TREM2+ and interstitial-like macrophages orchestrate airway inflammation in SARS-CoV-2 infection in rhesus macaques

Abstract

The immunopathological mechanisms driving the development of severe COVID-19 remain poorly defined. Here, we utilize a rhesus macaque model of acute SARS-CoV-2 infection to delineate perturbations in the innate immune system. SARS-CoV-2 initiates a rapid infiltration of plasmacytoid dendritic cells into the lower airway, commensurate with IFNA production, natural killer cell activation, and a significant increase of blood CD14^-CD16⁺ monocytes. To dissect the contribution of lung myeloid subsets to airway inflammation, we generate a longitudinal scRNA-Seq dataset of airway cells, and map these subsets to corresponding populations in the human lung. SARS-CoV-2 infection elicits a rapid recruitment of two macrophage subsets: CD163⁺MRC1^-, and TREM2⁺ populations that are the predominant source of inflammatory cytokines. Treatment with baricitinib (Olumiant®), a JAK1/2 inhibitor is effective in eliminating the influx of non-alveolar macrophages, with a reduction of inflammatory cytokines. This study delineates the major lung macrophage subsets driving airway inflammation during SARS-CoV-2 infection.

Fig. 1. Early expansion of inflammatory cells in the blood following infection with SARS-CoV-2.

a Study design; RMs were infected intranasally and intratracheally with SARS-CoV-2 and tracked longitudinally (Cohort 1: n = 4, baricitnib cohort: n = 4, Cohort 2: n = 6). Baricitinib was administered daily to 4 RMs (baricitinib cohort) starting at 2 dpi. The 4 RMs  from Cohort 1 and 6 RMs from Cohort 2 were untreated. (Created with BioRender.com). b After SARS-CoV-2 inoculation, nasal, throat, and bronchoalveolar lavages (BAL) were collected and viral loads were quantified by qRT-PCR for total gRNA and sgRNA. c Longitudinal levels of monocytes within BAL and blood depicted as a % of CD45+ cells. p values: CD14−CD16+ Monocytes Blood: 1 dpi vs. −5 dpi = 0.03 and 2 dpi vs. −5 dpi = 0.004; CD14+CD16+ Monocytes Blood 2 dpi vs. −5 dpi = 0.004. d Longitudinal levels of plasmacytoid dendritic cells (pDCs) within BAL and blood depicted as a percentage of CD45+ cells. p value for pDCs Blood 2 dpi vs. −5 dpi = 0.02. e Longitudinal levels of NK cells expressing Granzyme B in BAL and blood. p values for Granzyme B+ NK Cells 2 dpi vs. −5 dpi BAL = 0.01 and blood = 0.008. n = 8 RM from Cohort 1 and baricitinib cohort. The red bars represent the mean. Statistical analysis was performed using one-tailed Wilcoxon signed-rank test in Graphpad Prism v7.02 comparing each timepoint to −5 dpi. *p value <0.05, **p value <0.01. Source data (b–e) are provided as a Source Data file.

Fig. 2. Early pro-inflammatory and ISG response observed in airways and peripheral blood by bulk transcriptomics.

n = 8 RM from Cohort 1 and baricitinib cohort for −5 dpi and 2 dpi except for (c) where n = 6 (3 RM Cohort 1 + 3 RM baricitnib cohort) at 2 dpi. n = 4 RM from Cohort 1 starting from 4 dpi. a Dot plots showing normalized enrichment scores and nominal p values for gene sets. Enrichment is indicated by dot color (red: positively enriched vs. −5 dpi; blue: negatively enriched), dot size indicates significance. Normalized enrichment scores and nominal p values were determined using GSEA. The exact nominal p values are included in Supplementary Data 1. b Heatmap of longitudinal responses for the ISG gene set. The color scale indicates log2 expression relative to the median of the −5 dpi samples. c Cytokines evaluation (Mesoscale) in BALF p values for 2 dpi vs. −5 dpi: IL6 = 0.02 and IP-10 = 0.03 and d Plasma; only significant cytokines are shown (p values for 2 dpi vs. −5 dpi: IP-10 = 0.008, MCP-1 = 0.008, MCP-2 = 0.004). e Sum of normalized expression of all IFNA genes in BAL. *p value = 0.04. f GSEA enrichment plot showing negative enrichment for AM gene signature (derived from SingleR) when comparing bulk BAL RNA-Seq samples from 4 dpi to −5 dpi (Nominal p value = 0). The red bar represents the mean. Statistical analysis for (c)–(e) was performed using one-tailed Wilcoxon signed-rank test in R v4.2.2 comparing each timepoint to −5 dpi. *p value <0.05, **p value <0.01. Source data (c–e) are provided as a Source Data file.

