Because we can’t see them, it’s easy to forget how many systems and processes are going on inside our bodies all the time. We have great tools for looking at the function of organs or systems in our bodies, but what about individual cells? How can we understand the function of different cells, whether they’re healthy or not, or what they’re doing at a given time?
Well, one really powerful technique that scientists and doctors rely on is called flow cytometry. This is a technique that lets us analyze both populations of cells as well as characteristics of individual cells. For example, we could determine which types of cells are circulating around in a person’s blood, and we can also find out what is happening inside or on the surface of individual cells in that population.
That might sound confusing and complicated, but you can think about a flow cytometer almost like a grocery store scanner. The checkout machine uses lasers to scan the barcodes of different foods to tell them apart. You can also use the checkout machine to determine an object’s weight which can provide some additional information about the item. Say, I went to the grocery store and grabbed a basket full of citrus fruits that were all orange in color. Some could be grapefruits and some could be oranges which are similar in color and shape. When I got to the register, I would put the fruits on the conveyor belt and they would be scanned one by one. The clerk could use the little barcode stickers on each fruit to figure out exactly how many oranges I grabbed and how many grapefruits I grabbed.
The main idea of flow cytometry is pretty similar to the grocery scanner. We basically feed cells one by one through the beam of a laser, and we are able to learn about the unique identity of individual cells. And, I know what you’re thinking, cells don’t have barcodes like foods in a grocery store. It’s definitely true that cells in our bodies don’t have the little plastic stickers on them, but there are ways of telling cells apart.
Think about comparing the oranges and grapefruits we bought at the store. They look pretty similar on the outside, but are clearly distinguishable by their internal color and flavor. Putting a barcode sticker on each fruit makes it super quick and easy for the laser of the checkout machine to tell different items apart, and this is exactly what we want to achieve in flow cytometry.
The cells in our bodies do share similar characteristics to each other, just like oranges and grapefruits do, but each cell type has some defining features that make it unique. These could be external features like the types of proteins that stick out on their surface, or the size of the cell, or they could be internal identifiers like the types of organelles a cell has or the proteins it makes. Just like fruits at the grocery store can be tagged with a sticker to make them visible to the laser scanner, in flow cytometry, we are adding tags to cells, so they can be scanned by the laser in the flow cytometer. This allows us to learn about cells at a population level and an individual level.
So, let’s dive into how this tool actually works. In order for the laser in the flow cytometer to scan our cells, we have to barcode them, and since we can’t just place tiny grocery store stickers on each individual cell, we’re going to rely on antibodies to help us tag our cells and make them visible to the flow cytometer. Like I said before, each cell type has unique identifying features, and we can mark those features with antibodies to create our cellular barcodes. Antibodies are great because they bind super specifically to one molecule, but this also means that we have to choose our antibodies carefully.
For instance, if I had a population of different immune cells, and I wanted to figure out the percentage of different cell types in my sample, I could do this by adding antibodies that are specific for each cell type I wanted to measure. I might add one antibody that binds a protein on T-cells, one that binds Natural Killer cells (or NK cells), one that binds neutrophils and so on. Eventually I will reach a limit of how many antibodies I can include in one sample, and I’ll show you why in one second. If I chose an antibody that binds to a protein found on both NK cells and T-cells, that wouldn’t help me answer my original question so I need antibodies that will help me clearly distinguish between different cells in one population.
Picking antibodies is a big part of flow cytometry because these markers determine which parts of a cell’s unique features will be their identifying barcode. If we don’t pick antibodies that are specific for the cell type or proteins we want to study, we might get mixed information about our cells. Non-specific antibodies would be like oranges and grapefruits having the same barcoded sticker to identify both of them. The checkout machine would just say that you bought “large citrus fruits” but you wouldn’t know about the unique identities of those fruits.
The good news is that there are lots of different antibodies available for us to use, so we can create specialized barcodes for virtually any cell. Some antibodies stick to proteins on the outside surface of the cell, but others are specific for proteins inside the cell. Doing internal staining is a bit more complicated than simply sticking an antibody to the surface of the cell because it involves fixing (or preserving our cells) and permeabilizing the cell membrane (or making it porous). This allows antibodies to move through the holes in the membrane and find their target on the inside of the cell.
