Since its development, flow cytometry gave a relevant contribution to the field of Immunology. Its unique potential to analyse multiple parameters at the single cell level allowed the identification of unknown cell subsets with specific roles in immunoregulation as well as in the pathogenesis of several diseases. More recently, with the advent of new equipments and fluorochromes, the possibility exists to analyse simultaneously a large number (up to 19) of parameters in a single cell. This strategy, defined polychromatic flow cytometry (PFC), has been widely utilised in the last years for the fine analysis of immune cell phenotypes, including antigen-specific T lymphocytes, B cell subsets, and the intracellular phosphoproteome, among others. A huge amount of data can be generated by such an approach, and their interpretation could become a very complex and time-consuming task. Protocols for performing PFC will be discussed in this chapter, together with some guidelines for data interpretation and analysis.
Investigating T cells by polychromatic flow cytometry / Lugli, E; Troiano, L; Cossarizza, Andrea. - ELETTRONICO. - 514:(2009), pp. 47-63. [10.1007/978-1-60327-527-9_5]
Investigating T cells by polychromatic flow cytometry
COSSARIZZA, Andrea
2009
Abstract
Since its development, flow cytometry gave a relevant contribution to the field of Immunology. Its unique potential to analyse multiple parameters at the single cell level allowed the identification of unknown cell subsets with specific roles in immunoregulation as well as in the pathogenesis of several diseases. More recently, with the advent of new equipments and fluorochromes, the possibility exists to analyse simultaneously a large number (up to 19) of parameters in a single cell. This strategy, defined polychromatic flow cytometry (PFC), has been widely utilised in the last years for the fine analysis of immune cell phenotypes, including antigen-specific T lymphocytes, B cell subsets, and the intracellular phosphoproteome, among others. A huge amount of data can be generated by such an approach, and their interpretation could become a very complex and time-consuming task. Protocols for performing PFC will be discussed in this chapter, together with some guidelines for data interpretation and analysis.
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