The Difference Between Purity, Single Cell, And Recovery Cell Sorting Techniques

Written by Michael Kissner

If you have experience sorting different kinds of cell types on a droplet sorter, you may have noticed that sorting efficiency often seems closely tied to the cell and sample type.

For instance, you may have experienced a better outcome, such as a higher efficiency and more cells recovered, after sorting lymphocytes versus sorting an adherent cell line. There are some fundamental concepts that underpin this phenomenon, and understanding them will help you perform better cell sorting experiments.

What Is Flow Cytometry Cell Sorting Efficiency?

Sorting efficiency, in fundamental terms, is a real-time measurement, generated by the instrument, of how successfully its sorting system is able to resolve cells that we want to sort (target events) from cells we do NOT want to sort (non-target events).

Note that we are talking about the sorting system's ability to resolve events here (the droplets) and NOT the electronics system.

Efficiency is calculated with the following equation:

The results of this equation are highly dependent on two aspects of the sort: 1) the sort mode chosen for the sort and 2) the setup of the sorting system. Sort modes are sets of rules that instruct the instrument on what to do in situations that I often refer to as “ambiguous.”

In order for the instrument's sort output to be acceptable with respect to the researcher's needs, it is not sufficient to simply tell the instrument WHAT to sort (i.e. assign a sort region), but is also critical to tell the instrument HOW to sort the target population. The HOW is determined by the sort modes.

Purity, Single, And Recovery Cell Sorting Modes

If high purity is critical for the downstream application, the sorter must be instructed to exclude any target events from the sort that fall close to any non-target events (usually within one half of a droplet). Otherwise, a non-target event can haphazardly be sorted along with the target events. This kind of sort mode is often called “Purity” or “Purify” mode.

Alternatively, if extremely accurate counting of the output cells is critical for the downstream application-for single cell sorting, for example-“Single” or “Single Cell” mode is often used.

Finally, sometimes it is important to recover every single cell possible from the sort, and there's not much concern for purity. In this case, we tell the instrument to ignore any rules and to sort everything that falls into the sort gate. These modes are often called “Yield” or “Recovery” modes and will always result in efficiencies of 100%.

Target cells that are sorted are termed sorts, and target cells that are not sorted due to violation of the sort mode rules are often called conflicts, coincidences, or aborts.

Although every type of sorter has its own way of implementing sort modes, all sorters must and do include them. In essence, these modes are comprised of combinations of masks that define where a cell can and cannot be in order for a sort to take place.

What Is A Flow Cytometry Cell Sorter “Mask”?

A certain type of mask, often called the “purity mask,” defines how close a non-target cell can come to a target cell in order to mark that target cell for sorting.

Another mask, often called the “yield mask,” defines how many drops should be sorted in order to include a target cell that may be close to a droplet boundary. In this case, the droplet to sort in order to capture this capricious cell is ambiguous and two droplets may be sorted in order to capture it.

Instruments define where cells fall in relation to droplets in relation to the cells' passage through the lasers. The only place on the instrument where it can “see” cells is at the laser-it cannot measure where the cells are when the stream breaks into droplets-so the system effectively predicts where the cells will fall in droplets, to a certain degree of resolution that depends on the instrument's electronics, by relating the timing of cells as they pass through the lasers with respect to the pattern by which droplets form.

It is important to emphasize here that the instrument's determination of cell positions in droplets are predictions, so there is a degree of uncertainty here that requires a buffer zone between events, determined by the masks, to ensure that the sort outcome is as desired. Additionally, cells may speed up or slow down, depending on the sample type and instrument, between the laser interrogation point and the droplet break-off, compounding uncertainty.

Why Cell Sorters Count Droplets, Not Cells

In addition to sort modes, the sort set-up and sort conditions are tightly bound to the efficiency and sort outcome.

The relevant parameters are primarily the droplet frequency, the event rate, and the percent positive (of the total number of events) of the target population. To understand this relationship, it is critical to keep in mind that when we sort we are NOT really sorting cells, but rather, we are sorting droplets.

In other words, the fundamental sorting unit on a droplet deflection sorter is NOT the cell but is the droplets that (ideally) contain the cell. Therefore, in order to sort, the stream of sheath fluid must be partitioned into discrete sorting units or droplets under controlled conditions.

The number of unique partitions depends on the droplet drive frequency. The higher the frequency, the more droplets are generated per second. Most importantly, the rate of droplet formation, once determined at setup, never changes during the sort.

Understanding the difference between cell sorting efficiency, purity, and recovery cell sorting techniques will help you perform better sorting experiments. When performing a sort, make sure you select the proper sort mode, whether it be purity, single cell, or recovery (the latter is sometimes referred to as yield). Remember, cell sorters use masks to predict which droplets, not cells, to sort. By keeping these facts in mind the next time you sort cells, your experiment will be more successful.

