it's good to learn about it using these spectral viewers.  The Biolegend Spectra Analyzer is quick and easy to use, and they even have an app for the program, so you can go mobile with it. This is useful when you're reviewing data with someone and don't want to access your traditional computer browser.

How To Identify Areas Of Spectral Spillover

Another powerful use of the spectral viewers is to understand what channels on an instrument a given fluorochrome will spill into. The following example is using Alexa Fluor® 488, with three instrument filters placed on the graph.

With the ThermoFisher Fluorescence SpectraViewer, if you hover over the filter, it will report the percentage of the curve that is contained within that filter. In this case, the 530/30 bandpass filter captures about 49% of the curve.

About 12% of the Alexa Fluor® 488 fluorescence is captured with the 585/42 filter, and about 1% with the 630/20 filter.

It is important to note that this is not the amount of compensation that needs to be applied, just the amount of the curve that is present in the filter.

Here is an example of another use for these spectral viewers, courtesy of the AffymetrixFluorPlan Spectra Viewer. In the results tab, it shows in table form the percentage of a given fluorochrome's emission curve found in the filter in question.  Looking at this figure, with the PE and PE-Cy7 curves plotted, what can be said about the PE-Cy7 fluorochrome?

It turns out that the FRET between the PE emission and the Cy7 excitation is not optimal.

How To Optimize Flow Cytometry Filters

Another great use of the spectral viewers is to optimize the filters for a given fluorochrome on a specific instrument. Take for example, the following data. A researcher noticed some sensitivity issues off of two detectors when an instrument was installed. Beads were stained with FITC (488 nm excitation) and QDot545 (405 nm excitation) and run on the instrument. The data looked like this:

When the 532 nm laser was on, it was clear that the dim signals were shifted to the right. The instrument came with the vendor supplied filters. In modeling this issue, putting these two filters in, along with the laser lines, we see the following:

Notice that the 532 nm laser line was directly in the middle of these two filters. The cause of the loss of resolution was a result of the scatter from cells as they pass through the 532 nm laser. A fraction of this scatter wound up in the fibers leading to the blue and violet detectors.

The lesson learned from this was to always model your filters before ordering an instrument.  A tweak of the filter solved this problem, and the experiments continued.

What Is The FluoroFinder Spectral Viewer?

Recently, FluoroFinder released a new version of their panel design package.  As part of that package, when the cursor hovers over a given fluorochrome, the system will provide the researcher information based on the instrument configuration and filters on the machine. This is shown below.

This is an excellent resource when designing polychromatic panels. It is nice to get a view of the spectra of the fluorochrome choices on the instrument being used and quickly get a feel for how well a given filter/detector combination will capture the photons emitted from the fluorochrome. It also helps to see what other channels might be affected by the fluorochrome choice.

For example, on this instrument, there are several possible filters that can be used for QDOT565. Based on the filter configuration and emission profile of the fluorochrome, this emission may impact three other detectors. For that reason, it may be better to choose a different fluorochrome. This addition to FluoroFinder is a great feature to help make those critical fluorochrome choices during the design process.

Fluorochrome emission is the lifeblood of flow cytometry. The use of in silico tools can save a lot of effort and missed opportunity by allowing for the modeling of excitation and emission profiles in the context of what filters a given instrument is equipped with. Using these tools, it is easy to identify where a new fluorochrome will be measured on an instrument, where a fluorochrome may cause issues with other fluorochromes, and what filters are best for detection. These tools can save a lot of troubleshooting at the beginning of an experiment, and also help understand when issues do pop up. Bookmark them and use them at every opportunity.

To learn more about spectral viewers 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.