Basics of flow cytometry.

  • Radcliff G
  • Jaroszeski M
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Abstract

In summary, a beginner requires fundamental knowledge about flow cytometric instrumentation in order to effectively use this technology. It is important to remember that flow cytometers are very complex instruments that are composed of four closely related systems. The fluidic system transports particles from a suspension through the cytometer for interrogation by an illumination system. The resulting light scattering and fluorescence is collected, filtered, and converted into electrical signals by the optical and electronics system. The data storage and computer control system saves acquired data and is also the user interface for controlling most instrument functions. These four systems provide a very unique and powerful analytical tool for researchers and clinicians. This is because they analyze the properties of individual particles, and thousands of particles can be analyzed in a matter of seconds. Thus, data for a flow cytometric sample are a collection of many measurements instead of a single bulk measurement. Basic knowledge of instrumentation is a tremendous aid to designing experiments that can be successfully analyzed using flow cytometry. For example, it is important to know the emission wavelength of the laser in the instrument that will be used for analysis. This wavelength is critical knowledge for selecting probes. It is also important to understand that a different range of wavelengths is detected for each fluorescent channel. This will aid selection of probes that are compatible with the flow cytometer. Understanding the complication that emission spectra overlap contributes to detection can be used to guide fluorochrome selections for multicolor analysis. All of these experiment design considerations that rely on knowledge of how flow cytometers work are a very practical and effective means of avoiding wasted time, energy, and costly reagents. Data analysis is a paramount issue in flow cytometry. Analysis includes interpreting as well as presenting data that has been stored in list-mode files. Data analysis is very graphically oriented. There are a number of types of graphic representation that are available to visually aid data analysis. Two standard types of displays are used. These data plots are one-parameter histograms and bivariate plots. A user must be familiar with these two fundamental types of display in order to effectively analyze data. Histograms are the most simple modes of data representation. Histograms allow visualization of a single acquired parameter. Mean fluorescence and distributional statistics can be obtained based on markers that the user can graphically set on the plot. Percentages of positively expressing particles relative to a control sample can also obtained in a similar manner. In addition, multiple histograms can be overlayed on one another to depict qualitative and quantitative differences in two or more samples. Two-parameter data plots are somewhat more complicated than histograms; however, they can yield more information. Two-parameter dot plots of FSC vs SSC allow visualization of both light-scattering parameters that are important for identifying populations of interest. Bivariate fluorescent plots allow discrimination of dual-labeled populations that might remain hidden if histograms were used to display fluorescent data. Two-parameter plots that combine one light-scattering parameter and a fluorescent parameter are useful for analyzing control samples to elucidate the origin of nonspecific binding. Data analysis is very graphically oriented. Experience and pattern recognition become important when using two-parameter data plots for qualitative as well as quantitative analysis. The technique of gating or drawing regions on dual parameter light-scatter plots allows one to exclude information and examine the population of interest by disallowing particles that might confound or interfere with analysis. This is one of the fundamental uses for gating. (ABSTRACT TRUNCATED)

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Authors

  • G Radcliff

  • M J Jaroszeski

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