4 Biggest Mistakes Scientists Make During Multicolor Flow Cytometry Cell Sorting Experiments
Multicolor cell sorting is a complicated process and certain scientific errors can be common.
Unsuccessful multicolor sorts can result in erroneous data and inconclusive results. Successful multicolor sorts, on the other hand, can give excellent results and lead to dynamic conclusions.
Successful multicolor cell sorting requires special attention to planning.
Using specific setup strategies for your experiment can create a streamlined system for an otherwise complicated process. For example, these critical steps and strategies for multicolor sorting experiments can save you time and maximize your results.
When setting up a multicolor experiment, the most common mistakes are failing to set PMT voltages properly, failing to use a viability dye, failing to address doublet discrimination properly, and failing to set the right sort regions and gates. Eliminating these 4 mistakes is important for any kind of flow cytometry experiment, but particularly for flow cytometry cell sorting experiments.
The following 4 mistakes should be avoided prior to the setup phase, which should be executed immediately before the sort. This setup phase should be included as part of the planning, optimization, and trial process of the experiment to give you the best cell sorting results possible.
Here are 4 common multicolor cell sorting mistakes you should avoid…
1. Failing to set the PMT voltages properly.
When setting up a multicolor experiment, the most saliently critical step is to set PMT voltages and to do so properly.
The overarching theme to this portion of experimental setup, as with most anything in flow cytometry, is to maximize signal-to-background resolution.
As such, setting voltages using an unstained sample to place the negative peak in the first log quadrant (or any other desired position in the plot) may not, and often doesn’t, accomplish the goal of maximizing sensitivity in each channel.
Keep in mind that PMTs do not perform maximally (i.e. convert photons to electrons as efficiently as possible) at every single voltage setting. Moreover, in order to ensure that a detector is operating at peak performance, a sample that contains both negative and positive populations must be used.
An unstained sample provides perspective with respect to the negative population only, so it cannot be used to determine how well a stained population will be resolved from an unstained population.
In general, the danger arises when the voltage is set too low, which may result in suboptimal photoelectron generation and signal detection.
When measuring signal in channels in which cells tend to autofluoresce, like the green region of the spectrum, setting voltages based on the position of the unstained may result in a PMT voltage that is too low. Conversely, setting voltages based on the position of the unstained in red channels, in which cells autofluoresce very little, may result in the voltage being set too high, which in turn may result in the positive population to be off-scale once the full-stain is acquired.
If using BD instruments controlled by FACSDiva (e.g. FACSAria, LSR II, LSR Fortessa) the CS&T system can help to determine minimum baseline voltages, or the minimum voltage at which that detector should be operated. There are some excellent references that provide extensive and thorough methods to accomplish the same goal.
In general, there some useful rules of thumb that can help guide you along the most optimal path for setting your PMT voltages properly.
First, voltages must be set so that no stained population is off-scale. This is critical both from a visualization perspective (no one likes to look at data where staining is smashed up against the high end of the scale), and from a measurement one. The very high portion of the scale may not be in the linear range of the detector and may not facilitate proper signal measurement. Again, this goal can only be accomplished by running a sample with a clear positive population.
Be wary of using compensation beads to set voltages.
Staining can be very bright, which may result in a tendency to reduce voltage to possibly suboptimal settings. After checking to make sure no staining is off-scale, adjust the voltages, usually by increasing them, so that the separation between positive and negative populations is clear and maximized as best as possible.
One common practice in flow cytometry is the tendency to adjust PMT settings with the specific aim of minimizing percent overlap in the compensation matrix. Remember, the primary goal in setting voltages is to ensure that the resolution between positive and negative is maximized.
The percent overlap is not a particularly good indicator of whether separation is maximized.
As long the voltages are set so that no populations are off-scale, the detectors are operating in linear range, and that positive and negative are well separated, do not worry about the compensation percentages, assuming that compensation was set up properly. Instead, let the data speak for itself.
Always ensure that the PMT voltages are the same for each control. Compensation will not be calculated correctly if voltages in all channels are not consistent between controls.
2. Failing to use a viability dye.
Antibodies have a tendency to stick to dead cells, which will result in false positives that may drastically compromise purity.
This can be devastating for a sort, especially when the cells will be used for downstream molecular applications that rely on high-integrity sort purities. Moreover, while false-positive dead cells including in the sort fraction may not grow in cell-based assays, their presence may affect cellular processes of other cells present.
There are many nice choices for viability dyes and there are two kinds whose mechanisms are different: DNA-binding dyes and amine-reactive dyes.
DNA-binding dyes, like propidium iodide (PI), DAPI, and 7-AAD, are typically positively charged molecules with strong DNA-affinity that cannot pass through intact cell membranes. Thus, they only stain the DNA of dead or dying cells with compromised membranes. These dyes are good choices because staining is very rapid, so the dye can be added very soon before the sort and does not require a separate staining step.
Because the stain is present in the buffer in excess, DNA-binding dyes provide a “real-time” indicator of cell death; cells that die during the sort will allow dye into the nucleus and will begin to fluoresce.
While typically not a concern for sorting, these dyes cannot be used with fixed cells because the dye-DNA binding is non-covalent and equilibrium-driven.
If cells are fixed after staining, dye that dissociates from DNA in cells that were dead before the fixation may stain DNA of cells that were live before the fixation, given that fixation disrupts cell membrane integrity. Alternatively, amine-reactive dyes, often called “fixable” dyes, bind covalently to free amines on and in the cell. Staining with these kinds of dyes must be performed during an independent staining step.
Dye will enter and stain cells that are dead and have compromised membranes, so staining intensity of dead cells will be much higher than that of live cells, which permit binding of the dye to only those amines on the cell surface. After staining, cells can be fixed if desired, due to the fact that the dye-amine bond is covalent and not equilibrium-driven, so staining integrity will be preserved after fixation.
