Phenotypic analysis of the pediatric immune response to SARS-CoV-2 by flow cytometry

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Erscheinungsjahr:
2022
Medientyp:
Text
Beschreibung:
  • 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.

Lizenz:
  • info:eu-repo/semantics/openAccess
Quellsystem:
Forschungsinformationssystem des UKE

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oai:pure.atira.dk:publications/baf59674-891a-4b36-b59e-25f0963546b6