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.

12 Flow Cytometry Terms And Definitions Most Scientists Get Wrong

Written by Tim Bushnell, Ph.D.

The most important part of executing a flow cytometry experiment correctly is actually understanding what you are doing. This means you must understand the terms and definitions that are critical to the field of flow cytometry.

As a scientist, you should not just place your faith in a specialized technician. You should not blindly agree with the data you see in front of you without you yourself knowing what 'logicle scaling' means, what 'differential pressure' means, what happens when you change the differential pressure on an instrument, and so on.

You must also be able to communicate your methodologies and results intelligently. This means, for example, knowing the difference between flow cytometry, flow cytometry cell sorting, and FACS analysis: the latter merely being a trademarked term “owned” by a flow cytometry company.

Top 12 Most Commonly Misunderstood Flow Cytometry Terms

To help resolve this confusion, we have worked with our 700+ Mastery Class members to compile a list of the top 12 most commonly unknown or commonly misunderstood flow cytometry terms here…

1. Autofluorescence

Autofluorescence is the term given to describe the natural fluorescence that occurs in cells. The common compounds that give rise to this fluorescence signal include cyclic ring compounds like NAD(P)H, Collagen, and Riboflavin, as well as aromatic amino acids including tyrosine, tryptophan, phenylalanine. These compounds absorb in UV to Blue range (355-488 nm), and emit in the Blue to Green range (350-550 nm).

The consequence of this autofluorescence is the loss of signal resolution in these light ranges and a decrease in signal sensitivity. Autofluorescence typically increases with cell size. Larger cells have more autofluorescence than small cells due to the simple fact that the larger cells often contain more autofluorescent compounds. 

2. Logicle Scaling

Logicle scaling is an implementation of biexponential scaling published by the Herzenberg lab at Stanford. The biexponential scale is a combination of linear and log scaling on a single axis using an arcsine function as its backbone.

The “logicle” implementation of biexponential was implemented in many popular software packages like FACSDiva and FlowJo. Other types of biexponential scaling exist, including Hyperlog.

Biexponential scales are more generally referred to as hybrid scales and include other variations like lin/log or log with negative. More information on logicle scaling can be found here: Parks DR et al. A new “Logicle” display method.

3. Fluorescence Minus One, or FMO Control

The Fluorescence Minus One control, or FMO control is a type of control used to properly interpret flow cytometry data.  It is used to identify and gate cells in the context of data spread due to the multiple fluorochromes in a given panel.

An FMO control contains all the fluorochromes in a panel, except for the one that is being measured. For example, in the 4-color antibody panel, there would be four separate FMO controls, as shown in the table below. The FMO control ensures that any spread of the fluorochromes into the channel of interest is properly identified.

4. Sheath Fluid

Sheath fluid is the solution that runs in a flow cytometer.  Once the sheath fluid is running at laminar flow, the cells are injected into the center of the stream, at a slightly higher pressure. The principles of hydrodynamic focusing cause the cells to align, single file in the direction of flow.

Depending on experimental needs, different formulations of sheath fluid can be used. Many labs purchase pre-mixed phosphate-buffered saline, while other labs use their own Hepes-buffered saline. The latter is particularly useful for high-pressure cell sorting as Hepes controls pH better at high pressure than phosphate buffers do.

Finally, since the sheath and sample core stream do not mix, you can use water as a sheath fluid on analyzers. Adding a small amount (0.1%) of 2-phenoxyethanol will help as this serves as a surfactant, helping keep the system flowing by reducing the surface tension.

5. Sample Injection Port

In flow cytometry, suspended cells are moved through the flow cytometer's tubing all the way to the interrogation point and finally into the waste (or to be sorted and recovered). To do this, the fluidics components of the flow cytometry are required.

The fluidics are comprised of three components. The first component is a running fluid (or sheath fluid – see above), that runs through the system in laminar flow. The movement of this sheath can be achieved by several mechanisms, the most common method using pressure provided by pumps.

The second component of the fluidics is the sample injection port (SIP). This is where the sample is pushed through the tubing to be introduced to the sheath fluid. Based on the principles of hydrodynamic focusing, these cells are strung out, single file, in the direction of the flow, where they will pass the interrogation point.

The third and final main component of the fluidics is the flow cell, which is where the first two components and the suspended cells themselves come together. 

6. Isotype Control

The“ isotype” in isotype control refers to the genetic variation in the heavy and light chains that make up the whole antibody moiety. In mammals, there are 9 possible heavy chain isotypes and two light chain isotypes. Every antibody will have a specific isotype, and this is available on the technical information spec sheet.

For example, you might have an antibody with an isotype of IgG1, kappa. This indicates the heavy chain is of the IgG1 isotype. Where things get interesting is that these isotypes can have different non-specific binding affinity to cells, which has lead to investigators using isotype controls, as a control to identify where cells are positive or negative.