Fig. 3. Influx of pro-inflammatory macrophages in BAL.

a Projection of single-cell macrophages/monocytes from −5 dpi (green) and 4 dpi (magenta) 10X BAL samples obtained from three SARS-CoV-2 infected rhesus macaques (Cohort 1) onto the reference UMAP of lung macrophage/monocytes from uninfected rhesus macaques (NCBI GEO: GSE149758). b UMAP projections showing the predicted cell type annotations based on the uninfected lung reference split by time of sample collection (Cohort 1). c DotPlots showing the expression of marker genes for the different macrophage/monocyte subsets in SARS-CoV-2 infected BAL samples (Cohort 1). d Log2 fold-changes compared to −5 dpi for APOBEC3A, CHIT1 and MARCO in bulk BAL RNA-Seq data (Cohort 1). Significance was determined using DESeq2. The p values corrected by the default Benjamini and Hochberg method were used *adj p value <0.05, ***adj p value <0.001. The exact p values are included in Supplementary Data 2. Percentage of a given subset out of all macrophage/monocyte subsets at −5 dpi and 4 dpi from all three animals pooled (Cohort 1) (e) and at −7 dpi and 4 dpi from all six animals pooled (Cohort 2) (f). Percentage of a given subset out of all macrophage/monocyte subsets for each animal at −5 dpi and 4 dpi from Cohort 1 (n = 3) (g) and at −7 dpi (n = 5) and 4 dpi (n = 6) for Cohort 2 (h). The black lines indicate the median. p values for Cohort 2 (f) for 4 dpi vs. −7 dpi: CD163+MRC1+ = 0.009, CD163+MRC1+TREM2+ = 0.03, and CD163+MRC1− = 0.004. Contribution of each macrophage/monocyte subset toward the production of the pro-inflammatory genes and ISG—Cohort 1 pooled (i), Cohort 2 pooled (j), Cohort 1 individual (k) and Cohort 2 individual (l). p values for (l): * = 0.03. The percentage contribution was calculated by dividing the sum of normalized expression of a given gene in a macrophage/monocyte subset by the sum of the normalized expression of the gene in all macrophage/monocyte subsets. a–c, e, g, i, k Cohort 1: n = 3 for both −5 dpi and 4 dpi, d Cohort 1: n = 8 for 2 dpi and n = 4 for 4 dpi, f, h, j, l Cohort 2: n = 5 for −7 dpi and n = 6 for 4 dpi. The black lines indicate the median. Statistical analysis was performed using two-tailed Wilcoxon singed rank test for (g, k, l) and two-tailed Mann–Whitney U test for (h) in R v4.2.2. *p value <0.05, **p value <0.01. Source data (d–l) are provided as a Source Data file.

Fig. 4. Comparison of rhesus and human macrophage subsets.

a UMAP of macrophage subsets in lungs from six healthy human donors (GEO: GSE135893). b UMAP of macrophage subsets in lungs from three healthy rhesus macaques (GEO: GSE149758). c DotPlots showing the expression of marker genes. The color gradient represents the level of expression and the size of the dot represents the percentage of cells expressing a given gene. d UMAP of BAL samples from human donors that are healthy (n = 3), or suffering from moderate (n = 3) or severe (n = 6) COVID-19 (GEO: GSE145926) mapped to the healthy lung reference using the Seurat MapQuery function. e Percent of predicted cell types out of all macrophage/monocytes in each human BAL sample. The black bar indicates the median. Statistical analysis was performed using pairwise two-tailed Mann–Whitney U test in R v4.2.2. p value * = 0.02. Contribution of each predicted macrophage/monocyte subsets in human BAL toward the production of the pro-inflammatory genes and ISG—pooled (f) and individual (g). The percentage contribution was calculated by dividing the sum of normalized expression of a given gene in a macrophage/monocyte subset by the sum of the normalized expression of the gene in all macrophage/monocyte subsets. The black bars represent the median. Statistical analysis was performed using two-tailed Wilcoxon signed rank test in R v4.2.2. *p value 0.03 for all except FABP4 vs. Proliferating for IL6, IL1B, TNF, CXCL3, CXCL8 and SPP1hi vs. Proliferating for CCR2: p value = 0.04. Source data (e–g) are provided as a Source Data file.

Fig. 5. Baricitinib reduced the influx of pro-inflammatory macrophages in addition to the pro-inflammatory gene expression profile.

a Projection of macrophages/monocytes from −5 dpi and 4 dpi 10X BAL samples from three untreated and two baricitinib-treated rhesus macaques on the reference UMAP of uninfected lung macrophages/monocytes (NCBI GEO: GSE149758). b UMAP split by treatment and timepoint showing predicted cell annotations based on mapping to the reference lung macrophages/monocytes. Percentage of a given macrophage/monocyte subset of all the macrophages/monocytes in the BAL samples—pooled (c) and individual (d). Violin plots showing expression of pro-inflammatory cytokines (e), chemokines (f) and ISG (g) in the different macrophage/monocyte subsets in BAL 10X samples from baricitinib-treated and untreated samples. h Absolute number of pDC in BAL samples from scRNA-Seq and i Percentage of pDC out of all cells in the BAL samples from scRNA-Seq. Source data (c, d, h, i) are provided as a Source Data file.