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Pediatric SARS-CoV-2 infection is often mild or asymptomatic and the immune responses of children are understudied compared to adults. Here, we present and evaluate the performance of a two-panel (16- and 17 parameter) flow cytometry-based approach for immune phenotypic analysis of cryopreserved PBMC samples from children after SARS-CoV-2 infection. The panels were optimized based on previous SARS-CoV-2 related studies for the pediatric immune system. PBMC samples from seven SARS-CoV-2 seropositive children from early 2020 and five age-matched healthy controls were stained for analysis of T-cells (panel T), B and innate immune cells (panel B). Performance of the panels was evaluated in two parallel approaches, namely classical manual gating of known subpopulations and unbiased clustering using the R-based algorithm PhenoGraph. Using manual gating we clearly identified 14 predefined subpopulations of interest for panel T and 19 populations in panel B in low-volume pediatric samples. PhenoGraph found 18 clusters within the T-cell panel and 21 clusters within the innate and B-cell panel that could be unmistakably annotated. Combining the data of the two panels and analysis approaches, we found expected differentially abundant clusters in SARS-CoV-2 seropositive children compared to healthy controls, underscoring the value of these two panels for the analysis of immune response to SARS-CoV-2. We established a two-panel flow cytometry approach that can be used with limited amounts of cryopreserved pediatric samples. Our workflow allowed for a rapid, comprehensive, and robust pediatric immune phenotyping with comparable performance in manual gating and unbiased clustering. These panels may be adapted for large multi-center cohort studies to investigate the pediatric immune response to emerging virus variants in the ongoing and future pandemics.

Almost 2 years into the pandemic and with vaccination of children significantly lagging behind adults, long-term pediatric humoral immune responses to SARS-CoV-2 are understudied. The C19.CHILD Hamburg (COVID-19 Child Health Investigation of Latent Disease) Study is a prospective cohort study designed to identify and follow up children and their household contacts infected in the early 2020 first wave of SARS-CoV-2. We screened 6113 children P = 0.047). Most importantly, children showed sustained seroconversion up to 9 months PSO, and serum antibody concentrations persistently surpassed adult levels (ratio serum IgG spike children vs. adults 90 days PSO 1.75, P P = 0.01; 270 days 1.54, P = 0.001). In a low-incidence setting, SARS-CoV-2 infection and humoral immune response present distinct patterns in children including higher antibody levels, and lower seroprevalence in families with pediatric index cases. Children show long-term SARS-CoV-2 antibody responses. These findings are relevant to novel variants with increased disease burden in children, as well as for the planning of age-appropriate vaccination strategies.

INTRODUCTION Th17 cells can either be identified by co-staining of surface markers or by intracellular cytokine staining (ICS) for IL-17 production. Discrepancies regarding the published frequencies of Th17 cells in peripheral blood mononuclear cells (PBMC) of HIV patients may partly be due to the different methodologies used. METHODS Cryopreserved PBMC from healthy controls and HIV-infected subjects, including treated (cART) and viremic patients, were split and analyzed side-by-side by flow cytometry for expression of surface markers CCR6, CXCR3, CCR4, and CD161, or for intracellular expression of IL-17A and IFNγ after stimulation. RESULTS The characterization of Th17 cells as CXCR3 - CCR6 + CCR4 + CD161+ yielded considerably higher frequencies than the corresponding frequencies obtained by characterization via cytokines (IL-17 + IFNγ-), regardless of the HIV status. However, the overall frequencies delivered by the two methods significantly correlated. The relative frequency of Th17 cells within the CD4+ T cell compartment was preserved in HIV infection but there was a significant decrease in the absolute Th17 number, which was restored after initiation of cART, paralleling CD4+ T cell recovery. Absolute Th17 numbers inversely correlated with HIV viral load. CONCLUSION The definition of Th17 cells by surface markers might overestimate their frequency in comparison to functional assessment of IL-17 production by ICS, regardless of the HIV infection status. However, both methods yield proportionate results with reduced absolute numbers of Th17 cells in untreated HIV disease, reflecting the depletion of total CD4+ T cells in viremic HIV patients, and restoration with cART. © 2016 International Clinical Cytometry Society.

Recently, CD32 has been described to be a specific surface marker of latently HIV-infected CD4 T cells, but little is known about the frequency and distribution of CD32 expression on naive and memory CD8 and CD4 T cell populations in HIV patients and healthy individuals.We studied peripheral blood samples of 36 HIV-1-infected patients [23 viremic patients / 13 antiretroviral therapy(ART)-treated] and healthy individuals (n = 14) as well as cells from lymph nodes (8 HIV infected, 5 controls) using a multiparametric flow cytometry panel determining surface expression of CD3, CD8, CD4, CD45RA, CCR7, CD27, CD25, CD127, CCR5, CCR6, CXCR4, CD38, HLA-DR, TIGIT, and PD-1.Overall, expression of CD32 on total peripheral CD4 T cells between viremic HIV patients, ART-treated and healthy individuals only slightly differed (mean values 1.501%, 0.2785%, and 0.2343%, respectively). However, the level of expression was significantly higher in peripheral and lymph nodal memory CD4 T cell subpopulations of viremic patients compared with ART-treated patients and healthy controls. CD32 CD4 T cells showed higher immune activation and higher expression of CXCR4 than their CD32 counterparts. Furthermore, expression of CD32 on total CD4 T cells and memory T cell populations correlated with general immune activation regardless of the infection status.Follow-up studies will have to further evaluate CD32 as marker of latently HIV-infected CD4 T cells since other host-related variables such as immune activation seem to influence CD32 expression regardless of the infection status.

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