![]() It has many innovative uses but we mainly use it at MSRI as a cell biology tool to study immune cells. Understanding these processes will also allow us to rationally design more specific treatments for MS.įlow cytometry is a technique used to study the surface and interior of immune or other cells. Flow cytometers and Cell sorters are invaluable pieces of laboratory equipment which allow us to dissect the processes in immune cells which lead to the development of MS.This is the goal of the research we do at MSRI. The key to understanding this process in MS is to define the stages of function and malfunction of T regulatory cells and the resultant dysfunction of unrestrained T effector cells.In the case of autoimmunity such as MS, the T regulatory cells may not only fail to function but may change to function like T effector cells which cause inflammation and tissue (myelin) damage. T regulatory cells normally act to suppress the function of other immune cells called T effector cells, which prevents the development of autoimmunity. ![]() The failure of T regulatory cells is the result of a long developmental process which precedes the onset of clinical MS and which involves genetic inheritance as well as environmental influences acting on these cells to ultimately disturb their normal function.This type of disease is primarily due to a defect in function of certain immune cells known as T regulatory cells. Restricted autoimmune diseases like MS are confined to one tissue or organ.They reflect a widespread derangement in immune function. Systemic autoimmune diseases like Lupus affect the whole body.MS is an autoimmune disease which damages myelin and starts a chronic degenerative process in the brain and spinal cord.It is down to the user preference as to which display is preferred, but sometimes discrete populations of cells are easier to visualize on contour diagrams.Influenza viruses, 3D illustration showing surface glycoprotein spikes hemagglutinin and neuraminidase FSC contour plot plus outliers FSC, forward scatter SSC, side scatter. Examples of contour maps are shown in Figure 14.įig. ![]() PB, Pacific Blue FSC, forward scatter SSC, side scatter.Įvents can also be displayed as a dot plot where no density information is shown or as a contour map to show the relative intensity of scatter patterns. Forward and side scatter gating is often used to remove dead cells which have increased autofluorescence and non-specific binding of antibodies however, including a viability dye is a much more reliable method.įig. Data can also be plotted as a combination of fluorescence and forward or side scatter as seen with CD45 Pacific Blue in Figure 13B. The forward scatter threshold can be increased to avoid collecting these events, or they can be removed by gating on the populations of interest (Figure 13A). Debris and dead cells often have a lower level of forward scatter and are found at the bottom left corner of the density plot. ![]() The light scatter patterns of granulocytes, monocytes and lymphocytes allow them to be distinguished from cellular debris and dead cells. The red/yellow/green/blue hot spots indicate increasing numbers of events resulting from discrete populations of cells. As can be seen in the density plots in Figure 13, red cell lysed whole blood has several distinct populations. Distinguishing populations of cells can be relatively straight forward for cell lines where there is only one type of cell, but it can be more complex for samples where there are multiple cell types. Forward and side scatter give an estimation of the size and granularity of the cells respectively, although this can depend on several factors such as the sample, the wavelength of the laser, the collection angle and the refractive index of the sample and the sheath fluid. The first step in gating is often distinguishing populations of cells based on their forward and side scatter properties. In addition to this flow guide we have a handy PDF available to download on our gates, plots and regions page, which can be used as a quick reminder. Here we will show what the common flow cytometry graph outputs look like and how in a few simple steps you can identify different cell populations that have been stained with antibodies conjugated to fluorophores. Gates and regions are placed around populations of cells with common characteristics, usually forward scatter, side scatter and marker expression, to investigate and to quantify these populations of interest. Flow cytometry data analysis is fundamentally based upon the principle of gating. ![]()
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