The nuances of using CFSE to monitor lymphocyte proliferation

Measuring proliferation of lymphocytes such as T cells isolated from peripheral blood monuclear cells (PBMC) using carboxyfluorescein diacetate succinimidyl ester (CFSE) is not a foolproof protocol.  CFSE can be toxic to cells and non-optimal CFSE labeling conditions can thus hamper proliferation of cells and obscure interpretation of results.  An article in Nature Protocols by Quah et al., details CFSE labeling conditions and how to achieve optimal results.

CFSE is a fluorescent cell membrane permeable dye with similar excitation and emission properties as fluorescein isothiocyanate (FITC).  Thus CFSE can be assayed in flow cytometry by the same channels that detect the fluorescence intensity of FITC.  The CFSE precursor, carboxyfluorescein diacetate succinimidyl ester (CFDA-SE) that is used to label cells is non-fluorescent, but once inside cells, acetate groups are removed by intracellular esterases, causing the resulting CFSE molecule to become fluorescent and also less membrane permeable.  Furthermore, the succinimidyl ester group of CFSE covalently couples to primary amine groups, thus remaining bound to proteins inside cells for long time periods.  As a cell divides, the intensity of CFSE staining in the resultant daughter cells will be half that of the parent, allowing easy flow cytometric assessment of the number of cell divisions that have occurred since labeling.

While CFSE is commonly used to assess lymphocyte proliferation, CFSE can be toxic and impair cell division.  According to Quah et al., four parameters of the labeling conditions must be considered to minimize this toxicity:

1. The concentration of the cells.

2. The concentration of CFSE.

3. The duration of cell labeling.

4. The presence of amino acids in the labeling media.

CFSE will bind to free amines in aqueous conditions and thus reduce the remaining CFSE concentration. To avoid the loss of CFSE to amino acids in the labeling media, PBS is the recommended diluent for CFSE prior to adding to cells.  Cells are uniformly suspended in PBS with serum, and the CFSE/PBS stock is immediately mixed rapidly with the cells and allowed to incubate for the optimal amount of time.

Regarding cell and CFSE concentration, these two parameters must be considered in the context of the other.  Cells at higher concentrations can be labeled with higher concentrations of CFSE with a minimal effect of CFSE toxicity on cell division.  For instance, cells at a concentration of 50 x 106/ml can be labeled with 5uM CFSE, but cells at a concentration of 1 x 106/ml will experience significant toxicity if labeled with 5uM CFSE but will do well with 1uM CFSE.  The time of labeling is also important, and longer incubation times will increase toxicity.  Quah et al. recommended 5 minutes of incubation with CFSE before washing the cells.

To assess proliferation, after CFSE labeling, cells are washed and then stimulated with a mitogenic signal.  For instance, T cells can be stimulated with anti-CD3 + anti-CD28, PHA, SEB, PMA + ionomycin or other stimuli.  Then the cells will be allowed to divide for a number of days which must also be optimized depending on the stimulus used.

T cells will die if left unstimulated in vitro and as they proliferate, they can undergo activation induced cell death (AICD).  Thus, some amount of cell loss must be anticipated.  In an accompanying protocol in Nature Methods, Hawkins et al. detail the incorporation of cell count beads during flow cytometry to more accurately measure the degree of cell proliferation.

Thus, there are many nuances to consider when using CFSE to label cells for assays such as proliferation.  I recommend reading both of these protocols to achieve robust assay performance.

Further Reading:

Monitoring lymphocyte proliferation in vitro and in vivo with the intracellular fluorescent dye carboxyfluorescein diacetate succinimidyl ester.  Quah BJ, Warren HS, Parish CR. Nat Protoc. 2007;2(9):2049-56.

Measuring lymphocyte proliferation, survival and differentiation using CFSE time-series data.  Hawkins ED, Hommel M, Turner ML, Battye FL, Markham JF, Hodgkin PD. Nat Protoc. 2007;2(9):2057-67.


Understanding MFI in the context of FACS data

Understanding MFI in the context of FACS data

The speed, sensitivity and versatility of flow cytometry are things of beauty, but with great power comes great responsibility. The fact is that with potentially millions of data points accrued over the run of a single sample, finding the best way to compare those data can be daunting. One of the more commonly misunderstood and often misleading tools in FACS analysis is a pesky little statistic — MFI.


What is MFI?

mean mode median MFIThe first point of confusion is born from the name itself. MFI is often used without explanation, to abbreviate either arithmetic mean, geometric mean, or median fluorescence intensity. In a perfect world, our data would be normally distributed and in that case means, median and mode are all equal. In reality, flow data is rarely normal and never perfect. The more that the data skews, the further the mean drifts in the direction of skew and becomes less representative of the data being analyze as seen on the graphical representation.

Because fluorescent intensity increases logarithmically, arithmetic mean quickly becomes useless to generalize a population of events, as a right-hand skew causes even more exaggeration of the mean. To combat this, geometric mean (gMFI) is often used to account for the log-normal behavior of flow data, however, even gMFI is susceptible to significant shifts. This leaves us with the median or the mid-point of the population. Median is considered a much more robust statistic in that it is less influenced by skew or outliers. Is there a “right” MFI to use to analyze flow data? No. But generally speaking, median is the safest choice and usually most representative of a “typical” cell.


Three common mistakes when using MFI

            Characterizing a bi-modal population: Any average only holds true for normal distributions, and a bi-modal population is by definition not normal. Statistics aside, gating each population and presenting percentages will yield data that is both more easily interpretable as well as more statistically significant.

            Comparing data from disparate experiments: Because fluorescent intensity is sensitive to experimental condition (e.g. antibody dilution, tandem dye degradation, laser fluctuations, etc.), it is dangerous to compare intensity of any kind across multiple experiments.

            Blindly using MFI as a quantification of expression: While FACS is more than sensitive enough to provide estimates of ligand abundance, such calculations require normalization and calibration using a standard curve. Additionally, it is tempting to say that a population with a higher MFI has higher expression than one with a lower MFI, however, care must be taken to ensure other factors are not responsible. For example, a large cell with more membrane and consequently more surface protein, can appear brighter than a smaller cell of the same type. Thus, it is important to control carefully for things such as size or compensation that may confound results.


So, when should I use MFI?

Not until asked by a reviewer.


MFI has many important uses, but can sometimes be as much a distraction from the data as it is a clarification. Ultimately, like any piece of data, MFI should only be applied if you are absolutely certain that it is the best comparison to make, otherwise it is simply clutter on an otherwise clean histogram.


For further reading:

Flowjo’s excellent explanation of the differences between mean, median and mode.

An amazing article explaining when and why to use bi-exponential axes. Importantly, the affect scaling can have on actually visualizing the median value of a population.


adam bestAdam Best is currently a post-doctoral fellow at the University of California, San Diego where he also received his Ph.D. in Biomedical Sciences. His research focuses on understanding the transcriptional events that govern the formation of memory T cells