Single-Cell Analysis Reveals the Immune Characteristics of Myeloid Cells and Memory T Cells in Recovered COVID-19 Patients With Different Severities

Abstract

Despite many studies on the immune characteristics of Coronavirus disease 2019 (COVID-19) patients in the progression stage, a detailed understanding of pertinent immune cells in recovered patients is lacking. We performed single-cell RNA sequencing on samples from recovered COVID-19 patients and healthy controls. We created a comprehensive immune landscape with more than 260,000 peripheral blood mononuclear cells (PBMCs) from 41 samples by integrating our dataset with previously reported datasets, which included samples collected between 27 and 47 days after symptom onset. According to our large-scale single-cell analysis, recovered patients, who had severe symptoms (severe/critical recovered), still exhibited peripheral immune disorders 1-2 months after symptom onset. Specifically, in these severe/critical recovered patients, human leukocyte antigen (HLA) class II and antigen processing pathways were downregulated in both CD14 monocytes and dendritic cells compared to healthy controls, while the proportion of CD14 monocytes increased. These may lead to the downregulation of T-cell differentiation pathways in memory T cells. However, in the mild/moderate recovered patients, the proportion of plasmacytoid dendritic cells increased compared to healthy controls, accompanied by the upregulation of HLA-DRA and HLA-DRB1 in both CD14 monocytes and dendritic cells. In addition, T-cell differentiation regulation and memory T cell-related genes FOS, JUN, CD69, CXCR4, and CD83 were upregulated in the mild/moderate recovered patients. Further, the immunoglobulin heavy chain V3-21 (IGHV3-21) gene segment was preferred in B-cell immune repertoires in severe/critical recovered patients. Collectively, we provide a large-scale single-cell atlas of the peripheral immune response in recovered COVID-19 patients.

Keywords: HLA class II; disease severity; memory T cells; myeloid cells; recovered COVID-19 patients.

Figure 1

Single-cell atlas of recovered COVID-19 patients and healthy controls. (A) Flowchart depicting the overall design of the study. (B) UMAP presentation of the integrated single-cell transcriptomes of cells derived from recovered COVID-19 patients and healthy controls. (C) Box plots show the comparative analysis of the percentage of major cell types in PBMC cells. NK, natural killer cells; Mono, monocytes; DC, dendritic cells. T test with healthy, *p < 0.05, **p < 0.01.

Figure 2

Single-cell transcriptome characteristics of the myeloid immune response in recovered COVID-19 patients. (A) Boxplots depicting percentages of multiple cell types in PBMC cells, colored by group-specific color. T tests (and non-parametric tests), *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. (B) The box plots show the cell subtype proportions in different genders. (C) The correlation analysis charts show the correlation between patient age and cell subtype proportions (Spearman’s correlation). (D) UMAPs of PBMC cells colored by inflammatory score (top panel) and HLA_class II score (bottom panel). (E) Box plots show the inflammatory score (top panel) and HLA_class II score ​(bottom panel) of subtypes from healthy controls (n = 19), mild/moderate recovered (n=16), severe/critical recovered (n=6) patients. Significance was evaluated with T tests (and non-parametric tests), for each subtype versus healthy controls. (F) Dot plots depict enriched signaling pathways in different serious groups in CD14 monocytes and pDCs. The number in parentheses represents the number of genes with significant differences. Mono, monocytes; pDCs, plasmacytoid dendritic cells; HC, healthy control; MR, mild/moderate recovered; SR, severe/critical recovered. T tests (and non-parametric tests), *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Figure 3

Single-cell transcriptome characteristics of the T and NK cell immune response in recovered COVID-19 patients. (A) Boxplots depicting percentages of T cell subtypes in PBMC cells, colored by group-specific color. (B) Heatmap visualization of average mRNA expression levels of the differential genes in three severity groups in T and NK cell subtypes. (C) Dot plot depicting enriched signaling pathways in different serious groups in CD4m T and CD8m T(GZMK). HC, healthy control; MR, mild/moderate recovered; SR, severe/critical recovered. The number in parentheses represents the number of genes with significant differences. (D) Boxplots of the gene expression of CD4m T(GZMK) cluster from healthy controls (n = 19), mild/moderate recovered (n = 16), severe/critical recovered (n = 6) patients. T tests (and non-parametric tests), *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Figure 4

Distribution of BCR/TCR expanded clonotypes and associations of patient age and COVID-19 severity with the diversity of B and T cell repertoires. (A) UMAPs embedding of T/B cells colored by the density of cells characterized by different clonal expansion sizes (n = 1, n = 2-4, and n > = 5). Shown separately in different COVID-19 severity. (B) Column charts of T/B cell subpopulation composition of expanded TCR/BCR clones. (C) Box plots show characterization and comparison of TCR clonal expansion among severe/critical recovered patients (SR), mild/moderate recovered patients (MR), and healthy controls (HC), by quantifying the ratio of expanded clones. (D) The correlation analysis charts show the correlation between patient age and the BCR/TCR diversity of CD8m T(GZMH), CD8m T(GZMK), Prolif T, Memory B, and Plasma (Spearman’s correlation). (E) Box plots show the BCR/TCR diversity of CD8m T(GZMH), CD8m T(GZMK), Prolif T, Memory B, and Plasma among severe/critical recovered patients (SR), mild/moderate recovered patients (MR), and healthy controls (HC). The chao1 method in R-package Immunarch was used to evaluate repertoire diversity.

Figure 5

The interactions of monocyte, DC, NK, and CD4+/CD8+ memory T cell. (A) Heatmaps showing the overall signaling associated with each cell subtype. ​For each signaling pathway considered for the cell–cell interaction analysis using CellChat (see Methods ), we can compare the aggregated incoming and outgoing signaling for each cell subtype in each severity. The top barplot represents the total non-normalized signaling for each cell subpopulation, while the right barplot represents the total log-normalized signaling for each pathway. (B) Circos plot showing the prioritized interactions mediated by ligand-receptor pairs between different cell types. HC, healthy control; MR, mild/moderate recovered; SR, severe/critical recovered; DC, dendritic cells; Mono, monocytes; NK, natural killer cells. (C) Summary illustration comparing the list of HLA genes and inflammatory genes that were upregulated or downregulated in mild/moderate recovery (MR) and severe/critical recovery (SR) compared to healthy controls (HC) in T cells, DCs, and monocytes.