Analysing Pediatric Immune Response to SARS-CoV -2 Using Flow Cytometry

COVID-19 in children

The COVID-19 pandemic has impacted every country in the world. In adults, 10-20% of the patients develop severe or life-threatening disease. However, in children, most patients display only minor symptoms and so their contributions to spreading the SARS-CoV-2 virus is unclear.¹ The immune response of children has been under-studied compared to adults, and an understanding of how the immune system clears the virus without adverse symptoms may provide clues on how to treat adult patients.¹

Study of pediatric COVID-19 using flow cytometry

In this research study, Sibbertsen F, et.al have attempted to rapidly analyze the frequencies of lymphoid and myeloid cell populations, and the differentiation stages of lymphocytes in paediatric samples of peripheral blood mononuclear cells (PBMCs) using flow cytometry. The authors aimed to establish and evaluate flow panels with robust performance in both classic gating as well as the state-of-the-art flow bioinformatic approaches like unbiased clustering and visualization by Uniform Manifold Approximation and Projection (UMAP) analysis.

Methods

The authors used blood samples drawn into EDTA tubes and separated the PBMCs using the manufacturer’s instructions. The PBMCs were cryopreserved and stored in liquid nitrogen till analysis.

Two different panels, T and B, were created by the authors. The goal of the panel T (16 parameters) was to identify key functional subsets and differential stages of T cells, while the panel B (17 parameters) included markers for B cell subpopulations and innate cell subsets. The data was collected on a BD FACSymphony™ A3 flow cytometer, using FACSDiva™ Software Version 9.1.

Summary of the results

The study resulted in the identification of 14 predefined subpopulations of interest for panel T and 19 for panel B in low-volume paediatric samples using classical manual gating of known populations. In parallel, the authors performed unbiased clustering using the R-based algorithm PhenoGraph. Using this approach, they found 18 clusters within the T cell panel and 21 within the B cell and innate panel that could be clearly annotated.

According to the authors, the two panels allow for a broad assessment of innate and adaptive immune systems, while also identifying small subpopulations with possible relevance in children and SARS-CoV-2 infection such as ILCs, pharmablasts, recent thymic emigrants, CD4+ and CX3CR1+ CD8+ T cells.¹

Read the Cytometry article: Phentoypic analysis of the pediatric immune response to SARS-CoV-2 by flow cytometry.