Single-cell characterization of a model of poly I:C-stimulated peripheral blood mononuclear cells in severe asthma

Abstract

Background: Asthma has been associated with impaired interferon response. Multiple cell types have been implicated in such response impairment and may be responsible for asthma immunopathology. However, existing models to study the immune response in asthma are limited by bulk profiling of cells. Our objective was to Characterize a model of peripheral blood mononuclear cells (PBMCs) of patients with severe asthma (SA) and its response to the TLR3 agonist Poly I:C using two single-cell methods.

Methods: Two complementary single-cell methods, DropSeq for single-cell RNA sequencing (scRNA-Seq) and mass cytometry (CyTOF), were used to profile PBMCs of SA patients and healthy controls (HC). Poly I:C-stimulated and unstimulated cells were analyzed in this study.

Results: PBMCs (n = 9414) from five SA (n = 6099) and three HC (n = 3315) were profiled using scRNA-Seq. Six main cell subsets, namely CD4 + T cells, CD8 + T cells, natural killer (NK) cells, B cells, dendritic cells (DCs), and monocytes, were identified. CD4 + T cells were the main cell type in SA and demonstrated a pro-inflammatory profile characterized by increased JAK1 expression. Following Poly I:C stimulation, PBMCs from SA had a robust induction of interferon pathways compared with HC. CyTOF profiling of Poly I:C stimulated and unstimulated PBMCs (n = 160,000) from the same individuals (SA = 5; HC = 3) demonstrated higher CD8 + and CD8 + effector T cells in SA at baseline, followed by a decrease of CD8 + effector T cells after poly I:C stimulation.

Conclusions: Single-cell profiling of an in vitro model using PBMCs in patients with SA identified activation of pro-inflammatory pathways at baseline and strong response to Poly I:C, as well as quantitative changes in CD8 + effector cells. Thus, transcriptomic and cell quantitative changes are associated with immune cell heterogeneity in this model to evaluate interferon responses in severe asthma.

Fig. 1

Study workflow

Fig. 2

Single-cell RNAseq of PMBCs Identifies Distinct Clusters of Cells. a Top ten cluster markers for the five main cell types in all cells (n = 9390). b UMAP of all cell clusters including dendritic cells (n = 9414). c UMAP of all cell clusters by disease status, severe asthma (SA) (n = 6099) and healthy control (HC) (n = 3315). This figure demonstrates a similar distribution of cells across patients with severe asthma and healthy controls. d UMAP of all cell clusters by stimulation status, unstimulated (n = 4283) and poly I:C (n = 5131). This figure demonstrates a similar distribution of unstimulated and poly I:C stimulated cells

Fig. 3

Single-cell RNAseq of unstimulated cells. a UMAP of unstimulated PBMCs demonstrates a similar distribution of cells between severe asthma (SA) and healthy controls (HC). b Several pro-inflammatory transcripts including JAK1, IL7R, CCL4, NEAT1, CCL5, IL32, CFL1, and ACTG1 are highly expressed in cells from patients with SA (blue) compared to HC (orange). c Expression of the anti-inflammatory transcripts CMKLR1 and CD300LF were lower in SA than HC

Fig. 4

Single-cell RNAseq of PBMCs stimulated with poly I:C. a Poly I:C stimulation led to a robust increase in the expression of STAT1 and multiple interferon-stimulated genes in SA. b Genes involved in antigen presentation, including HLA-DRA, IGKC, IGHM, and CD74 had a heterogeneous expression across cell types and between SA and HC. Similarly, genes involved in ubiquitination and unfolded protein response also demonstrated a heterogeneous response across cells and disease status

Fig. 5

Pseudotime analysis of CD4 + T cells demonstrated a strong association with interferon signaling in severe asthma. a PHATE analysis for pseudotemporal reconstruction of CD4 + T cells. b Heatmap of transcripts correlated with pseudotime identified multiple interferon-stimulated genes correlated with the response to poly I:C. c Regulon analysis identified IRF1, STAT1, IRF7, STAT2, and IRF9 as the top five transcription factors positively correlated with pseudotime and critical regulators of positively correlated genes in response to poly I:C

Fig. 6

CyTOF analysis of PBMCs from the same subjects profiled with single-cell RNAseq identifies a similar distribution of cells. a tSNE plot of cell clusters on CyTOF. b Heatmap of cell surface markers and clusters determined by CyTOF. This is a simplified version of all the clustering results; the Additional file 2: Figure S2 includes all clusters. CD4 cells, together with CD4 effector cells (CD4 Eff), CD4 memory (CD4 Mem), CD4-Th1, and CD4-Th17 cells, are clustered independently from B cells, natural killer (NK), dendritic cells (DCs). CD8 cells are also clustered independently and include CD8 effector (CD8 Eff), CD8 central memory (CD8 Tcm), CD8 naïve and memory (CD8 N&M), CD8-low cells, and CD8 cells. A small subset of Cytokine-induced killer cells (CIK) was identified in this analysis