The issue with isotype controls is that they are not proper gating controls. Instead, these controls should only be used for identifying potential blocking problems. For more on this, read the following paper: Herzenberg, LA et al. Interpreting flow cytometry data.

7. Antibody Titration

Titration is the process of identifying the best concentration to use an antibody for a given assay. While the antibody's vendor will provide a specific concentration to use, this may not be appropriate for your assay.

Performing titration is a simple process: fix the cell concentration, the time of incubation, the volume of reaction, and temperature. The graph below displays an antibody that was used to stain 1×106 cells for 20 minutes on ice. To identify the best concentration to use, the modified Staining Index (SI) was calculated and plotted against the concentration. As is shown by this figure, as the concentration increases above 0.5 μg/ml, the SI decreases, due in part to the increase in the background (non-specific staining).

At concentrations below 0.25  μg/ml, the SI decreases because the antibody is no longer at a saturating concentration. Therefore, the best concentration to use is between 0.25-0.5 μg/ml. Titration helps save money and reagents, ensures the optimal concentration of reagent is being used, and avoids background due to high concentration of antibodies.

8. Differential Pressure

Differential pressure-based flow cytometers currently dominate the market. These systems have two pressure regulators. The first is at a constant pressure that sets how fast the fluids run through the system. The second is regulated by you, the scientist.

As the sample pressure goes from low, to medium, to high, the pressure on the sample increases. This results in the volume of the sample increasing (from ~15 ml/min to ~60 ml/min). The difference between the sample pressure and the sheath pressure is the differential pressure. This controls the width of the core stream and the total number of cells passing the laser intercept point. 

9. Jablonski Diagram

The Jablonski diagram illustrates the electronic states of a molecule as well as the transitions between them. These states are arranged vertically by energy, and grouped horizontally by spin multiplicity.

In the below image, nonradiative transitions are indicated by straight arrows and radiative transitions by squiggly arrows. The vibrational states of each electronic state are indicated with parallel horizontal lines. For flow cytometry, it is important to note that the energy of the emission is usually less than that of the absorption. As such, fluorescence normally occurs at lower energies or longer wavelengths.

10. Bandpass, Shortpass, And Longpass Filters

A bandpass filter is a filter that allows light between a set wavelength to pass through it, reflecting only light above and below the set wavelength. For example, a bandpass filter with a wavelength of 550/40nm would allow light between 530nm and 570nm to pass through, but reflect light below 530nm and above 570nm.

A shortpass filter is a filter that allows light over a set wavelength to pass through and reflects light above the set wavelength. For example, a shortpass filter with a wavelength of 450nm would allow light with a wavelength less than 450nm to pass through the filter, but reflect light higher than 450nm.

A longpass filter, on the other hand, is a filter that allows light over a set wavelength to pass through and reflects light below the set wavelength. For example, a longpass filter with a wavelength of 670nm would allow light with a wavelength greater than 670nm to pass through the filter, but reflect light lower than 670nm.

11. Spectral Profile And Spectral Viewer

Every fluorophore has a unique excitation and emission profile which is usually displayed on a spectral viewer, or spectral graph. The combination of the excitation and emission profiles is the fluorophore's spectral profile. Every fluorophore has a peak excitation wavelength (the wavelength at optimal excitation) and a peak emission wavelength (the wavelength of optimal detection). Each fluorophore will also have a much larger range of excitation and emission wavelengths at reduced optimization. This “curve” is what is displayed on a spectral viewer.

The spectral profile of a fluorophore is used to determine the excitation and detection efficiency at any given wavelength. The spectral profile aids in panel design and selecting optimal fluorophores for a given instrument. The spectral profile can also help in determining compensation considerations. There are numerous resources available to view the spectral profiles of various fluorophores, including this resource from eBioscience.

12. FACS Analysis

Flow cytometry is the science of measuring the physical and biochemical processes on cells and cell-like particles. This analysis is performed in an instrument called the flow cytometer.  FACS Analysis is the shorthand expression for this type of cell analysis. The term FACS stands for Fluorescent Activated Cell Sorting, a term first coined by Len Herzenberg in the 1970's, and later trademarked by Becton Dickinson. Since that time, FACS has come to be used as a generic term for all of flow cytometry, even though it is a specific trademarked term.

Understanding the above terms, as well as the proper definition of each term, will help you perform better flow cytometry experiments. It will also help you intelligently communicate your methodologies and results in grant submissions and peer-reviewed paper submissions. By being careful not to misuse words such as FACS Analysis, or misunderstand words such as logicle scaling, you will be seen as competent in the field of flow cytometry and your grants and paper will stand better odds of being awarded and passing the dreaded third reviewer, respectively.

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.