Literature DB >> 18383316

Nine-color flow cytometry for accurate measurement of T cell subsets and cytokine responses. Part I: Panel design by an empiric approach.

Bridget E McLaughlin1, Nicole Baumgarth, Martin Bigos, Mario Roederer, Stephen C De Rosa, John D Altman, Douglas F Nixon, Janet Ottinger, Carol Oxford, Thomas G Evans, David M Asmuth.   

Abstract

Polychromatic flow cytometry offers the unprecedented ability to investigate multiple antigens per cell. Unfortunately, unwanted spectral overlaps and compensation problems increase when more than four colors are used, but these problems can be minimized if staining combinations are chosen carefully. We used an empiric approach to design, test and identify six-color T cell immunophenotyping reagent panels that can be expanded to include three or more functional or other markers in the FITC, PE, and APC channels without significant spectral limitations. Thirty different six-color T cell surface antigen reagent panels were constructed to identify major T cell subsets and maturational subtypes as defined by CCR7 and CD45RA expression, while excluding monocytes, B and non-viable cells. Staining performance of each panel was compared on cryopreserved cells from a single healthy donor recorded on a multiparameter cell sorter. Ten of the thirty reagent panels offered reliable resolution of T cell major and maturational surface markers. Of these, two panels were selected that showed the least spectral overlap and resulting background increase in the FITC, PE, and APC channels. These channels were left unoccupied for inclusion of additional phenotypic or functional markers, such as cytokines. Careful reagent titration and testing of multiple candidate panels are necessary to ensure quality results in multiparametric measurements. (c) 2008 International Society for Advancement of Cytometry.

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Year:  2008        PMID: 18383316      PMCID: PMC9191630          DOI: 10.1002/cyto.a.20555

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.714


  22 in total

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  24 in total

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