Approaches in Biomedical Research: Flow Cytometry, Part 2

Our first Flow Cytometry educational series was focused on understanding how flow cytometry works, the types of machines used, and how data is collected. In this second part in the series, we will go over some types of flow cytometry data and how that data is interpreted.

What are the different types of flow cytometry data that are collected?

In flow cytometry, there are a few types of light that are detected by the sensors during the data acquisition. The source of light (which is non-fluorescent) can create two different paths. The first is called Forward scatter (FSC), which is formed as laser light hits a cell, and is turned into a digital version that reflects the size of the cell (Figure 1). Second, this same laser light also causes Side scatter (SSC), which is a measure of the internal complexity of the cell. For example, if there are many granules in the cell, there will be a higher SSC than for a cell with little granularity. Together, this can be very informative for separating different cell types, which can be further combined with fluorescence data, discussed below.

FSC and SSC FigureFigure 1: Detecting size and granularity of the cells by using laser light.

The third type of light detected is fluorescent light. Laser light flashes at cells passing through the cytometer, which results in the emission of different fluorescent colors that are then collected by mirrors and filters and can be decoded and turned into digital data using computer software (as described in part 1 of this series). Cells themselves have natural fluorescence, though this is usually lower in intensity. In order to detect different types of cells, we typically label them with fluorescent-tagged antibodies that are specific to surface or intracellular molecules of that cell. The cells can also be labeled with naturally fluorescent molecules such as Green Fluorescent Protein, or GFP (to be described in more detail in future blogs).

Antibodies are proteins that are produced by the subtype of immune cells called B cells. There are many different antibodies, and each antibody is like a key for a different lock, and can bind to one of the billions of different types of molecules expressed by cells, viruses, and bacteria. This makes them very useful for identifying specific cell types, because one can generate an antibody that binds to a protein only on one specific cell type, such as T cells but not on B cells. There are commercially available antibodies, each one specific to one of thousands of different proteins that each cell expresses. Various companies can produce these antibodies, and then conjugate them to fluorescent dyes (green, red, orange, blue, etc.) that emit different colors of light. In one flow cytometry experiment, we can use a combination of 10-20 of these different antibodies, each with a different color tagged to it, to identify the frequency of specific cells, such as those found in blood.

Using size and granularity data in combination with fluorescence data is also very useful. For example, in blood, lymphocytes are smaller and less granular than monocytes or neutrophils, which are larger and more granular cells. In an example of data from a blood sample, shown in figure 2A, the lymphocytes are first defined from the rest of the cells by size and granularity, and then put into a “gate,” or the drawing around them. Then looking at just this gate, shown in figure 2B, we can ask what kinds of cells there are in the “lymphocyte” region using specific antibodies that bind to different types of lymphocytes, like T cells and B cells for example.

During this particular experiment, we had stained the cells with two different antibodies, specific to either T cells (orange-tagged antibody binding to CD3) or B cells (violet-tagged antibody binding to CD19). This shows us that within the population of cells that are lymphocytes, about 86% of them are labeled as T cells and 6% are B cells.  Of course, the picture shown is a representation of the fluorescent colors turned into a digital format. This type of picture is called a contour plot, with red, green, and blue representing levels of cells detected, with more cells appearing as green and red. The intensity of the axis (either X or Y) reflects the amount of orange or violet light detected, and thus the amount of CD3 and CD19 antigens detected by the antibodies.

figure2Figure 2: Example data from a blood sample, showing (A) lymphocytes gated based on size and granularity, and (B) fluorescent antibody detection of B cells and T cells within the population of lymphocytes. Credit: Data shown was generated in Unutmaz Lab at the Jackson Laboratory.

Stay tuned for the third part of this series, where we will discuss how blood samples are processed in preparation for a flow cytometry experiment, including what part of the blood is relevant to us from an immunological standpoint.

References:
Introduction to Flow Cytometry, Abcam
Flow Cytometry Data Analysis, Biorad
What is Flow Cytometry (FACS Analysis)?, antibodies-online
Flow Cytometry, Wikipedia
Antibody, Wikipedia

 

One thought on “Approaches in Biomedical Research: Flow Cytometry, Part 2

  1. Pingback: Approaches in Biomedical Research: Flow Cytometry, Part 1 – Advances in ME/CFS

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