From Purity To Biosafety, Understanding The Cell Sorting Process
The Power Of Flow Cytometry In Cell Sorting
Often, cell sorting is described as trying to find a needle in a haystack. In 2008, David Brown wrote an article on cell sorting for the Washington Post. In that article, he wrote :“Finding and sorting a few cells from a great mass of them is sometimes likened to finding a needle in a haystack. But it’s actually more watching a parade of 10,000 undertakers, and spotting the two who are wearing yellow ties, and the three who are wearing pink ties, and getting them out of the line, without making everyone else lose step.”
This really captures the essence of the sorting process. It is also a very scary process for the average researcher. After spending hours and hours preparing samples, they are often handed off to an operator who puts them into the cell sorter. With fingers crossed, the researcher hopes the cells are sorted correctly, and there are enough of them to perform the downstream experiments that are the real goal of the process.
Most of the time, things go right, but now and then, they fail, sometimes catastrophically. Cell sorting is a balancing act of optimizing the sample and system to get the best yield with the highest purity in the shortest time possible. So we turn our attention to how to win that balancing act.
A Word About Biosafety
Before continuing onto the meat of this discussion, it is important to take a moment to discuss biosafety. Cell sorters are designed to generate aerosols, and these are of the size to settle in the deep lung if inhaled. This is important because in 1990 there was a report of a laboratory-acquired infection due to aerosolization during centrifugation. While aerosolization of HIV in animal studies have not shown infection, this article by Jones and Brosseau from 2015 discusses this issue in more detail.
The International Society for the Advancement of Cytometry, which in many ways can be considered the industry standard, published their first comment on biosafety in 1997, reviewed it in ’99, and most recently revised it in 2014. Central to this biosafety of cell sorting is an assessment of the dangers. A good place to start, if you have not already, is to work with your institutional biosafety officer. Safety involves multiple levels of controls from engineering controls to personal protective equipment. Testing and validation is also a critical step. Your biosafety officer can help you with this process. Don’t shirk in this area.
The Sorting Balancing Act
Cell sorting is a combination of a numbers game (Recovery), quality of output (Purity) and speed. For any experiment, the end goal is going to be measured by these three characteristics, and as soon as one of these measures is more heavily favored, the other two must be compromised in some manner.
When designing a sorting experiment, start with the question of what will the cells be used for after sorting, and how many cells will you need for those experiments? That will set the minimum recovery that is needed. The second question is how pure do you need the cells? The requirements of the downstream assay will also dictate the purity needed.
The cell type being used will, in part, dictate the speed of sorting. Smaller cells can be sorted faster because a smaller nozzle can be used.
When you start a cell sort it’s important that you are aware of the downstream analysis and assays that you want to run. This will determine how you perform the sort and how you determine if your sort was successful or not.
Successful cell sorting involves balancing recovery, yield and speed. What do these three terms mean and what influences each of these factors?
- Speed is how fast your cells can be sorted. This is influenced by the size of the cell. The larger the cell the slower the rate that cells can be sorted. This is because larger cells require larger nozzles. Larger nozzles, in turn, require lower sheath pressures to run and lower sheath pressure influences the rate at which droplets can be generated. The lower the sheath pressure, the slower droplets can be generated. This finally leads into the Poisson statistics, which is a way to describe the arrival of a given number of events per unit time, with the caveat that each event arrives independently of the previous event. The relationship between nozzle size and droplet frequency are shown in Figure 1.
Figure 1: Relationship between frequency and droplet generation. The larger the nozzle, the lower the frequency, which in turn impacts how many events per second one should sort at. The dashed lines represent the upper and lower limits for a given nozzle, based on the data in Arnold and Lannigan (2010) Curr. Protoc. Cytom.51:1.24.1-1.24.30.
- Recovery is how many target cells are recovered. This is generally defined as the number of particles of interest in the sorted sample divided by the number of particles of interest sorted based on the sort report. Several factors can influence recover. How well the sort streams are aimed into the collection tubes is one thing to consider, as is how the collection tubes are treated. Since the droplets containing the cells are charged, it is important to neutralize the charge of the catch tube. This can be done by coating the tubes with protein. The easiest way to do this is by adding your staining buffer with protein to the catch tubes and let them roll around for about 30 minutes before use. Additionally the sorting ‘envelope’ that is used can also impact the recovery, as will an inaccurate drop delay.