Ok, so once we’ve chosen the antibodies we want to use, we have to make sure that these antibodies can be identified by the flow cytometer. To do this, we utilize something called a fluorophore, which is a molecule that absorbs a certain wavelength of light and emits a color that can be detected. Often, the antibodies we use to tag specific features of our cells will be directly linked to a fluorophore. Other times, we have to add a second antibody that binds to the first one we added. If you have more than one antibody in a sample, it’s important to make sure that the fluorophores are different colors otherwise you’ll lose the ability to tell your proteins, and therefore your cells, apart.
So, sticking with our immune cell example, once all the cells have been tagged with fluorescent antibodies, it’s time to actually analyze them in the flow cytometer. Like I said, the power of this technique is that it gives us information about individual cells, so we have to make sure that only one cell is analyzed at a time, just like the checkout machine at the grocery store. The flow cytometer sucks up our mixture of cells and then funnels them so that all the cells have to line up one after the other. The cells are then injected into a stream of sheath fluid which makes sure they move at a constant rate through the rest of the machine. It’s like the conveyor belt at the check out machine moving items along at a constant rate.
After the cells make it into the sheath fluid, they are passed through the main analysis chamber of the machine. Individual cells move past a laser beam which gives us lots of great information about the cell. The laser first gives us a measure of the forward scatter and side scatter of the cell. Forward scatter tells us about the size of the cell. Larger cells have a larger forward scatter. Side scatter measures something called granularity. This sounds confusing, but basically some cells are packed full of more proteins or organelles than others are and cells with more stuff inside their cytoplasm are considered more granular so they will have a larger side scatter measurement. Here’s what this data actually looks like. Forward scatter is on the X-axis, and is commonly abbreviated “FSC” and side scatter is on the Y axis as “SSC.” Each dot on the plot represents data from an individual cell, so if we think about our sample of immune cells, we’re looking at the entire cell population we fed into the machine. Even if you were someone who just passed by the machine without knowing what cells went into it, you could probably already tell that there are different clusters of cells in this graph. If we just look at the X-axis, and draw a vertical line, all of the cells around this line have a similar size, but you’ll also notice that cells of the same size can still be very different because of their granularity.
The other type of information we get from a flow cytometer is fluorescence data. When the laser hits a cell, it excites the fluorescent antibodies we tagged it with. This fluorescent signal is picked up by detectors that are specific for different colored fluorophores. Different flow cytometer machines will have a different number of fluorophores they can detect, so the type of machine you use dictates how many antibodies you can include in one sample. Remember, the antibodies are only there as markers of the unique features of a cell, so more fluorescence means the cell has more of whatever the antibody is bound to. Let’s look at another graph, so I can show you what I mean.
This time we’re going to plot the number of cells vs the intensity of one specific fluorescent signal. Back at the beginning of our experiment with the immune cells, we added antibodies that stuck to different types of cells. Since each fluorescent signal is picked up by a different detector, we can only look at data from one detector at a time. Let’s look at fluorescence data from the T-cell marker that had a red signal. In this graph, on the Y-axis we’re looking at how many cells in our entire population were fluorescing. The X-axis is the intensity level of the fluorescent signal. The further you go to the right on the graph, the brighter the signal is. A taller peak indicates that there are more cells in our population that exhibited that level of fluorescence. In this graph, we can see two peaks. The peak further to the right represents cells that have a higher level of red fluorescence. The peak further to the left shows cells that did not fluoresce a red color, so they do not express the protein our red antibody was bound to. This graph shows a clear distinction between cells that express a T-cell marker (and therefore fluoresce red) and cells that do not. We can do this same thing for each of the fluorescent markers we used, and we can use analysis software to determine the percentage of different immune cells in our population.
Now, this is just one application for flow cytometry. We can use this tool to look at several proteins at the same time to separate cell populations even more specifically or we can compare the expression of proteins between different people or under different conditions. This information helps us better understand what individual cells “look” like and how they respond to their environment. This technique opens up lots of avenues for exploration from diagnosing different conditions in the clinic to testing hypotheses in the lab, and all of this information can help us better understand how cells work and what we might be able to do to keep them healthy.
