title: Discrimination of T-cell subsets and T-cell receptor repertoire distribution.
abstract: Flow cytometry-based analysis of T-cell receptor (TCR) repertoires is an essential tool for the detection of clonal T-cell expansions in physiologic and pathologic conditions. Individual T-cell subsets can be investigated based on their surface properties. The aims of our study were to provide reference values for various disease settings and delineate the contribution of individual TCR repertoires to the human T-cell differentiation pathway. We analyzed blood of 66 healthy subjects aged 0 (cord blood) to 72 years. Lymphocyte subpopulations and TCR repertoires were simultaneously explored using antibodies specific to CD3, CD4, CD8, CD45RA, CCR7, CD27, CD57 and a set of 25 antibodies detecting human TCR-Vβ chains. Statistical analysis included Wilcoxon, paired t and ANOVA tests. Initially, TCR expansion values were calculated based on the analysis of TCR-Vβ distribution on CD4+ and CD8+ T cells. We then established gating strategies and an algorithm for data analysis allowing for discrimination of T-cell subsets and TCR distribution. Dominant TCR expansions were present within effector as opposed to central/effector memory or naive cells, e.g., median TCR-Vβ expansion rate was highest on CD45RA+/CCR7- effector CD4+/8+ cells (eight and 11-fold, respectively). Remarkably, TCR expansions were missing (0) or very low (0.5) on CD4+ and CD8+ central memory population, respectively. No significant gender-related variability of TCR repertoires was identified, and significant impact of chronic cytomegalovirus infection was shown. Our results serve as reference for future studies elucidating clonal TCR dominance of T-cell subsets.
authors.affiliation: Institute of Medical Immunology, Charité-University Medicine, Campus Virchow-Klinikum, Institutsgebäude Süd, Föhrer Str. 15/Südstr. 2, 13353, Berlin, Germany, isabell.bretschneider@gmail.com.
authors.forename: Isabell
authors.initials: I
authors.lastname: Bretschneider
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Clemente
authors.forename: Christian
authors.initials: C
authors.lastname: Meisel
authors.forename: Manuel
authors.initials: M
authors.lastname: Guerreiro
authors.forename: Mathias
authors.initials: M
authors.lastname: Streitz
authors.forename: Werner
authors.initials: W
authors.lastname: Hopfenmüller
authors.forename: Jaroslav P
authors.initials: JP
authors.lastname: Maciejewski
authors.forename: Marcin W
authors.initials: MW
authors.lastname: Wlodarski
authors.forename: Hans-Dieter
authors.initials: HD
authors.lastname: Volk
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D015496:CD4-Positive T-Lymphocytes / Q000276:immunology*; D018414:CD8-Positive T-Lymphocytes / Q000276:immunology*; D002454:Cell Differentiation / Q000276:immunology; D002648:Child; D002675:Child, Preschool; D005260:Female; D005312:Fetal Blood / Q000166:cytology / Q000276:immunology; D005434:Flow Cytometry; D006801:Humans; D016130:Immunophenotyping / Q000379:methods; D007223:Infant; D007231:Infant, Newborn; D007963:Leukocytes, Mononuclear / Q000166:cytology / Q000276:immunology; D008297:Male; D008875:Middle Aged; D011948:Receptors, Antigen, T-Cell / Q000276:immunology*; D012016:Reference Values; D018709:Statistics, Nonparametric; D016176:T-Lymphocyte Subsets / Q000276:immunology*; D055815:Young Adult
chemical_list: D011948:Receptors, Antigen, T-Cell