- Purity is a measure of how many target cells were sorted. This is defined as the number of target cells in the sorted sample divided by the total number of particles in the sorted sample. The goal of the sorting experiment is to get many target cells with as few other contaminating cells. These contaminating cells can come from poorly sort drop delay, poorly resolved doublets, dead cells and poorly defined gating strategies. When sorting, viability dyes are a must, and dump channels are strongly encouraged. Also, simple sample preparation tips to reduce clumping should be employed. These include adding a small amount of EDTA to staining buffer, adding 10 Units per mL of DNAse I to reduce clumping caused by free DNA and filtration just before the sort.These three factors also influence the yield of the sort. The yield is the number of target cells in the sorted sample divided by the total number of target cells in the original population. The second number is usually calculated based on the frequency of the target population, as defined by the gating strategy, times the number of cells started with.
What Is The Sort Envelope?
When the sort operator is setting up the sort, they will often ask what sort mode to use. The sort mode will impact the sort window, and thus the purity and yield of the sort. Following the recommendations derived from Poisson statistics, the goal is to have 1 cell per every 4 droplets. After the cell in interrogated, the system will used a value called the drop delay, to determine which drop to charge. The predicted location of the cell in the droplet will also impact how big the drop envelope is. This is shown in Figure 2.
Figure 2: Impact of predicted positive event and sort window size.
On the left is when a one-drop window is used. This requires the positive event to be predicted to be in the center of the drop. If the predicted location of the positive event is not in the center, then the drop will not be sorted. As you can imagine, this will reduce the recovery of the event cells as much as 75%. Typically one-drop windows are used when high purity is required, such as for single-cell genomics.
On the right is when a two-drop window is used. In this case the predicted location of the positive event is off-center. With a two drop sort window, the second drop is sorted with the interrogated drop to ensure that the target cell is captured. This is good for high purity sorts with good yields. In these cases, if there is a contaminating cell predicted to be close to the target cell, these cells are not sorted, to ensure the purity of the sorted population.
There is a third sorting option, which focuses on maximizing recovery. In this case, contaminating cells are not considered, and if there is a target cell in a drop, it is sorted. This maximizes the recovery of the target cells, but decreases purity.
Thus, knowing how pure your sorted population needs to be can help determine the specifics of the sort window to be used.
Putting It All Together
When designing a sorting experiment, there are several considerations. One of the first important things is to meet with the sort team and discuss the cells that will be sorted. This way, the proper biosafety procedures are put in place.
Moving on to the downstream application that the cells will be used for can help determine how many positive cells are needed. These calculations are discussed here, and shown in Figure 5. This table also can help determine how many cells to start with. Of course, if the time to sort is going to be too long, one should consider some enrichment steps before going to the sorter. In parallel with the number of cells needed is the purity of the population, which leads to making a decision on the sort window, as discussed above.
Looking at the balancing act of speed, purity and recovery in cell sorting is the third area to consider. Speed of sorting is dictated by the size of the cells, which impact the size of the nozzle and therefore the pressure of the sheath fluid. The pressure impacts droplet generation and following Poisson statistics, sorting should be conducted with an event rate that is 1/4th droplet generation rate.
Decisions as to the sorting mode help dictate the purity and recovery of the target cells. If recovery is the main goal, a sort mode that captures all the target cells, regardless of the presence of contaminating cells will give the most recover, but sacrifices purity. If purity is more important, recovery must be sacrificed to ensure that purity is not compromised. In the extreme case where the downstream application demands the highest purity cells, a more extreme sort mode should be employed which sacrifices all but the most perfectly aligned target cells, reducing recovery even more.
In the end, consideration of all good sorting experiments starts with the needed outcome – how many cells are needed for the downstream application. From that determination come all the next considerations and calculations. Taken together, the number and purity of the target cells is balanced by speed of the sort. Since the sort speed is often fixed based on cell size, the consideration of the sort window becomes important in helping to define recovery and purity.
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