Optimized quantification of lymphocyte subsets by use of CD7 and CD33
Department of Laboratory Medicine, Donauspital, Vienna, Austria. .Cytometry Part A (Impact Factor: 2.93). 03/2013; 83A(3). DOI: 10.1002/cyto.a.22245
Identification and quantification of lymphocyte subsets is based on the expression of specific cell surface antigens. As only a minority of these structures is lineage-restricted gating strategies were established, which should permit to include a maximum of lymphocytes, to reach a high purity within the gate and to avoid specific loss of subsets. Two problems remain: First, the incomplete removal of nonlymphoid cells when CD14 is used to exclude them from the lymphocyte gate. Second, the lack of a restricted marker to identify NK cells that are usually defined as CD3(-) /CD16/56(+) lymphocytes, though contaminating monocyte subsets share the expression of CD16, respectively, CD56. This study demonstrates the advantage of CD33 over CD14 at the creation of a pure lymphocyte gate, because CD33 enables the exclusion of all monocyte subpopulations as well as basophils and granulocytes. Independent of the applied NK cell marker mean purity was significantly higher, when CD33 was used (P < 0.001). For the identification of NK cells, CD7 was compared with CD16/56 and with single stained CD56. CD7 and CD16/56 exhibited as equivalent in various CD33 settings (P ≥ 0.173), whereas the mean proportion of CD56(+) NK cells was significantly lower (P ≤ 0.008). Use of CD14 entailed a significantly higher amount of CD3(-) /CD16/56(+) cells than of CD3(-) /CD7(+) cells (P = 0.008) because of the remaining CD14(-) /CD16(+) monocytes. As CD7 is restricted to T cells and NK cells in peripheral blood, misclassification of contaminating monocytes is avoided and CD7(+) NK cells can be identified by lack of CD3. Applying this new selection of mAbs, we reached a mean purity of ≥99.50% within the revised lymphocyte gate. As gates can be set very broadly, high inclusivity and high purity are not mutually exclusive. We propose the adoption of CD7 and CD33 for the quantification of lymphocyte subsets. © 2013 International Society for Advancement of Cytometry.
- Cytometry Part A 07/2014; 85(7). DOI:10.1002/cyto.a.22476 · 2.93 Impact Factor
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ABSTRACT: Pregnant women experience increased morbidity and mortality after influenza infection, for reasons that are not understood. Although some data suggest that natural killer (NK)- and T-cell responses are suppressed during pregnancy, influenza-specific responses have not been previously evaluated. Thus, we analyzed the responses of women that were pregnant (n = 21) versus those that were not (n = 29) immediately before inactivated influenza vaccination (IIV), 7 d after vaccination, and 6 wk postpartum. Expression of CD107a (a marker of cytolysis) and production of IFN-γ and macrophage inflammatory protein (MIP) 1β were assessed by flow cytometry. Pregnant women had a significantly increased percentage of NK cells producing a MIP-1β response to pH1N1 virus compared with nonpregnant women pre-IIV [median, 6.66 vs. 0.90% (P = 0.0149)] and 7 d post-IIV [median, 11.23 vs. 2.81% (P = 0.004)], indicating a heightened chemokine response in pregnant women that was further enhanced by the vaccination. Pregnant women also exhibited significantly increased T-cell production of MIP-1β and polyfunctionality in NK and T cells to pH1N1 virus pre- and post-IIV. NK- and T-cell polyfunctionality was also enhanced in pregnant women in response to the H3N2 viral strain. In contrast, pregnant women had significantly reduced NK- and T-cell responses to phorbol 12-myristate 13-acetate and ionomycin. This type of stimulation led to the conclusion that NK- and T-cell responses during pregnancy are suppressed, but clearly this conclusion is not correct relative to the more biologically relevant assays described here. Robust cellular immune responses to influenza during pregnancy could drive pulmonary inflammation, explaining increased morbidity and mortality.Proceedings of the National Academy of Sciences 09/2014; 111(40). DOI:10.1073/pnas.1416569111 · 9.67 Impact Factor
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