In general, DNA-binding dyes are preferable to amine reactive dyes for sorting, given their ease of use and “real-time” properties, so stick with the many choices available for these when designing a panel.
Reagent manufacturers have devised DNA-binding viability in many flavors, so finding one that fits into your panel should not be a difficult task. The SYTOXⓇ dyes, manufactured by ThermoFisher, can be a good choice.
One nice thing is to combine a viability dye with a dump channel, or a channel used to gate out cells that are positive for a marker or multiple markers, to remove “lineage-negative” cells from analysis, for example. Since both the dump and viability dye channels are used to gate out cells that are stained, both can be combined into one channel, which can free up another channel on the cytometer for a another marker.
3. Failing to discriminate between doublets and single cells.
Doublets occur when two cells pass through the interrogation point so close together that the instrument treats them as one event.
When this occurs, the pulses from a doublet event measured in the FSC detector look like those illustrated in the figure below.
The height of a doublet pulse will generally be equivalent to the height of a single-particle pulse.
However, because a doublet pulse is essentially the merger of two single-particle pulses, the area and width of such a pulse will be larger than that of a single-particle pulse. We can take advantage of the disparity between the pulse parameters of single particle and doublet signals to distinguish the two from each other.
Typically, area is plotted against height, height is plotted against width, or area is plotted against width. All cells must have a measurable signal in the parameter chosen, so forward scatter or side scatter are usually utilized.
Also, two doublet discrimination gates, one utilizing FSC and the other utilizing SSC, can be included for more robust doublet identification. While doublet discrimination is important for any kind of flow cytometry experiment, it is especially critical for cell sorting.
Failure to discriminate doublets from single cells can severely compromise the purity of a multicolor cell sort.
A doublet event may incorporate one cell that fulfills the sort logic AND another cell that does not fulfill the sort logic. Because the sorter has identified both of these cells into one event, the entire event — both the target cell and the non-target cell — will be sorted, resulting in both a target and non-target cell in the collection fraction.
The presence of doublets does not necessarily indicate poor performance of a sorter.
Doublet events are a normal and expected aspect of a flow cytometry experiment and whose frequencies are dictated by how the cells are dispersed into a stream. Denser suspensions and sticker cell types can certainly influence dispersion, so do not be dismayed if doublets are observed. The most important thing is to find and eliminate them.
4. Failure to set the right sort regions and gates.
Setting the right sort regions and gates is especially critical for sorting, given that all set-up must be perfect before the sort begins in order to achieve results of the highest caliber. Gates should be set based on the boundaries of positivity determined by FMO controls to ensure that only true positive cells are sorted.
Keep in mind that populations in flow cytometry are distributions with inherent variances or widths.
The width of a population is primarily a function of both the number of fluorophores bound to (immunofluorescence) or expressed by (fluorescent proteins) the cell as well as the measurement variation. The fluorescence of a single theoretical cell passed through a cytometer 1,000 times will be measured differently each time and will give rise to its own “population”.
The degree to which this is the case depends on many factors, including laser power, collection efficiency of the instrument, and wavelength of detection. The lower the population falls on a log scale, the more this error will be revealed in the same way that error is revealed by compensation resulting in spillover spreading.
Lower decades on a log scale contain fewer bins, or fluorescence intensity values, than decades higher on the log scale, so a distribution with the same variance will look broader in the second decade of a log scale than in the third decade.
In the above example, the GFP+ population falls very close to the GFP- population and the two populations overlap.
As such, it is critical in this case to position the region that classifies events as GFP+ far enough away from the negative population to ensure that no GFP- cells fall into the GFP+ region as a result of measurement imprecision. Moreover, the distribution of the negative population reflects no fluorescence signal whatsoever, and there is no meaning to where a cell falls in that distribution.
For the most part, assuming the autofluorescence of all cells in the negative population is the same, a cell on the left side of the negative distribution is no different than a cell on the right side of a distribution. As such, do not expect a “pure” population if the sort region encompasses a specific portion of the non-fluorescent population.
When run back through the instrument for a purity check, the entire negative distribution will be repopulated, given that there is absolutely no difference between unstained cells with regards to where they appear on the scale.
As a tip, it is often better to distinguish dim GFP signal from background on a two-dimensional dot-plot than on a histogram, as illustrated below.
By plotting GFP, or any other signal for that matter, on a plot against another parameter that is not being utilized in the experiment, low-expressing cells can be distinguished from the autofluorescence of non-expressing cells due to how the cells are distributed in both channels, as illustrated above.
The figure below, from Arnold and Lannigan, clearly emphasizes the importance of setting sort gates conservatively when signal is dim. Failure to do so can severely impact purity by permitting non-expressing cells into the sort region.
The above figure is from a paper published in Current Protocols in Cytometry by Arnold et al. Here, Panels A and C shows the effect when the sort gate, R1, is placed too close to the negative population (R2). Because this gate encroaches on the negative distribution, it does not distinguish non-expressing cells from expressing cells. Purity is poor using this gate.
When the sort gate is positioned more conservatively, purity is much higher.
Keep this in mind when setting gates for dimly expressing cells. It can make the difference between a successful sort and a suboptimal one.
Multicolor flow cytometry sorting experiments, while sometimes challenging, are not unsurmountable. When setting up a multicolor experiment, the most saliently critical step is to set PMT voltages properly. In addition, using a viability dye and addressing doublet discrimination and setting the right sort regions and gates is important for any kind of flow cytometry experiment, but particularly for cell sorting. Utilizing the tips described here as well as the abundant other resources available to help optimize multicolor staining, should help clarify some of the more difficult aspects of setting up and executing this kind of cytometry experiment.
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