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Multicolor Flow Cytometry and High-Dimensional Data Analysis to Probe Complex Questions in Vaccinology.
Cole, Megan E; Guo, Yanping; Cheeseman, Hannah M; Pollock, Katrina M.
  • Cole ME; The Pirbright Institute, Surrey, UK.
  • Guo Y; Cancer Research UK Flow Cytometry Translational Technology Platform, Cancer Institute, UCL, London, UK.
  • Cheeseman HM; Department of Infectious Disease, Imperial College London, London, UK.
  • Pollock KM; Department of Infectious Disease, Imperial College London, London, UK. k.pollock@imperial.ac.uk.
Methods Mol Biol ; 2414: 433-447, 2022.
Article in English | MEDLINE | ID: covidwho-1588848
ABSTRACT
Vaccines induce a highly complex immune reaction in secondary lymphoid organs to generate immunological memory against an antigen or antigens of interest. Measurement of post immunization immune responses generated by specialized lymphocyte subsets requires time-dependent sampling, usually of the blood. Several T and B cell subsets are involved in the reaction, including CD4 and CD8 T cells, T follicular helper cells (Tfh), and germinal center B cells alongside their circulating (c) counterparts; cTfh and antibody secreting cells. Multicolor flow cytometry of peripheral blood mononuclear cells (PBMC) coupled with high-dimensional analysis offers an opportunity to study these cells in detail. Here we demonstrate a method by which such data can be generated and analysed using software that renders multidimensional data on a two dimensional map to identify rare vaccine-induced T and B cell subsets.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Leukocytes, Mononuclear / Flow Cytometry Topics: Vaccines Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-1900-1_23

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Leukocytes, Mononuclear / Flow Cytometry Topics: Vaccines Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2022 Document Type: Article Affiliation country: 978-1-0716-1900-1_23